Levels of Information Processing in a Fitts law task (LIPFitts)

State-of-the-art flight technology has restructured the task of human operators, decreasing the need for physical and sensory resources, and increasing the quantity of cognitive effort required, changing it qualitatively. Recent technological advances have the most potential for impacting a pilot in two areas: performance and mental workload. In an environment in which timing is critical, additional cognitive processing can cause performance decrements, and increase a pilot's perception of the mental workload involved. The effects of stimulus processing demands on motor response performance and subjective mental workload are examined, using different combinations of response selection and target acquisition tasks. The information processing demands of the response selection were varied (e.g., Sternberg memory set tasks, math equations, pattern matching), as was the difficulty of the response execution. Response latency as well as subjective workload ratings varied in accordance with the cognitive complexity of the task. Movement times varied according to the difficulty of the response execution task. Implications in terms of real-world flight situations are discussed

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools II: Contextual Constraints and Information Sources

Recent advances in artificial intelligence, machine learning, data mining and sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the second of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explored fundamental issues associated with the development of such a system. In this report, we extend this work to focus on two critical aspects of these systems: 1) the constraints and conditions that drive the dynamic prioritization and presentation of data and information to the pilots, and 2) specific data and information to be accessed, monitored, integrated, and displayed in such a system

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems

Fludarabine as a cost-effective adjuvant to enhance engraftment of human normal and malignant hematopoiesis in immunodeficient mice

There is still an unmet need for xenotransplantation models that efficiently recapitulate normal and malignant human hematopoiesis. Indeed, there are a number of strategies to generate humanized mice and specific protocols, including techniques to optimize the cytokine environment of recipient mice and drug alternatives or complementary to the standard conditioning regimens, that can be significantly modulated. Unfortunately, the high costs related to the use of sophisticated mouse models may limit the application of these models to studies that require an extensive experimental design. Here, using an affordable and convenient method, we demonstrate that the administration of fludarabine (FludaraTM) promotes the extensive and rapid engraftment of human normal hematopoiesis in immunodeficient mice. Quantification of human CD45+ cells in bone marrow revealed approximately a 102-fold increase in mice conditioned with irradiation plus fludarabine. Engrafted cells in the bone marrow included hematopoietic stem cells, as well as myeloid and lymphoid cells. Moreover, this model proved to be sufficient for robust reconstitution of malignant myeloid hematopoiesis, permitting primary acute myeloid leukemia cells to engraft as early as 8 weeks after the transplant. Overall, these results present a novel and affordable model for engraftment of human normal and malignant hematopoiesis in immunodeficient mice

Methoxy-substituted 9-aminomethyl-9,10-dihydroanthracene (AMDA) derivatives exhibit differential binding affinities at the 5-HT2A receptor

The effects of methoxy-substitution at the 1-, 2-, 3- and 4-positions of 9-aminomethyl-9,10-dihydroanthracene (AMDA) on h5-HT2A receptor affinity were determined. Racemic mixtures of these compounds were found to show the following affinity trend: 3-MeO > 4-MeO > 1-MeO ~ 2-MeO. Comparison of the effects of these substitutions, with the aid of computational molecular modeling techniques, suggest that the various positional and stereochemical isomers of the methoxy-substituted AMDA compounds interact differently with the h5-HT2A receptor. It is predicted that for the compounds with higher affinities, the methoxy oxygen atom is able to interact with hydrogen bond-donating sidechains within alternative h5-HT2A receptor binding sites, whereas the lower-affinity isomers lack this ability

Michael acceptor approach to the design of new salvinorin A-based high affinity ligands for the kappa-opioid receptor

The neoclerodane diterpenoid salvinorin A is a major secondary metabolite isolated from the psychoactive plant Salvia divinorum. Salvinorin A has been shown to have high affinity and selectivity for the κ-opioid receptor (KOR). To study the ligand–receptor interactions that occur between salvinorin A and the KOR, a new series of salvinorin A derivatives bearing potentially reactive Michael acceptor functional groups at C-2 was synthesized and used to probe the salvinorin A binding site. The κ-, δ-, and μ-opioid receptor (KOR, DOR and MOR, respectively) binding affinities and KOR efficacies were measured for the new compounds. Although none showed wash-resistant irreversible binding, most of them showed high affinity for the KOR, and some exhibited dual affinity to KOR and MOR. Molecular modeling techniques based on the recently-determined crystal structure of the KOR combined with results from mutagenesis studies, competitive binding, functional assays and structure–activity relationships, and previous salvinorin A–KOR interaction models were used to identify putative interaction modes of the new compounds with the KOR and MOR

A Study of Brain Networks Associated with Swallowing Using Graph-Theoretical Approaches

Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI) was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, 23.1±1.52 years of age). To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia. © 2013 Luan et al

Communication Biophysics

Contains reports on five research projects.National Institutes of Health (Grant 5 RO1 NB-05462-02)National Aeronautics and Space Administration (Grant NsG-496)National Science Foundation (Grant GP-2495)National Institutes of Health (Grant MH-04737-05

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Nitrate stable isotopes and major ions in snow and ice samples from four Svalbard sites

Increasing reactive nitrogen (N-r) deposition in the Arctic may adversely impact N-limited ecosystems. To investigate atmospheric transport of N-r to Svalbard, Norwegian Arctic, snow and firn samples were collected from glaciers and analysed to define spatial and temporal variations (1 10 years) in major ion concentrations and the stable isotope composition (delta N-15 and delta O-18) of nitrate (NO3-) across the archipelago. The delta N-15(NO3-) and delta O-18(NO3-) averaged -4 parts per thousand and 67 parts per thousand in seasonal snow (2010-11) and -9 parts per thousand and 74 parts per thousand in firn accumulated over the decade 2001-2011. East-west zonal gradients were observed across the archipelago for some major ions (non-sea salt sulphate and magnesium) and also for delta N-15(NO3-) and delta O-18(NO3-) in snow, which suggests a different origin for air masses arriving in different sectors of Svalbard. We propose that snowfall associated with long-distance air mass transport over the Arctic Ocean inherits relatively low delta N-15(NO3-) due to in-transport N isotope fractionation. In contrast, faster air mass transport from the north-west Atlantic or northern Europe results in snowfall with higher delta N-15(NO3-) because in-transport fractionation of N is then time-limited