Modeling contact forces during human-robot interactions for performing activities of daily living.

This study aims to characterize contact forces between humans and tools during activities of daily living (ADL) to provide information to a personal care robot. The study was conducted on non-impaired subjects to capture various static and dynamic force levels when making contact with three different robotic tools, each designed to perform an ADL task: hair brushing, face wiping, and face shaving. The static trial of the study involved 21 participants. Forces were collected at fixed locations for each task and used to develop models for each participant. Extraction of the maximum force levels was performed for both the maximum and desired levels of force. The dynamic trial involved 24 individuals. Participants were asked to maintain a comfortable level of force for the duration of their contact with the tool as the robot moved along its path to perform the ADL task. For the static and dynamic trials, higher forces were observed during hair brushing compared to the other two tasks. It was observed that the hair brushing task force at a specific contact point has an overall maximum of 55.66 N, while the maximum forces detected in the face wiping and face shaving tasks were 36.40 and 11.11 N, respectively. The forces collected were analyzed, and no trends were found relating the contact forces to the gender, height, or weight of the subjects. Based on the analysis of the results, recommendations have been made to enhance the force safety limits for the personal care robot working environment.

HACSim: an R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves.

Assessing levels of standing genetic variation within species requires a robust sampling for the purpose of accurate specimen identification using molecular techniques such as DNA barcoding; however, statistical estimators for what constitutes a robust sample are currently lacking. Moreover, such estimates are needed because most species are currently represented by only one or a few sequences in existing databases, which can safely be assumed to be undersampled. Unfortunately, sample sizes of 5-10 specimens per species typically seen in DNA barcoding studies are often insufficient to adequately capture within-species genetic diversity. Here, we introduce a novel iterative extrapolation simulation algorithm of haplotype accumulation curves, called HACSim (Haplotype Accumulation Curve Simulator) that can be employed to calculate likely sample sizes needed to observe the full range of DNA barcode haplotype variation that exists for a species. Using uniform haplotype and non-uniform haplotype frequency distributions, the notion of sampling sufficiency (the sample size at which sampling accuracy is maximized and above which no new sampling information is likely to be gained) can be gleaned. HACSim can be employed in two primary ways to estimate specimen sample sizes: (1) to simulate haplotype sampling in hypothetical species, and (2) to simulate haplotype sampling in real species mined from public reference sequence databases like the Barcode of Life Data Systems (BOLD) or GenBank for any genomic marker of interest. While our algorithm is globally convergent, runtime is heavily dependent on initial sample sizes and skewness of the corresponding haplotype frequency distribution.

Defending eliminative structuralism and a whole lot more (or less).

Ontic structural realism argues that structure is all there is. In (French, 2014) I argued for an 'eliminativist' version of this view, according to which the world should be conceived, metaphysically, as structure, and objects, at both the fundamental and 'everyday' levels, should be eliminated. This paper is a response to a number of profound concerns that have been raised, such as how we might distinguish between the kind of structure invoked by this view and mathematical structure in general, how we should choose between eliminativist ontic structural realism and alternative metaphysical accounts such as dispositionalism, and how we should capture, in metaphysical terms, the relationship between structures and particles. In developing my response I shall touch on a number of broad issues, including the applicability of mathematics, the nature of representation and the relationship between metaphysics and science in general.

Impacts of Combined Cooling, Heating and Power Systems, and Rainwater Harvesting on Water Demand, Carbon Dioxide, and NOx Emissions for Atlanta.

The purpose of this study is to explore the potential water, CO2 and NOx emission, and cost savings that the deployment of decentralized water and energy technologies within two urban growth scenarios can achieve. We assess the effectiveness of urban growth, technological, and political strategies to reduce these burdens in the 13-county Atlanta metropolitan region. The urban growth between 2005 and 2030 was modeled for a business as usual (BAU) scenario and a more compact growth (MCG) scenario. We considered combined cooling, heating and power (CCHP) systems using microturbines for our decentralized energy technology and rooftop rainwater harvesting and low flow fixtures for the decentralized water technologies. Decentralized water and energy technologies had more of an impact in reducing the CO2 and NOx emissions and water withdrawal and consumption than an MCG growth scenario (which does not consider energy for transit). Decentralized energy can reduce the CO2 and NOx emissions by 8% and 63%, respectively. Decentralized energy and water technologies can reduce the water withdrawal and consumption in the MCG scenario by 49% and 50% respectively. Installing CCHP systems on both the existing and new building stocks with a net metering policy could reduce the CO2, NOx, and water consumption by 50%, 90%, and 75% respectively.

Use of Highly Fortified Products among US Adults.

It is complicated to ascertain the composition and prevalence of the use of highly fortified food and supplement products (HFPs) because HFP foods and HFP supplements have different labeling requirements. However, HFPs (energy bars, energy drinks, sports drinks, protein bars, energy shots, and fortified foods/beverages) are popular in the United States. A web-based survey balanced to reflect US census data was used to describe their use in a sample of 2,355 US adults >18 yr in 2011 and trends in their use from 2005. In 2011, 33% of adults reported using HFP; use was significantly higher among males, African Americans, Hispanics, and more highly educated individuals (e.g. some college or more) and those <45 yr compared to non-users. Multiple product use was common. Of users, 46% consumed sports drinks, 37% fortified foods/beverages, 32% protein bars, 27% energy drinks, 24% energy bars, and 12% energy shots. For those HFP products as a group, prevalence of use was 36% (n=2039) in 2005, 35% in 2009 (n=2010), and 30% in 2011 (n=2355). Although use was significantly lower in 2011 than in 2005 especially among females, non-Hispanics, and those with high school education or less (P≤0.05). HFP, particularly energy and sports drinks, continue to be widely used by many U.S. adults.

Neighborhood commuting environment and obesity in the United States: an urban-rural stratified multilevel analysis.

OBJECTIVE: Automobile dependency and longer commuting are associated with current obesity epidemic. We aimed to examine the urban-rural differential effects of neighborhood commuting environment on obesity in the US METHODS: The 1997-2005 National Health Interview Survey (NHIS) were linked to 2000 US Census data to assess the effects of neighborhood commuting environment: census tract-level automobile dependency and commuting time, on individual obesity status. RESULTS: Higher neighborhood automobile dependency was associated with increased obesity risk in urbanized areas (large central metro (OR 1.11[1.09, 1.12]), large fringe metro (OR 1.17[1.13, 1.22]), medium metro (OR 1.22[1.16, 1.29]), small metro (OR 1.11[1.04, 1.19]), and micropolitan (OR 1.09[1.00, 1.19])), but not in non-core rural areas (OR 1.00[0.92, 1.08]). Longer neighborhood commuting time was associated with increased obesity risk in large central metro (OR 1.09[1.04, 1.13]), and less urbanized areas (small metro (OR 1.08[1.01, 1.16]), micropolitan (OR 1.06[1.01, 1.12]), and non-core rural areas (OR 1.08[1.01, 1.17])), but not in (large fringe metro (OR 1.05[1.00, 1.11]), and medium metro (OR 1.04[0.98, 1.10])). CONCLUSION: The link between commuting environment and obesity differed across the regional urbanization levels. Urban and regional planning policies may improve current commuting environment and better support healthy behaviors and healthy community development.

Electrorheological analysis of colloidal dispersions of aluminum oxide and silicone oil.

The electrorheological properties of colloidal dispersions of aluminum oxide nanotubes and nanoparticles in silicone oil were investigated. The shear storage modulus of colloidal dispersions containing 5 wt% of aluminum oxide nanotubes increased by four orders of magnitude upon the application of an external electric field of as low as 400 V/mm. The storage modulus of the nanotube systems increased further by increasing the concentration of nanotubes. The electrorheological response of aluminum oxide nanoparticles dispersions was significantly lower than that of the dispersions containing the same weight fraction of aluminum oxide nanotubes at the same external electric field. This result reflects the effect of shape anisotropy on the electrorheological features of colloidal dispersions.

Shifting to structures in physics and biology: a prophylactic for promiscuous realism.

Within the philosophy of science, the realism debate has been revitalised by the development of forms of structural realism. These urge a shift in focus from the object oriented ontologies that come and go through the history of science to the structures that remain through theory change. Such views have typically been elaborated in the context of theories of physics and are motivated by, first of all, the presence within such theories of mathematical equations that allow straightforward representation of the relevant structures; and secondly, the implications of such theories for the individuality and identity of putative objects. My aim in this paper is to explore the possibility of extending such views to biological theories. An obvious concern is that within the context of the latter it is typically insisted that we cannot find the kinds of highly mathematised structures that structural realism can point to in physics. I shall indicate how the model-theoretic approach to theories might help allay such concerns. Furthermore, issues of identity and individuality also arise within biology. Thus Dupré has recently noted that there exists a 'General Problem of Biological Individuality' which relates to the issue of how one divides 'massively integrated and interconnected' systems into discrete components. In response Dupré advocates a form of 'Promiscuous Realism' that holds, for example, that there is no unique way of dividing the phylogenetic tree into kinds. Instead I shall urge serious consideration of those aspects of the work of Dupré and others that lean towards a structuralist interpretation. By doing so I hope to suggest possible ways in which a structuralist stance might be extended to biology.

A knowledge - based approach to using existing data for seismic risk assessment

Techniques for seismic risk assessment have improved rapidly in the past decade. Much more is known about how different types of structures responde to an earthquake. To make assessment of seismic risk, this earthquake hazard information must be combined with an inventory of buildings by structure type. The cost of obtaining such inventory information presents a key stumbling block to implementing risk assessment techniques for large urban areas. Structure inventories based on field surveys are too expensive and become outdated as soon as they are completed. No single secondary data source contains the detailed structural information requiered by today's risk assessment techniques. This paper describes a knowledge - based system that makes inferences about structure types based on secondary data. Existing land use, structure age, size, number of stories and improvement are use to classify buildings by structure type. The knowledge - based system described here uses a set of rules to make inferences about structure type based on these characteristics. In this way the knowledge based system creates new data not available from secondary sources (AU)