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At least 487 records · Page 27

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

Nguyen, Nhan T.↗

Global Positioning System (GPS) Precipitable Water in Forecasting Lightning at Spaceport Canaveral

This paper evaluates the use of precipitable water (PW) from Global Positioning System (GPS) in lightning prediction. Additional independent verification of an earlier model is performed. This earlier model used binary logistic regression with the following four predictor variables optimally selected from a candidate list of 23 candidate predictors: the current precipitable water value for a given time of the day, the change in GPS-PW over the past 9 hours, the KIndex, and the electric field mill value. This earlier model was not optimized for any specific forecast interval, but showed promise for 6 hour and 1.5 hour forecasts. Two new models were developed and verified. These new models were optimized for two operationally significant forecast intervals. The first model was optimized for the 0.5 hour lightning advisories issued by the 45th Weather Squadron. An additional 1.5 hours was allowed for sensor dwell, communication, calculation, analysis, and advisory decision by the forecaster. Therefore the 0.5 hour advisory model became a 2 hour forecast model for lightning within the 45th Weather Squadron advisory areas. The second model was optimized for major ground processing operations supported by the 45th Weather Squadron, which can require lightning forecasts with a lead-time of up to 7.5 hours. Using the same 1.5 lag as in the other new model, this became a 9 hour forecast model for lightning within 37 km (20 NM)) of the 45th Weather Squadron advisory areas. The two new models were built using binary logistic regression from a list of 26 candidate predictor variables: the current GPS-PW value, the change of GPS-PW over 0.5 hour increments from 0.5 to 12 hours, and the K-index. The new 2 hour model found the following for predictors to be statistically significant, listed in decreasing order of contribution to the forecast: the 0.5 hour change in GPS-PW, the 7.5 hour change in GPS-PW, the current GPS-PW value, and the KIndex. The new 9 hour forecast model found the following five independent variables to be statistically significant, listed in decreasing order of contribution to the forecast: the current GPSPW value, the 8.5 hour change in GPS-PW, the 3.5 hour change in GPS-PW, the 12 hour change in GPS-PW, and the K-Index. In both models, the GPS-PW parameters had better correlation to the lightning forecast than the K-Index, a widely used thunderstorm index. Possible future improvements to this study are discussed.

Kehrer, Kristen C.↗

High Performance EVA Glove Collaboration: Glove Injury Data Mining Effort

Human hands play a significant role during Extravehicular Activity (EVA) missions and Neutral Buoyancy Lab (NBL) training events, as they are needed for translating and performing tasks in the weightless environment. Because of this high frequency usage, hand and arm related injuries are known to occur during EVA and EVA training in the NBL. The primary objectives of this investigation were to: 1) document all known EVA glove related injuries and circumstances of these incidents, 2) determine likely risk factors, and 3) recommend interventions where possible that could be implemented in the current and future glove designs. METHODS: The investigation focused on the discomforts and injuries of U.S. crewmembers who had worn the pressurized Extravehicular Mobility Unit (EMU) spacesuit and experienced 4000 Series or Phase VI glove related incidents during 1981 to 2010 for either EVA ground training or in-orbit flight. We conducted an observational retrospective case-control investigation using 1) a literature review of known injuries, 2) data mining of crew injury, glove sizing, and hand anthropometry databases, 3) descriptive statistical analyses, and finally 4) statistical risk correlation and predictor analyses to better understand injury prevalence and potential causation. Specific predictor statistical analyses included use of principal component analyses (PCA), multiple logistic regression, and survival analyses (Cox proportional hazards regression). Results of these analyses were computed risk variables in the forms of odds ratios (likelihood of an injury occurring given the magnitude of a risk variable) and hazard ratios (likelihood of time to injury occurrence). Due to the exploratory nature of this investigation, we selected predictor variables significant at p≤0.15. RESULTS: Through 2010, there have been a total of 330 NASA crewmembers, from which 96 crewmembers performed 322 EVAs during 1981-2010, resulting in 50 crewmembers being injured inflight and 44 injured during 11,704 ground EVA training events. Of the 196 glove related injury incidents, 106 related to EVA and 90 to EVA training. Over these 196 incidents, 277 total injuries (126 flight; 151 training) were reported and were then grouped into 23 types of injuries. Of EVA flight injuries, 65% were commonly reported to the hand (in general), metacarpophalangeal (MCP) joint, and finger (not including thumb) with fatigue, abrasion, and paresthesia being the most common injury types (44% of total flight injuries). Training injuries totaled to more than 70% being distributed to the fingernail, MCP joint, and finger crotch with 88% of the specific injuries listed as pain, erythema, and onycholysis. Of these training injuries, when reporting pain or erythema, the most common location was the index finger, but when reporting onycholysis, it was the middle finger. Predictor variables specific to increased risk of onycholysis included: female sex (OR=2.622), older age (OR=1.065), increased duration in hours of the flight or training event (OR=1.570), middle finger length differences in inches between the finger and the EVA glove (OR=7.709), and use of the Phase VI glove (OR=8.535). Differentiation between training and flight and injury reporting during 2002-2004 were significant control variables. For likelihood of time to first onycholysis injury, there was a 24% reduction in rate of reporting for each year increase in age. Also, more experienced crewmembers, based on number of EVA flight or training events completed, were less likely to report an onycholysis injury (3% less for every event). Longer duration events also found reporting rates to occur 2.37 times faster for every hour of length. Crewmembers with larger hand size reported onycholysis 23% faster than those with smaller hand size. Finally, for every 1/10th of an inch increase in difference between the middle finger length and the glove, the rate of reporting increased by 60%. DISCUSSION: One key finding was that the Series 4000 glove had a lower injury risk than the Phase VI, which provides a platform for further evaluation. General interventions that reduce hand overexertion and repetitive use exposure through tool development, procedural changes and shorter exposures may be one mitigation path, but due to the way the training event times were reported, we cannot provide a guideline for a specific event duration change. When the finger length was different from the glove length, the risk of injury increased indicating that the use of larger finger take-ups could be contributing to injury and therefore may not be recommended. Prior to this investigation, there was one previous investigation indicating hand anthropometry may be related to onycholysis. We found different hand anthropometry variables indicated by this investigation as compared to the prior, specifically differences in middle finger length compared to glove finger length, which point more towards a sizing issue than a specific anthropometry issue. Additionally, although this investigation has identified sizing as an issue, the force and environmental-related variables of the EVA glove that could also cause injury were not accounted for.

Reid, C. R.↗

Automatic variable selection in ecological niche modeling: A case study using Cassin’s Sparrow (Peucaea cassinii)

MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max’s Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin’s Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim’s Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species’ bioclimatic niche. It also selected biologically and ecologically plausible predictors from a more diverse set of 86 environmental variables derived from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, foster exploratory experimentation with otherwise difficult-to-use climate data sets, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

John L. Schnase↗

Northeast US Ecological Forecasting: Modeling Invasive Plant Habitat Suitability to Support Management Efforts in the American Northeast

Invasive plant species threaten environmental and economic interests when they spread into new areas, outcompete native species, and disrupt ecosystem services. If the spread is not controlled early, species can become well-established and increasingly difficult to manage. The National Park Service (NPS) Invasive Plant Management Teams (IPMTs) strive for an “early detection, rapid response” approach to reducing invasive species spread. Management teams can better prioritize their work with the help of species distribution models (SDMs), which map habitat suitability by combining species occurrences with environmental predictor variables. Scarce invaded range data for newly arrived invasive species presents a particular challenge for producing accurate models. To improve future modeling efforts, this project compared SDM methods using different spatial scales to model two plant species invasive to the Northeast US: the well-established Japanese stiltgrass (Microstegium vimineum) and newer invasive species wavyleaf basketgrass (Oplismenus undulatifolius). The team used NASA Earth observations and climate datasets to model occurrence data and predictor layers at a US-specific extent (90m2 spatial resolution) and global extent (1 km2 spatial resolution). Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) provided data for US Normalized Difference Moisture Indices (NDMI), while global NDMI and topographic predictor layers were derived from Shuttle Radar Topography Mission (SRTM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting models indicated important predictor variables for each species and explored the benefits and tradeoffs of using global data to model habitat suitability for new-arrival invasive species.

Rebecca Ohman↗

Probabilistic Hydrological Estimation of LandSlides (PHELS): Global Ensemble Landslide Hazard Modelling

In this study we present a model for the global Probabilistic Hydrological Estimation of LandSlides (PHELS). PHELS estimates the daily hazard of hydrologically triggered landslides at a coarse spatial resolution of 36 km, by combining landslide susceptibility (LSS) and (percentiles of) hydrological variable(s). The latter include daily rainfall, a 7-day antecedent rainfall index (ARI7) or root-zone soil moisture content (rzmc) as hydrological predictor variables, or the combination of rainfall and rzmc. The hazard estimates with any of these predictor variables have areas under the receiver operating characteristic curve (AUC) above 0.68. The best performance was found with combined rainfall and rzmc predictors (AUC = 0.79), which resulted in the lowest number of missed alarms (especially during spring) and false alarms. Furthermore, PHELS provides hazard uncertainty estimates by generating ensemble simulations based on repeated sampling of LSS and the hydrological predictor variables. The estimated hazard uncertainty follows the behaviour of the input variable uncertainties, is about 13.6 % of the estimated hazard value on average across the globe and in time and is smallest for very low and very high hazard values.

Anne Felsberg↗

Using predictions of outcomes of cache memory access requests for controlling whether a request generator sends memory access requests to a memory in parallel with cache memory access requests

An electronic device handles memory access requests for data in a memory. The electronic device includes a memory controller for the memory, a last-level cache memory, a request generator, and a predictor. The predictor determines a likelihood that a cache memory access request for data at a given address will hit in the last-level cache memory. Based on the likelihood, the predictor determines: whether a memory access request is to be sent by the request generator to the memory controller for the data in parallel with the cache memory access request being resolved in the last-level cache memory, and, when the memory access request is to be sent, a type of memory access request that is to be sent. When the memory access request is to be sent, the predictor causes the request generator to send a memory request of the type to the memory controller.

97 MATHEMATICS AND COMPUTING↗

Analysis of calibration data for the uranium active neutron coincidence counting collar with attention to errors in the measured neutron coincidence rate

The declared linear density of 238 U and 235 U in fresh low enriched uranium light water reactor fuel assemblies can be verified for nuclear safeguards purposes using a neutron coincidence counter collar in passive and active mode, respectively. The active mode calibration of the Uranium Neutron Collar - Light water reactor fuel (UNCL) instrument is normally performed using a non-linear fitting technique. The fitting technique relates the measured neutron coincidence rate (the predictor) to the linear density of 235 U (the response) in order to estimate model parameters of the nonlinear Parte equation, which traditionally is used to model the calibration data. Alternatively, following a simple data transformation, the fitting can also be performed using standard linear fitting methods. This article compares performance of the nonlinear technique to the linear technique, using a range of possible error variance magnitudes in the measured neutron coincidence rate. We develop the required formalism and then apply the traditional (nonlinear) and alternative approaches (linear) to the same experimental and corresponding simulated representative datasets. Here, we find that, in this context, because of the magnitude of the errors in the predictor, it is preferable not to transform to a linear model, and it is preferable not to adjust for the errors in the predictor when inferring the model parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Disentangling natural and anthropogenic effects on benthic macroinvertebrate assemblages in western US streams

Abstract Stream macroinvertebrate assemblages are shaped by natural and human‐related factors that operate through complex hierarchical pathways. Quantifying these relationships can provide additional insights into stream ecological assessment. We applied a structural equation modeling framework to evaluate hypothesized pathways by which watershed, riparian, and in‐stream factors affect benthic macroinvertebrate condition in the Western Mountains (WMT) and Xeric (XER) ecoregions in the United States. We developed a conceptual model grounded in theory, empirical evidence, and expert opinion to evaluate the following hypotheses: (1) macroinvertebrate assemblages are primarily driven by proximal, in‐stream factors (e.g., water quality and physical habitat); (2) anthropogenic land uses affect macroinvertebrates indirectly by altering in‐stream characteristics; and (3) riparian vegetation cover attenuates land use effects. We tested our model separately on three measures of benthic macroinvertebrate assemblage condition: ratio of observed‐to‐expected taxonomic richness (O/E); a multimetric index (MMI); and richness of Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT). In the WMT, site‐level riparian cover, in‐stream physical habitat (relative bed stability), and water chemistry (total nitrogen) were the top three predictors of macroinvertebrate assemblages, each having over two times the magnitude of effect on macroinvertebrates compared with watershed‐level predictors. In the arid XER, annual precipitation and stream flow characteristics were top predictors of macroinvertebrate assemblages and had similar magnitudes of effect as in‐stream water chemistry. Path analyses revealed that land use activities in the watershed and at the stream site degraded macroinvertebrate assemblages indirectly by altering relative bed stability, water quality, and riparian cover/complexity. Increased riparian cover was associated with greater macroinvertebrate condition by reducing land use impacts on stream flow, streambed substrate, and water quality, but the pathways differed among ecoregions. In the WMT, site‐level riparian cover affected macroinvertebrate assemblages partly through indirect pathways associated with greater streambed stability and reduced total nitrogen concentrations. In contrast, in the XER, watershed‐level riparian cover affected macroinvertebrate assemblages through greater specific stream power. Identifying the relative effects of and pathways by which natural and anthropogenic factors affect macroinvertebrates can serve as a framework for prioritizing management and conservation efforts.

Environmental Sciences & Ecology↗

The impact of demographic, clinical, genetic, and imaging variables on tau PET status

Purpose: A substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer’s disease (AD) dementia and mild cognitive impairment (MCI) are tau PET–negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET–positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status. Methods: We included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [ 18 F]flortaucipir ( n = 1944) or [ 18 F]RO948 ( n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOE ε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model. Results: Tau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan. Conclusion: We identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.

60 APPLIED LIFE SCIENCES↗

Recent use of NSAID and NOAC medications are associated with a positive CT arteriogram

Background: Computed tomography angiography (CTA) is a diagnostic modality utilized in patients with suspected active lower gastrointestinal (GI) bleeding. CTA use in clinical practice is limited by the risk of contrast-induced nephropathy, and the loss of patients from direct physician observation while undergoing the test. Identifying clinical predictors of a positive result would be useful in guiding physician utilization of CTA studies. Methods: We performed a single-center retrospective study to determine which clinical predictors are associated with a positive CTA. Binary logistical regression modeling was used to identify the independent predictors and the results were expressed as adjusted odds ratios with corresponding 95% CI . Results: 262 patients met inclusion criteria and there were 61 (23.3%) positive CTA exams. In unadjusted analysis those who were CTA positive were more likely to require management in the intensive care unit (85.2% vs. 14.8%, p < 0.01) and being CTA positive was associated with a significantly increased in-hospital mortality (14.8% vs. 4.5%, p < 0.01). The use of a novel oral anticoagulant (NOAC) in the week prior to presentation was associated with a positive CTA after adjustment for confounders (adjusted odds ratio = 3.89; 95% CI 1.05–14.43). Similarly, the use of a non-steroidal anti-inflammatory drug (NSAID) was associated with a positive CTA (OR 2.36; 1.03–5.41). Only 8% of patients experienced contrast-induced nephropathy. Conclusion: Use of either NOACs or NSAIDs in the previous week is independently associated with a positive CTA in the setting of acute lower GI bleeding. CTA exams appear to confer a low risk of contrast-induced nephropathy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Pattern of Retained Contrast on Immediate Postprocedure Computed tomography (CT) After Particle Embolization of Liver Tumors Predicts Subsequent Treatment Response

PurposeTo determine if the pattern of retained contrast on immediate postprocedure computed tomography (CT) after particle embolization of hepatic tumors predicts modified Response Evaluation Criteria in Solid Tumors (mRECIST) response.Materials and MethodsThis study was approved by the Institutional Review Board with a waiver of authorization. One hundred four liver tumors were embolized with spherical embolic agents (Embospheres, Bead Block, LC Bead) and polyvinyl alcohol. Noncontrast CT was performed immediately after embolization to assess contrast retention in the targeted tumors, and treatment response was assessed by mRECIST criteria on follow-up CT (average time 9.0 {+-} 7.7 weeks after embolization). Tumor contrast retention (TCR) was determined based on change in Hounsfield units (HUs) of the index tumors between the preprocedure and immediate postprocedure scans; vascular contrast retention (VCR) was rated; and defects in contrast retention (DCR) were also documented. The morphology of residual enhancing tumor on follow-up CT was described as partial, circumferential, or total. Association between TCR variables and tumor response were assessed using multivariate logistic regression.ResultsOf 104 hepatic tumors, 51 (49 %) tumors had complete response (CR) by mRECIST criteria; 23 (22.1 %) had partial response (PR); 21 (20.2 %) had stable disease (SD); and 9 (8.7 %) had progressive disease (PD). By multivariate analysis, TCR, VCR, and tumor size are independent predictors of CR (p = 0.02, 0.05, and 0.005 respectively). In 75 tumors, DCR was found to be an independent predictor of failure to achieve complete response (p < 0.0001) by imaging criteria.ConclusionTCR, VCR, and DCR on immediate posttreatment CT are independent predictors of CR by mRECIST criteria.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Peripheral Stent Thrombosis Leading to Acute Limb Ischemia and Major Amputation: Incidence and Risk Factors in the Aortoiliac and Femoropopliteal Arteries

PurposeTo report the real-world incidence and risk factors of stent thrombosis in the aortoiliac and femoropopliteal arteries in case of bare nitinol stent (BNS) or covered nitinol stent (CNS) placement from a single-centre retrospective audit.Materials and MethodsMedical records of consecutive patients treated with peripheral stent placement for claudication or critical limb ischemia were audited for definite stent thrombosis defined as imaging confirmed stent thrombosis that presented as acute limb-threatening ischemia. Cases were stratified between aortoiliac and femoropopliteal anatomy. Cox regression analysis was employed to adjust for baseline clinical and procedural confounders and identify predictors of stent thrombosis and major limb loss.Results256 patients (n = 277 limbs) were analysed over a 5-year period (2009–2014) including 117 aortoiliac stents (34 CNS; 12.8 ± 5.0 cm and 83 BNS; 7.8 ± 4.0 cm) and 160 femoropopliteal ones (60 CNS; 21.1 ± 11.0 cm and 100 BNS; 17.5 ± 11.9 cm). Median follow-up was 1 year. Overall stent thrombosis rate was 6.1% (17/277) after a median of 43 days (range 2–192 days) and affected almost exclusively the femoropopliteal segment (12/60 in the CNS cohort vs. 4/100 in the BNS; p = 0.001). Annualized stent thrombosis rates (per 100 person-years) were 12.5% in case of CNS and 1.4% in case of BNS (HR 6.3, 95% CI 2.4–17.9; p = 0.0002). Corresponding major amputations rates were 8.7 and 2.5%, respectively (HR 4.5, 95% CI 2.7–27.9; p = 0.0006). On multivariable analysis, critical leg ischemia and CNS placement were the only predictors of stent thrombosis. Diabetes, critical leg ischemia, femoropopliteal anatomy, long stents and CNS were independent predictors of major amputations.ConclusionsPlacement of long femoropopliteal covered nitinol stents is associated with an increased incidence of acute stent thrombosis and ensuing major amputation. Risks are significantly lower in the aortoiliac vessels and with use of bare nitinol stents.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Two-Year Mortality After Angioplasty of the Femoro-Popliteal Artery with Uncoated Balloons and Paclitaxel-Coated Balloons—A Pooled Analysis of Four Randomized Controlled Multicenter Trials

Purpose: In view of a recent meta-analysis reporting increased mortality following angioplasty with paclitaxel-coated devices in peripheral arteries, we performed a patient-level 2-year mortality analysis based on pooled original data of four randomized controlled trials (THUNDER, FEMPAC, PACIFIER and CONSEQUENT). Methods and Results: Clinical data of four randomized controlled trial were pooled to assess 2-year mortality following paclitaxel-coated balloon (PCB) angioplasty compared to angioplasty without paclitaxel (control group). A logistic regression model was applied to identify potential predictors of mortality. At two years, 13 of 185 (7.0%) patients had died in the control group and 16/184 (8.7%) in the PBC group, p = 0.55. Kaplan–Meier analysis revealed no significant difference from all-cause death at 2 years (log rank p = 0.54). Causes of death were well balanced between the groups with no pattern or trend in favour of any specific causes in the PBC group. Logistic regression revealed that treatment groups (controls or PBC) were not a predictor of 2-year mortality. The only predictor for mortality was patient age ≥ 75 years. The delivered paclitaxel doses per patient were not significantly different in patients that died and those who did not die during the 24-month follow-up (5.300 ± 4.224 μg vs. 6.248 ± 4.629 μg, p = 0.433). Conclusions: Based on original patient-level data of four pooled randomized controlled trials, we found no increase in 2-year mortality in patients treated with PCB compared to control patients treated with uncoated balloons. Causes of death were well balanced between PCB and control patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Impact of global atmospheric reanalyses on statistical precipitation downscaling

Statistical downscaling based on a perfect prognosis approach often relies on global reanalyses to infer the statistical relationship between synoptic predictors and the local variable of interest, here daily precipitation. Nowadays, many reanalyses are available and their impact on the downscaled variable is not often considered. The present work assessed the impact of ten reanalyses on the performance of seven variants of analogue methods for statistical precipitation downscaling at 301 stations in Switzerland. Even though the study location is in a data-rich region, significant differences were found between reanalyses and their impact on the performance of the method can be even higher than the choice of the predictor variables. There was no single overall winner, but a selection of recommended reanalyses resulting in higher skill scores depending on the considered predictor variables. The impact of the output spatial resolution was assessed for different types of variables. Output resolutions below one degree were found to be often of low to no interest. Reanalyses with longer archives allow the pool of potential analogues to be increased, resulting in better performance. However, when adding variables affected by errors in a more distant past, the skill score decreased again. The use of multiple members from two reanalyses was also tested over a recent and a past period. The benefit of using members to increase the performance by better incorporating the uncertainties was found to be limited, and even problematic with methods using multiple analogy levels.

Meteorology & Atmospheric Sciences↗

Density and shrinkage as guiding criteria for the optimization of the thermal conductivity of poly(urethane)-class aerogels

We investigated the effect of gelation solvent, monomer type, and monomer concentration on the physical properties of freeze-dried poly(urethane)-poly(isocyanurate) (PUR-PIR) aerogels, with particular emphasis on their thermal conductivity. It was found that the gelation solvent considerably affects aerogel morphology and physical properties. Aerogels with the lowest thermal conductivity were obtained using a mixture of tetrahydrofuran (THF) and acetonitrile, in a 50% volume ratio. The influence on thermal conductivity of polyol and isocyanate structure and of their concentration was also investigated. Rigid precursors, phloroglucinol (POL), and an aromatic polyisocyanate based on toluene diisocyanate (Desmodur RC) yielded the lowest thermal conductivity. Our results were compared with recent work reporting on parameters that could be used as predictors of thermal conductivity and other physical properties of organic aerogels. None of these parameters were found to be satisfactory predictors of aerogel properties. For example, no systematic correlation between solvent solubility parameters and aerogel properties was observed. We also examined the role of the K-index. This index, defined as the ratio between porosity and contact angle, was shown recently to be a good predictor of the properties of polyurea aerogels. While the thermal conductivity scaled with the K-index, the scaling was different for each of the isocyanate monomers considered in our experiments. Thermal conductivity, instead, scaled well with the product of density and shrinkage of aerogels, independent of monomer type. The reasons of this dependence on shrinkage and density are discussed, and the use of these parameters to guide experimentation on other systems is discussed. Physical properties such as static and dynamic compression modulus and thermal stability of the most promising formulations were also examined.

36 MATERIALS SCIENCE↗

The impacts of building characteristics, social psychological and cultural factors on indoor environment quality productivity belief

Indoor environmental quality (IEQ) plays a key role in determining occupants' productivity at work; however, analyses of the interconnected factors among building physical, attitudinal, social and demographic components in one study are lacking. To fill this research gap, this study investigates these interconnected factors' influence on occupants’ IEQ-productivity belief, defined as a personal, subjective evaluation of the linkage between the impacts of five IEQ aspects (the quality of indoor temperature, air, natural and electric lighting, and acoustics) and productivity. A cross-sectional survey data was collected in university offices from six countries (Brazil, Italy, Poland, Switzerland, Taiwan and the U.S.). Results of multiple linear regression models indicate that IEQ satisfaction is the strongest positive predictor of the IEQ-productivity belief and this relationship is stronger in private offices. Country of residence is the second primary predictor. Several attitudinal-behavioral factors, including thermal comfort, perceived ease of controlling indoor environmental features, and attitudes toward sharing controls are all positively associated with IEQ-productivity belief. Interestingly, the level of control accessibility to light switches has the strongest impact as opposed to other controls. On the other hand, group norms and conformity intention are not significant predictors. Regarding demographics, men are more likely than women to perceive the IEQs to have positive impacts on their productivity, without considering other variables in the regression model; however, women are more likely than men to consider all IEQs as having positive impacts on productivity, after considering other variables. Furthermore, our findings provide suggestions for prioritizing wellness in the workplace since the early design stage.

99 GENERAL AND MISCELLANEOUS↗

High-order, linearly stable, partitioned solvers for general multiphysics problems based on implicit–explicit Runge–Kutta schemes

This work introduces a general framework for constructing high-order, linearly stable, partitioned solvers for multiphysics problems from a monolithic implicit–explicit Runge–Kutta (IMEX-RK) discretization of the semi-discrete equations. The generic multiphysics problem is modeled as a system of n systems of partial differential equations where the i th subsystem is coupled to the other subsystems through a coupling term that can depend on the state of all the other subsystems. This coupled system of partial differential equations reduces to a coupled system of ordinary differential equations via the method of lines where an appropriate spatial discretization is applied to each subsystem. The coupled system of ordinary differential equations is taken as a monolithic system and discretized using an IMEX-RK discretization with a specific implicit–explicit decomposition that introduces the concept of a predictor for the coupling term. We propose four coupling predictors that enable the monolithic system to be solved in a partitioned manner, i.e., subsystem-by-subsystem, and preserve the IMEX-RK structure and therefore the design order of accuracy of the monolithic scheme. The four partitioned solvers that result from these predictors are high-order accurate, allow for maximum re-use of existing single-physics software, and two of the four solvers allow the subsystems to be solved in parallel at a given stage and time step. We also analyze the stability of a coupled, linear model problem with a specific coupling structure and show that one of the partitioned solvers achieves unconditional linear stability for this problem, while the others are unconditionally stable only for certain values of the coupling strength. We demonstrate the performance of the proposed partitioned solvers on several classes of multiphysics problems including a simple linear system of ODEs, advection–diffusion–reaction systems, fluid–structure interaction problems, and particle-laden flows, where we verify the design order of the IMEX schemes and study various stability properties.

97 MATHEMATICS AND COMPUTING↗