Food insecurity and physical activity among U.S. populations

Objectives: Examine the association between food insecurity (FI) and physical activity (PA) in the U.S. population. Methods: Accelerometry (PAM) and self-report PA (PAQ) data from NHANES 2003-2006 were used. Those aged less than six years or were older than 65 years, pregnant, with physical limitations, or with family income above 350% of the poverty line were excluded. FI was measured by the USDA Household Food Security Survey Module. Crude and adjusted odd ratios were calculated from logistic regression to identify the association between FI and adherence to the PA recommendation. Crude and adjusted coefficients were calculated from linear regression to identify the association between FI and both sedentary and activity minutes. Results: In children, FI was not associated with adherence to PA recommendation measured via PAM or PAQ (p>0.05) but was significantly associated with sedentary minutes (adjusted coefficient=10.74, one-sided p<0.05). Food-insecure children did less moderate-to-vigorous PA than did food-secure children (adjusted coefficient = -5.31, p = 0.032). In adults, FI was significantly associated with PA (adjusted OR=0.722 for PAM and OR=0.839 for PAQ, one-sided p<0.05) but not associated with sedentary minutes (p>0.05) Conclusions: FI children were more sedentary and FI adults were less likely to adhere to the PA recommendation than those without FI.

Household food insecurity is associated with less physical activity among children and adults in the U.S. population

Background Household food insecurity and physical activity are each important public-health concerns in the United States, but the relation between them was not investigated thoroughly. Objective We wanted to examine the association between food insecurity and physical activity in the U.S. population. Methods Physical activity measured by accelerometry (PAM) and physical activity measured by questionnaire (PAQ) data from the NHANES 2003–2006 were used. Individuals aged <6 y or >65 y, pregnant, with physical limitations, or with family income >350% of the poverty line were excluded. Food insecurity was measured by the USDA Household Food Security Survey Module. Adjusted ORs were calculated from logistic regression to identify the association between food insecurity and adherence to the physical-activity guidelines. Adjusted coefficients were obtained from linear regression to identify the association between food insecurity with sedentary/physical-activity minutes. Results In children, food insecurity was not associated with adherence to physical-activity guidelines measured via PAM or PAQ and with sedentary minutes (P > 0.05). Food-insecure children did less moderate to vigorous physical activity than food-secure children (adjusted coefficient = −5.24, P = 0.02). In adults, food insecurity was significantly associated with adherence to physical-activity guidelines (adjusted OR = 0.72, P = 0.03 for PAM; and OR = 0.84, P < 0.01 for PAQ) but was not associated with sedentary minutes (P > 0.05). Conclusion Food-insecure children did less moderate to vigorous physical activity, and food-insecure adults were less likely to adhere to the physical-activity guidelines than those without food insecurity.

The potential for new understandings of normal and abnormal cognition by integration of neuroimaging and behavioral data : Not an exercise in carrying coals to Newcastle

Discovering the means to prevent and cure schizophrenia is a vision that motivates many scientists. But in order to achieve this goal, we need to understand its neurobiological basis. The emergent metadiscipline of cognitive neuroscience fields an impressive array of tools that can be marshaled towards achieving this goal, including powerful new methods of imaging the brain (both structural and functional) as well as assessments of perceptual and cognitive capacities based on psychophysical procedures, experimental tasks and models developed by cognitive science. We believe that the integration of data from this array of tools offers the greatest possibilities and potential for advancing understanding of the neural basis of not only normal cognition but also the cognitive impairments that are fundamental to schizophrenia. Since sufficient expertise in the application of these tools and methods rarely reside in a single individual, or even a single laboratory, collaboration is a key element in this endeavor. Here, we review some of the products of our integrative efforts in collaboration with our colleagues on the East Coast of Australia and Pacific Rim. This research focuses on the neural basis of executive function deficits and impairments in early auditory processing in patients using various combinations of performance indices (from perceptual and cognitive paradigms), ERPs, fMRI and sMRI. In each case, integration of two or more sources of information provides more information than any one source alone by revealing new insights into structure-function relationships. Furthermore, the addition of other imaging methodologies (such as DTI) and approaches (such as computational models of cognition) offers new horizons in human brain imaging research and in understanding human behavior.

Jet and flash imprint defectivity - Assessment and reduction for semiconductor applications

Defectivity has been historically identified as a leading technical roadblock to the implementation of nanoimprint lithography for semiconductor high volume manufacturing. The lack of confidence in nanoimprint's ability to meet defect requirements originates in part from the industry's past experiences with 1 × lithography and the shortage in enduser generated defect data. SEMATECH has therefore initiated a defect assessment aimed at addressing these concerns. The goal is to determine whether nanoimprint, specifically Jet and Flash Imprint Lithography from Molecular Imprints, is capable of meeting semiconductor industry defect requirements. At this time, several cycles of learning have been completed in SEMATECH's defect assessment, with promising results. J-FIL process random defectivity of < 0.1 def/cm2 has been demonstrated using a 120nm half-pitch template, providing proof of concept that a low defect nanoimprint process is possible. Template defectivity has also improved significantly as shown by a pre-production grade template at 80nm pitch. Cycles of learning continue on feature sizes down to 22nm. © 2011 SPIE.

NEU-MODEL : a multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

Hip joint stabilization vs. propulsion and resistance in individuals with transfemoral amputation

Joint moments and joint powers are widely used to determine the effects of rehabilitation programs and prosthetic components (e.g., alignments). A complementary analysis of the 3D angle between joint moment and joint angular velocity has been proposed to assess whether the joints are predominantly driven or stabilized.

Structural complexity in structural health monitoring: Design of laboratory model and test plan

Many researchers in the field of civil structural health monitoring (SHM) have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Fieldwork has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. Informed by a brief review of the literature, this paper documents the design and proposed test plan of a structurally complex laboratory bridge model that has been specifically designed for the purpose of SHM research. Preliminary results have been presented in the companion paper.

U v U [2002] HCA 36: Commentary

This commentary offers a feminist analysis of relocation cases through the lens of U v U [2002] HCA 36, and with reference to the re-written judgment for the Australian Feminist Judgments project. First, the commentary considers the gendered nature of relocation cases, and analyses aspects of the reasoning and outcome of U v U that are of concern from a feminist perspective. Second, the commentary discusses how the re-written judgment addresses these concerns, thereby offering a feminist judgment on the issue of relocation in family law.

Limitations of a laboratory scale model in predicting optimal pilot scale conditions for dilute acid pretreatment of sugarcane bagasse

Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.

A laboratory assessment of the choice of vessel size under individual transferable quota regimes

This paper examines the effect of individual transferable quota regimes on technology choice, such as choice of vessel size, by using the laboratory experiment method. We find that even if vessel sizes change over time, the quota price can converge to the fundamental value conditioned on the vessels chosen. We also find that subjects choose their vessel type to maximise their profits based on the quota trading prices in the previous period. This result implies that the efficiency of quota markets in the beginning period is important because any inefficiency in quota markets may affect vessel sizes in ensuing periods. Moreover, we find that the initial allocations may significantly influence vessel sizes through two channels: first, a higher initial allocation to a subject increases the likelihood that the subject invests in a large-sized vessel; second, the quota price may be higher and more unstable under unequal allocation than under equal allocation; thus, whether the allocation is equal influences subjects' choice of vessel type. © 2014 Australian Agricultural and Resource Economics Society Inc.

Inadvertent hypothermia after procedural sedation and analgesia in a cardiac catheterisation laboratory: A prospective observational study

Objective To identify the prevalence of and risk factors for inadvertent hypothermia after procedures performed with procedural sedation and analgesia in a cardiac catheterisation laboratory. Design Single-centre, prospective observational study. Setting Tertiary care private hospital in Australia. Participants A convenience sample of 399 patients undergoing elective procedures with procedural sedation and analgesia were included. Propofol infusions were used when an anaesthetist was present. Otherwise, bolus doses of either midazolam or fentanyl or a combination of these medications was used. Interventions None Measurements and main results Hypothermia was defined as a temperature <36.0° Celsius. Multivariate logistic regression was used to identify risk factors. Hypothermia was present after 23.3% (n=93; 95% confidence interval [CI] 19.2%-27.4%) of 399 procedures. Sedative regimens with the highest prevalence of hypothermia were any regimen that included propofol (n=35; 40.2%; 95% CI 29.9%-50.5%) and the use of fentanyl combined with midazolam (n=23; 20.3%; 95% CI 12.9%-27.7%). Difference in mean temperature from pre to post-procedure was -0.27°C (Standard deviation [SD] 0.45). Receiving propofol (odds ratio [OR] OR 4.6 95% CI 2.5-8.6), percutaneous coronary intervention (OR 3.2 95% CI 1.7-5.9), body mass index <25 (OR 2.5 95% CI 1.4-4.4) and being hypothermic prior to the procedure (OR 4.9; 95% CI 2.3-10.8) were independent predictors of post-procedural hypothermia. Conclusions A moderate prevalence of hypothermia was observed. The small absolute change in temperature observed may not be a clinically important amount. More research is needed to increase confidence in our estimates of hypothermia in sedated patients and its impact on clinical outcomes.

Structural identification of a laboratory-based steel through truss cantilevered bridge with suspended span using a layered genetic algorithm with patternsearch step (GAPS)

Structural identification (St-Id) can be considered as the process of updating a finite element (FE) model of a structural system to match the measured response of the structure. This paper presents the St-Id of a laboratory-based steel through-truss cantilevered bridge with suspended span. There are a total of 600 degrees of freedom (DOFs) in the superstructure plus additional DOFs in the substructure. The St-Id of the bridge model used the modal parameters from a preliminary modal test in the objective function of a global optimisation technique using a layered genetic algorithm with patternsearch step (GAPS). Each layer of the St-Id process involved grouping of the structural parameters into a number of updating parameters and running parallel optimisations. The number of updating parameters was increased at each layer of the process. In order to accelerate the optimisation and ensure improved diversity within the population, a patternsearch step was applied to the fittest individuals at the end of each generation of the GA. The GAPS process was able to replicate the mode shapes for the first two lateral sway modes and the first vertical bending mode to a high degree of accuracy and, to a lesser degree, the mode shape of the first lateral bending mode. The mode shape and frequency of the torsional mode did not match very well. The frequencies of the first lateral bending mode, the first longitudinal mode and the first vertical mode matched very well. The frequency of the first sway mode was lower and that of the second sway mode was higher than the true values, indicating a possible problem with the FE model. Improvements to the model and the St-Id process will be presented at the upcoming conference and compared to the results presented in this paper. These improvements will include the use of multiple FE models in a multi-layered, multi-solution, GAPS St-Id approach.