Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here by permission of Taylor & Francis for personal use, not for redistribution. The definitive version was published in Journal of Operational Oceanography 10 (2017): 115-126, doi:10.1080/1755876X.2017.1322026.This paper outlines strategies that would advance coastal ocean modeling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the U.S. Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of U.S. based researchers with a cross-section of coastal oceanography and ocean modeling expertise and community representation drawn from Regional and U.S. Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modeling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3-8 year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, U.S. Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal-academic partnerships benefiting IOOS stakeholders and end users.2018-05-2

Autonomous and Lagrangian ocean observations for Atlantic tropical cyclone studies and forecasts

Author Posting. © The Oceanography Society, 2017. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 30, no. 2 (2017): 92–103, doi:10.5670/oceanog.2017.227.The tropical Atlantic basin is one of seven global regions where tropical cyclones (TCs) commonly originate, intensify, and affect highly populated coastal areas. Under appropriate atmospheric conditions, TC intensification can be linked to upper-ocean properties. Errors in Atlantic TC intensification forecasts have not been significantly reduced during the last 25 years. The combined use of in situ and satellite observations, particularly of temperature and salinity ahead of TCs, has the potential to improve the representation of the ocean, more accurately initialize hurricane intensity forecast models, and identify areas where TCs may intensify. However, a sustained in situ ocean observing system in the tropical North Atlantic Ocean and Caribbean Sea dedicated to measuring subsurface temperature, salinity, and density fields in support of TC intensity studies and forecasts has yet to be designed and implemented. Autonomous and Lagrangian platforms and sensors offer cost-effective opportunities to accomplish this objective. Here, we highlight recent efforts to use autonomous platforms and sensors, including surface drifters, profiling floats, underwater gliders, and dropsondes, to better understand air-sea processes during high-wind events, particularly those geared toward improving hurricane intensity forecasts. Real-time data availability is key for assimilation into numerical weather forecast models.The NOAA/AOML component of this work was originally funded by the Disaster Relief Appropriations Act of 2013, also known as the Sandy Supplemental, and is currently funded through NOAA research grant NA14OAR4830103 by AOML and CARICOOS, as well as NOAA’s Integrated Ocean Observing System (IOOS). The TEMPESTS component of this work is supported by NOAA through the Cooperative Institute for the North Atlantic Region (NA13OAR4830233) with additional analysis support from the WHOI Summer Student Fellowship Program, Nortek Student Equipment Grant, and the Rutgers University Teledyne Webb Graduate Student Fellowship Program. The drifter component of this work is funded through NOAA grant NA15OAR4320071(11.432) in support of the Global Drifter Program

Mental health in the aged: prevalence, covariates and related neuroendocrine, cardiovascular and inflammatory factors of successful aging

<p>Abstract</p> <p>Background</p> <p>Although aging is accompanied by diminished functioning, many elderly individuals preserve a sense of well-being. While the concept of "successful aging" has been popular for many decades, little is known about its psycho-physiologic and endocrine underpinnings. KORA-Age is a population-based, longitudinal study designed to determine the prevalence of successfully aged men and women between 65 and 94 years old in the MONICA/KORA Augsburg cohort of randomly selected inhabitants. Specifically, we aim to identify predictors of successful aging and to elucidate bio-psychosocial mechanisms that maintain mental health and successful adaptation despite adverse experiences of life and aging.</p> <p>Methods/Design</p> <p>Components of successful aging were assessed in a telephone survey of 4,127 participants (2008-2009) enrolled in the MONICA/KORA cohort, on average, 13 years earlier. Psychosocial, somatic and behavioural predictors are used to determine factors that contribute to successful aging. An age-stratified random sub-sample (n = 1,079) participated in a personal interview where further psychological mechanisms that may underlie successful adaptation (resilience, social support, attachment) were examined. The interactions among neuroendocrine systems in the aging process are investigated by studying the cortisol/dehydroepiandrosterone-sulfate ratio, the level of insulin-like growth factor I, and oxytocin.</p> <p>Discussion</p> <p>Longitudinal determinants of successful aging can be assessed based on a follow-up of an average of 13 years. A comprehensive analysis of biological as well as physio-psychological information provides a unique opportunity to investigate relevant outcomes such as resilience and frailty in the elderly population.</p

Cognitive and Tactile Factors Affecting Human Haptic Performance in Later Life

Background: Vision and haptics are the key modalities by which humans perceive objects and interact with their environment in a target-oriented manner. Both modalities share higher-order neural resources and the mechanisms required for object exploration. Compared to vision, the understanding of haptic information processing is still rudimentary. Although it is known that haptic performance, similar to many other skills, decreases in old age, the underlying mechanisms are not clear. It is yet to be determined to what extent this decrease is related to the age-related loss of tactile acuity or cognitive capacity. Methodology/Principal Findings: We investigated the haptic performance of 81 older adults by means of a cross-modal object recognition test. Additionally, we assessed the subjects ’ tactile acuity with an apparatus-based two-point discrimination paradigm, and their cognitive performance by means of the non-verbal Raven-Standard-Progressive matrices test. As expected, there was a significant age-related decline in performance on all 3 tests. With the exception of tactile acuity, this decline was found to be more distinct in female subjects. Correlation analyses revealed a strong relationship between haptic and cognitive performance for all subjects. Tactile performance, on the contrary, was only significantly correlated with male subjects ’ haptic performance. Conclusions: Haptic object recognition is a demanding task in old age, especially when it comes to the exploration o

Associations between a polymorphism in the pleiotropic GCKR and Age-related phenotypes: the HALCyon programme.

Background: The glucokinase regulatory protein encoded by GCKR plays an important role in glucose metabolism and a single nucleotide polymorphism (SNP) rs1260326 (P446L) in the gene has been associated with several age-related biomarkers, including triglycerides, glucose, insulin and apolipoproteins. However, associations between SNPs in the gene and other ageing phenotypes such as cognitive and physical capability have not been reported. Methods: As part of the Healthy Ageing across the Life Course (HALCyon) collaborative research programme, men and women from five UK cohorts aged between 44 and 90+ years were genotyped for rs1260326. Meta-analysis was used to pool within-study genotypic associations between the SNP and several age-related phenotypes, including body mass index (BMI), blood lipid levels, lung function, and cognitive and physical capability. Results: We confirm the associations between the minor allele of the SNP and higher triglycerides and lower glucose levels. We also observed a triglyceride-independent association between the minor allele and lower BMI (pooled beta on zscore = 20.04, p-value = 0.0001, n = 16,251). Furthermore, there was some evidence for gene-environment interactions, including physical activity attenuating the effects on triglycerides. However, no associations were observed with measures of cognitive and physical capability. Conclusion: Findings from middle-aged to older adults confirm associations between rs1260326 GCKR and triglycerides and glucose, suggest possible gene-environment interactions, but do not provide evidence that its relevance extends to cognitive and physical capability

Exploratory Study of Executive Function Abilities Across the Adult Lifespan in Individuals Receiving an ASD Diagnosis in Adulthood

The few studies of autism spectrum disorder (ASD) across adulthood suggest different age-related associations in different aspects of executive function (EF). In this exploratory study we examined EF abilities and self-report autism traits in 134 adults (aged 18-75 years; mean=31 years) with abilities in the normal range, receiving a first diagnosis of ASD. Results suggest that in some EF relying on speed and sequencing (Trails A and B; Digit Symbol), late-diagnosed ASD individuals may demonstrate better performance than typical age-norms. On other EF (Digit Span, Hayling, Brixton tests) age-related correlations were similar to typical age-norms. Different domains of EF may demonstrate different trajectories for ageing with ASD, with patterns of slower, accelerated or equivalent age-related change observed across different measures

Exploratory Study of Executive Function Abilities Across the Adult Lifespan in Individuals Receiving an ASD Diagnosis in Adulthood

The few studies of autism spectrum disorder (ASD) across adulthood suggest different age-related associations in different aspects of executive function (EF). In this exploratory study we examined EF abilities and self-report autism traits in 134 adults (aged 18-75 years; mean=31 years) with abilities in the normal range, receiving a first diagnosis of ASD. Results suggest that in some EF relying on speed and sequencing (Trails A and B; Digit Symbol), late-diagnosed ASD individuals may demonstrate better performance than typical age-norms. On other EF (Digit Span, Hayling, Brixton tests) age-related correlations were similar to typical age-norms. Different domains of EF may demonstrate different trajectories for ageing with ASD, with patterns of slower, accelerated or equivalent age-related change observed across different measures

Observing system simulation experiments on the Oahu Regional Ocean Model

M.S. University of Hawaii at Manoa 2011.Includes bibliographical references.Observing system simulation experiments were conducted using the Oahu Regional Ocean Modeling System. A twin experiment was implemented in which synthetic observing systems were withheld to establish the impact of each observing system on 4-day ocean forecasts over a 6 month experiment period. Synthetic High Frequency(HF) Radar had significant impacts on the forecasts across the region. It provided a surface velocity constraint that influenced forecasts at depth and in areas of the region not directly surveyed by HF Radar. Additional analyses of the observing systems were conducted at the outflow plume depth of a potential pilot Ocean Thermal Energy Conversion (OTEC) site off the south coast of Oahu as well as the circulation of Mamala Bay. Synthetic satellite data had a positive impact on the temperature forecasts, especially in the island wake area, west of Oahu. Glider data from continuous synthetic runs between Makapu'u and Penguin Banks and data from a synthetic mooring stationed in the deepest part of the Ka'iwi Channel constrained the model well in the Ka'iwi Channel. They both showed positive impact on temperature and velocity forecasts near the Ka'iwi Channel

Glimpse on Women in Entrepreneurial Context

Female Entrepreneurship has gained interest over the last 20 years. Therefore, this paper analyses 7,320 articles of the research field ‘women in entrepreneurial context’ published in 885 journals. The sample is analyzed by using a machine learning and text mining based methodological approach. Aiming to provide a broad overview over the research literature, 41 clusters and 11 superordinate topics were identified. Major developments of research attention are outlined by analyzing bibliometric data of the period from 2000 to 2020. Overall growth in terms of research attention measured by the development of yearly citations per article is best noticeable in clusters ‘corporate social responsibility’, ‘brand’, and ‘corporate (-governance)’, and in superordinate topics ‘performance’, ‘education’, and ‘corporate (board/ management)’. There are also indicators for an overall increase of research attention and cluster variety. The synthesis provides an insight into most trending superordinate topics. Therefore, this literature review gives a comprehensive and descriptive overview as well as an insight into thematic trend developments of the research field

Entrepreneurial Motivation: An Exploratory Study of Gender and Venture Types

Entrepreneurial motivations have become a frequently discussed topic in entrepreneurship research. However, few studies investigated entrepreneurs' motivation across gender and different venture types and tend to rely on surveys or case studies. By using a text mining approach, we investigate if there are differences between male and female entrepreneurs' motivation and if female entrepreneurs' motivation differs across different venture types. This text mining approach in combination with a qualitative content analysis was used to examine unique motivational data from 472 entrepreneurial projects from three different entrepreneurship support programs in Norway and Sweden. Findings suggest that motivation of female and male entrepreneurs differ only slightly, while motivation of female entrepreneurs differs according to the different venture types. We thus contribute to a better understanding of entrepreneurial motivation and to a better understanding of why female entrepreneurs start a business. This can, for instance, benefit the improvement of future female entrepreneurship support programs