The SPAR thermal analyzer: Present and future

The SPAR thermal analyzer, a system of finite-element processors for performing steady-state and transient thermal analyses, is described. The processors communicate with each other through the SPAR random access data base. As each processor is executed, all pertinent source data is extracted from the data base and results are stored in the data base. Steady state temperature distributions are determined by a direct solution method for linear problems and a modified Newton-Raphson method for nonlinear problems. An explicit and several implicit methods are available for the solution of transient heat transfer problems. Finite element plotting capability is available for model checkout and verification

Fossil fish studies

20 p., 8 fig.http://paleo.ku.edu/contributions.htm

Cooperative Restoration Programs in Critical Habitats in the Upper South Carolina Coastal Region

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations)

Siting Background Towers to Characterize Incoming Air for Urban Greenhouse Gas Estimation: A Case Study in the Washington, DC/Baltimore Area

There is increased interest in understanding urban greenhouse gas (GHG) emissions. To accurately estimate city emissions, the influence of extraurban fluxes must first be removed from urban greenhouse gas (GHG) observations. This is especially true for regions, such as the U.S. Northeastern Corridorâ Baltimore/Washington, DC (NECâ B/W), downwind of large fluxes. To help site background towers for the NECâ B/W, we use a coupled Bayesian Information Criteria and geostatistical regression approach to help site four background locations that best explain CO2 variability due to extraurban fluxes modeled at 12 urban towers. The synthetic experiment uses an atmospheric transport and dispersion model coupled with two different flux inventories to create modeled observations and evaluate 15 candidate towers located along the urban domain for February and July 2013. The analysis shows that the average ratios of extraurban inflow to total modeled enhancements at urban towers are 21% to 36% in February and 31% to 43% in July. In July, the incoming air dominates the total variability of synthetic enhancements at the urban towers (R2 = 0.58). Modeled observations from the selected background towers generally capture the variability in the synthetic CO2 enhancements at urban towers (R2 = 0.75, rootâ meanâ square error (RMSE) = 3.64 ppm; R2 = 0.43, RMSE = 4.96 ppm for February and July). However, errors associated with representing background air can be up to 10 ppm for any given observation even with an optimal background tower configuration. More sophisticated methods may be necessary to represent background air to accurately estimate urban GHG emissions.Key PointsFactoring in the variability of greenhouse gas enhancements in incoming air is critical for estimating emissions in an urban domainStatistical methods were used to site four towers sampling background air in the Washington, DC/Baltimore regionOptimal background tower configurations for representing incoming air can still have large errors for any given urban GHG observationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142902/1/jgrd54353_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142902/2/jgrd54353.pd

A novel paired associative stimulation protocol with a high-frequency peripheral component : A review on results in spinal cord injury rehabilitation

In recent decades, a multitude of therapeutic approaches has been developed for spinal cord injury (SCI), but few have progressed to regular clinical practice. Novel non-invasive, cost-effective, and feasible approaches to treat this challenging condition are needed. A novel variant of paired associative stimulation (PAS), high-PAS, consists of non-invasive high-intensity transcranial magnetic stimulation (TMS) and non-invasive high-frequency electrical peripheral nerve stimulation (PNS). We observed a therapeutic effect of high-PAS in 20 patients with incomplete SCI with wide range of injury severity, age, and time since injury. Tetraplegic and paraplegic, traumatic, and neurological SCI patients benefited from upper- or lower-limb high-PAS. We observed increases in manual motor scores (MMT) of upper and lower limbs, functional hand tests, walking tests, and measures of functional independence. We also optimized PAS settings in several studies in healthy subjects and began elucidating the mechanisms of therapeutic action. The scope of this review is to describe the clinical experience gained with this novel PAS approach. This review is focused on the summary of our results and observations and the methodological considerations for researchers and clinicians interested in adopting and further developing this new method.Peer reviewe

Modulation of Neutrophil Function by Recombinant Human IgG1 Fc Hexamer in the Endogenous K/BxN Mouse Model of Rheumatoid Arthritis.

INTRODUCTION Neutrophils are a pivotal cell type in the K/BxN mouse model of rheumatoid arthritis and play an essential role in the progression of the arthritis. They are readily activated by immune complexes (ICs) via their FcγRs to release IL-1β in addition to other cytokines, which are inducing cartilage destruction. Neutrophils also release neutrophil-active chemokines to recruit themselves in an autocrine manner to perpetuate tissue destruction. FcγR-expression on neutrophils is of crucial importance for the recognition of ICs. METHODS In this study, due to its high avidity for binding to FcγRs, we investigated the potential anti-inflammatory effect of a recombinant IgG1 Fc hexamer (rFc-µTP-L309C) on neutrophils in the K/BxN mouse model of endogenously generated chronic arthritis. 200 mg/kg rFc-µTP-L309C and human serum albumin (HSA), used as controls, were administered subcutaneously every other day. Mouse ankle joints were monitored daily to generate a clinical score. Immunohistology was used to evaluate neutrophil infiltration and TUNEL to assess apoptosis. ELISA was used to measure IL-1β. RESULTS Treatment with rFc-µTP-L309C, but not HSA, was able to significantly ameliorate the arthritis in the K/BxN mice. Significant neutrophil infiltration into the ankle joint was found, but treatment with rFc-µTP-L309C resulted in significantly less neutrophil infiltration. There was no significant influence of rFc-µTP-L309C on neutrophil death or apoptosis. Less neutrophil infiltration could not be correlated to chemokine-mediated migration. Significantly less IL-1β was measured in mice treated with rFc-µTP-L309C. CONCLUSION In the endogenous K/BxN mouse model of rheumatoid arthritis, amelioration can be explained in part by inhibition of neutrophil infiltration into the joints as well as inhibition of IL-1β production. Given the observed inhibitory properties on neutrophils, rFc-µTP-L309C may be a potential therapeutic candidate to treat autoimmune and inflammatory conditions in which neutrophils are the predominant cell type involved in pathogenesis

Computer simulation of syringomyelia in dogs

Syringomyelia is a pathological condition in which fluid-filled cavities (syringes) form and expand in the spinal cord. Syringomyelia is often linked with obstruction of the craniocervical junction and a Chiari malformation, which is similar in both humans and animals. Some brachycephalic toy breed dogs such as Cavalier King Charles Spaniels (CKCS) are particularly predisposed. The exact mechanism of the formation of syringomyelia is undetermined and consequently with the lack of clinical explanation, engineers and mathematicians have resorted to computer models to identify possible physical mechanisms that can lead to syringes. We developed a computer model of the spinal cavity of a CKCS suffering from a large syrinx. The model was excited at the cranial end to simulate the movement of the cerebrospinal fluid (CSF) and the spinal cord due to the shift of blood volume in the cranium related to the cardiac cycle. To simulate the normal condition, the movement was prescribed to the CSF. To simulate the pathological condition, the movement of CSF was blocked

Measuring changes in self-concept: a qualitative evaluation of outcome questionnaires in people having acupuncture for their chronic health problems

BACKGROUND: Changes in self-concept are an important potential outcome for many interventions for people with long-term conditions. This study sought to identify and evaluate outcome questionnaires suitable for quantifying changes in self-concept in people with long-term conditions, in the context of treatment with acupuncture and Chinese medicine. METHODS: A literature search was followed by an evaluation of three questionnaires: The Wellbeing Questionnaire W-BQ12, the Patient Enablement Instrument (PEI), and the Arizona Integrative Outcome Scale (AIOS). A convenience sample of 23 people completed the questionnaires on two occasions and were interviewed about their experience and their questionnaire responses. All acupuncturists were interviewed. RESULTS: Changes in self-concept were common and emerged over time. The three questionnaires had different strengths and weaknesses in relation to measuring changes in self-concept. The generic AIOS had face validity and was sensitive to changes in self-concept over time, but it lacked specificity. The PEI was sensitive and specific in measuring these changes but had lower acceptability. The sensitivity of the W-BQ12 was affected by initial high scores (ceiling effect) and a shorter timescale but was acceptable and is suitable for repeated administration. The PEI and W-BQ12 questionnaires worked well in combination. CONCLUSION: Changes in self-concept are important outcomes of complex interventions for people with long-term illness and their measurement requires carefully evaluated tools and long-term follow-up. The literature review and the analysis of the strengths and weaknesses of the questionnaires is a resource for other researchers. The W-BQ12 and the PEI both proved useful for this population and a larger quantitative study is planned