Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting.

PubMed

Pires, J C M; Gonçalves, B; Azevedo, F G; Carneiro, A P; Rego, N; Assembleia, A J B; Lima, J F B; Silva, P A; Alves, C; Martins, F G

2012-09-01

This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O(3)) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons. Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O(3) concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO(2)), and O(3) (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004. Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O(3) regimes were temperature, CO and NO(2) concentrations, due to their importance in O(3) chemistry in an urban atmosphere. In the prediction of O(3) concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.

Carbon deposition thresholds on nickel-based solid oxide fuel cell anodes II. Steam:carbon ratio and current density

NASA Astrophysics Data System (ADS)

Kuhn, J.; Kesler, O.

2015-03-01

For the second part of a two part publication, coking thresholds with respect to molar steam:carbon ratio (SC) and current density in nickel-based solid oxide fuel cells were determined. Anode-supported button cell samples were exposed to 2-component and 5-component gas mixtures with 1 ≤ SC ≤ 2 and zero fuel utilization for 10 h, followed by measurement of the resulting carbon mass. The effect of current density was explored by measuring carbon mass under conditions known to be prone to coking while increasing the current density until the cell was carbon-free. The SC coking thresholds were measured to be ∼1.04 and ∼1.18 at 600 and 700 °C, respectively. Current density experiments validated the thresholds measured with respect to fuel utilization and steam:carbon ratio. Coking thresholds at 600 °C could be predicted with thermodynamic equilibrium calculations when the Gibbs free energy of carbon was appropriately modified. Here, the Gibbs free energy of carbon on nickel-based anode support cermets was measured to be -6.91 ± 0.08 kJ mol-1. The results of this two part publication show that thermodynamic equilibrium calculations with appropriate modification to the Gibbs free energy of solid-phase carbon can be used to predict coking thresholds on nickel-based anodes at 600-700 °C.

Using Reanalysis Data for the Prediction of Seasonal Wind Turbine Power Losses Due to Icing

NASA Astrophysics Data System (ADS)

Burtch, D.; Mullendore, G. L.; Delene, D. J.; Storm, B.

2013-12-01

The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data to investigate various methods of predicting seasonal losses (October-March) due to icing at two wind turbine sites located 121 km apart in North Dakota. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using three methods. For each of the three methods, the required atmospheric variables are determined in one of two ways: using industry-specific software to correlate anemometer data in conjunction with the MERRA dataset and using only the MERRA dataset for all variables. For each season, a percentage of the total expected generated power lost due to icing is determined and compared to observed losses from the production data. An optimization is performed in order to determine the relative humidity threshold that minimizes the difference between the predicted and observed values. Eight seasons of data are used to determine an optimal relative humidity threshold, and a further three seasons of data are used to test this threshold. Preliminary results have shown that the optimized relative humidity threshold for the northern turbine is higher than the southern turbine for all methods. For the three test seasons, the optimized thresholds tend to under-predict the icing losses. However, the threshold determined using boundary layer similarity theory most closely predicts the power losses due to icing versus the other methods. For the northern turbine, the average predicted power loss over the three seasons is 4.65 % while the observed power loss is 6.22 % (average difference of 1.57 %). For the southern turbine, the average predicted power loss and observed power loss over the same time period are 4.43 % and 6.16 %, respectively (average difference of 1.73 %). The three-year average, however, does not clearly capture the variability that exists season-to-season. On examination of each of the test seasons individually, the optimized relative humidity threshold methodology performs better than fixed power loss estimates commonly used in the wind energy industry.

Assessing conservation relevance of organism-environment relations using predicted changes in response variables

USGS Publications Warehouse

Gutzwiller, Kevin J.; Barrow, Wylie C.; White, Joseph D.; Johnson-Randall, Lori; Cade, Brian S.; Zygo, Lisa M.

2010-01-01

1. Organism–environment models are used widely in conservation. The degree to which they are useful for informing conservation decisions – the conservation relevance of these relations – is important because lack of relevance may lead to misapplication of scarce conservation resources or failure to resolve important conservation dilemmas. Even when models perform well based on model fit and predictive ability, conservation relevance of associations may not be clear without also knowing the magnitude and variability of predicted changes in response variables. 2. We introduce a method for evaluating the conservation relevance of organism–environment relations that employs confidence intervals for predicted changes in response variables. The confidence intervals are compared to a preselected magnitude of change that marks a threshold (trigger) for conservation action. To demonstrate the approach, we used a case study from the Chihuahuan Desert involving relations between avian richness and broad-scale patterns of shrubland. We considered relations for three winters and two spatial extents (1- and 2-km-radius areas) and compared predicted changes in richness to three thresholds (10%, 20% and 30% change). For each threshold, we examined 48 relations. 3. The method identified seven, four and zero conservation-relevant changes in mean richness for the 10%, 20% and 30% thresholds respectively. These changes were associated with major (20%) changes in shrubland cover, mean patch size, the coefficient of variation for patch size, or edge density but not with major changes in shrubland patch density. The relative rarity of conservation-relevant changes indicated that, overall, the relations had little practical value for informing conservation decisions about avian richness. 4. The approach we illustrate is appropriate for various response and predictor variables measured at any temporal or spatial scale. The method is broadly applicable across ecological environments, conservation objectives, types of statistical predictive models and levels of biological organization. By focusing on magnitudes of change that have practical significance, and by using the span of confidence intervals to incorporate uncertainty of predicted changes, the method can be used to help improve the effectiveness of conservation efforts.

Predictors of the nicotine reinforcement threshold, compensation, and elasticity of demand in a rodent model of nicotine reduction policy.

PubMed

Grebenstein, Patricia E; Burroughs, Danielle; Roiko, Samuel A; Pentel, Paul R; LeSage, Mark G

2015-06-01

The FDA is considering reducing the nicotine content in tobacco products as a population-based strategy to reduce tobacco addiction. Research is needed to determine the threshold level of nicotine needed to maintain smoking and the extent of compensatory smoking that could occur during nicotine reduction. Sources of variability in these measures across sub-populations also need to be identified so that policies can take into account the risks and benefits of nicotine reduction in vulnerable populations. The present study examined these issues in a rodent nicotine self-administration model of nicotine reduction policy to characterize individual differences in nicotine reinforcement thresholds, degree of compensation, and elasticity of demand during progressive reduction of the unit nicotine dose. The ability of individual differences in baseline nicotine intake and nicotine pharmacokinetics to predict responses to dose reduction was also examined. Considerable variability in the reinforcement threshold, compensation, and elasticity of demand was evident. High baseline nicotine intake was not correlated with the reinforcement threshold, but predicted less compensation and less elastic demand. Higher nicotine clearance predicted low reinforcement thresholds, greater compensation, and less elastic demand. Less elastic demand also predicted lower reinforcement thresholds. These findings suggest that baseline nicotine intake, nicotine clearance, and the essential value of nicotine (i.e. elasticity of demand) moderate the effects of progressive nicotine reduction in rats and warrant further study in humans. They also suggest that smokers with fast nicotine metabolism may be more vulnerable to the risks of nicotine reduction. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Predictors of the nicotine reinforcement threshold, compensation, and elasticity of demand in a rodent model of nicotine reduction policy*

PubMed Central

Grebenstein, Patricia E.; Burroughs, Danielle; Roiko, Samuel A.; Pentel, Paul R.; LeSage, Mark G.

2015-01-01

Background The FDA is considering reducing the nicotine content in tobacco products as a population-based strategy to reduce tobacco addiction. Research is needed to determine the threshold level of nicotine needed to maintain smoking and the extent of compensatory smoking that could occur during nicotine reduction. Sources of variability in these measures across sub-populations also need to be identified so that policies can take into account the risks and benefits of nicotine reduction in vulnerable populations. Methods The present study examined these issues in a rodent nicotine self- administration model of nicotine reduction policy to characterize individual differences in nicotine reinforcement thresholds, degree of compensation, and elasticity of demand during progressive reduction of the unit nicotine dose. The ability of individual differences in baseline nicotine intake and nicotine pharmacokinetics to predict responses to dose reduction was also examined. Results Considerable variability in the reinforcement threshold, compensation, and elasticity of demand was evident. High baseline nicotine intake was not correlated with the reinforcement threshold, but predicted less compensation and less elastic demand. Higher nicotine clearance predicted low reinforcement thresholds, greater compensation, and less elastic demand. Less elastic demand also predicted lower reinforcement thresholds. Conclusions These findings suggest that baseline nicotine intake, nicotine clearance, and the essential value of nicotine (i.e. elasticity of demand) moderate the effects of progressive nicotine reduction in rats and warrant further study in humans. They also suggest that smokers with fast nicotine metabolism may be more vulnerable to the risks of nicotine reduction. PMID:25891231

Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases.

PubMed

Hwang, Eui Jin; Goo, Jin Mo; Kim, Jihye; Park, Sang Joon; Ahn, Soyeon; Park, Chang Min; Shin, Yeong-Gil

2017-08-01

To develop a prediction model for the variability range of lung nodule volumetry and validate the model in detecting nodule growth. For model development, 50 patients with metastatic nodules were prospectively included. Two consecutive CT scans were performed to assess volumetry for 1,586 nodules. Nodule volume, surface voxel proportion (SVP), attachment proportion (AP) and absolute percentage error (APE) were calculated for each nodule and quantile regression analyses were performed to model the 95% percentile of APE. For validation, 41 patients who underwent metastasectomy were included. After volumetry of resected nodules, sensitivity and specificity for diagnosis of metastatic nodules were compared between two different thresholds of nodule growth determination: uniform 25% volume change threshold and individualized threshold calculated from the model (estimated 95% percentile APE). SVP and AP were included in the final model: Estimated 95% percentile APE = 37.82 · SVP + 48.60 · AP-10.87. In the validation session, the individualized threshold showed significantly higher sensitivity for diagnosis of metastatic nodules than the uniform 25% threshold (75.0% vs. 66.0%, P = 0.004) CONCLUSION: Estimated 95% percentile APE as an individualized threshold of nodule growth showed greater sensitivity in diagnosing metastatic nodules than a global 25% threshold. • The 95 % percentile APE of a particular nodule can be predicted. • Estimated 95 % percentile APE can be utilized as an individualized threshold. • More sensitive diagnosis of metastasis can be made with an individualized threshold. • Tailored nodule management can be provided during nodule growth follow-up.

Use of Biotechnological Devices in the Quantification of Psychophysiological Workload of Professional Chess Players.

PubMed

Fuentes, Juan P; Villafaina, Santos; Collado-Mateo, Daniel; de la Vega, Ricardo; Gusi, Narcis; Clemente-Suárez, Vicente Javier

2018-01-19

Psychophysiological requirements of chess players are poorly understood, and periodization of training is often made without any empirical basis. For this reason, the aim of the present study was to investigate the psychophysiological response and quantify the player internal load during, and after playing a chess game. The participant was an elite 33 year-old male chess player ranked among the 300 best chess players in the world. Thus, cortical arousal by critical flicker fusion threshold, electroencephalogram by the theta Fz/alpha Pz ratio and autonomic modulation by heart rate variability were analyzed. Data revealed that cortical arousal by critical flicker fusion threshold and theta Fz/alpha Pz ratio increased and heart rate variability decreased during chess game. All these changes indicated that internal load increased during the chess game. In addition, pre-activation was detected in pre-game measure, suggesting that the prefrontal cortex might be preparatory activated. For these reasons, electroencephalogram, critical flicker fusion threshold and heart rate variability analysis may be highly applicable tools to control and monitor workload in chess player.

Comparison of body mass index, waist circumference, and waist to height ratio in the prediction of hypertension and diabetes mellitus: Filipino-American women cardiovascular study.

PubMed

Battie, Cynthia A; Borja-Hart, Nancy; Ancheta, Irma B; Flores, Rene; Rao, Goutham; Palaniappan, Latha

2016-12-01

The relative ability of three obesity indices to predict hypertension (HTN) and diabetes (DM) and the validity of using Asian-specific thresholds of these indices were examined in Filipino-American women (FAW). Filipino-American women ( n  = 382), 40-65 years of age were screened for hypertension (HTN) and diabetes (DM) in four major US cities. Body mass index (BMI), waist circumference (WC) and waist circumference to height ratio (WHtR) were measured. ROC analyses determined that the three obesity measurements were similar in predicting HTN and DM (AUC: 0.6-0.7). The universal WC threshold of ≥ 35 in. missed 13% of the hypertensive patients and 12% of the diabetic patients. The Asian WC threshold of ≥ 31.5 in. increased detection of HTN and DM but with a high rate of false positives. The traditional BMI ≥ 25 kg/m 2 threshold missed 35% of those with hypertension and 24% of those with diabetes. The Asian BMI threshold improved detection but resulted in a high rate of false positives. The suggested WHtR cut-off of ≥ 0.5 missed only 1% of those with HTN and 0% of those with DM. The three obesity measurements had similar but modest ability to predict HTN and DM in FAW. Using Asian-specific thresholds increased accuracy but with a high rate of false positives. Whether FAW, especially at older ages, should be encouraged to reach these lower thresholds needs further investigation because of the high false positive rates.

Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL

PubMed Central

Li, Wen; Arasu, Vignesh; Newitt, David C.; Jones, Ella F.; Wilmes, Lisa; Gibbs, Jessica; Kornak, John; Joe, Bonnie N.; Esserman, Laura J.; Hylton, Nola M.

2016-01-01

Functional tumor volume (FTV) measurements by dynamic contrast-enhanced magnetic resonance imaging can predict treatment outcomes for women receiving neoadjuvant chemotherapy for breast cancer. Here, we explore whether the contrast thresholds used to define FTV could be adjusted by breast cancer subtype to improve predictive performance. Absolute FTV and percent change in FTV (ΔFTV) at sequential time-points during treatment were calculated and investigated as predictors of pathologic complete response at surgery. Early percent enhancement threshold (PEt) and signal enhancement ratio threshold (SERt) were varied. The predictive performance of resulting FTV predictors was evaluated using the area under the receiver operating characteristic curve. A total number of 116 patients were studied both as a full cohort and in the following groups defined by hormone receptor (HR) and HER2 receptor subtype: 45 HR+/HER2−, 39 HER2+, and 30 triple negatives. High AUCs were found at different ranges of PEt and SERt levels in different subtypes. Findings from this study suggest that the predictive performance to treatment response by MRI varies by contrast thresholds, and that pathologic complete response prediction may be improved through subtype-specific contrast enhancement thresholds. A validation study is underway with a larger patient population. PMID:28066808

Evaluation of waist-to-height ratio to predict 5 year cardiometabolic risk in sub-Saharan African adults.

PubMed

Ware, L J; Rennie, K L; Kruger, H S; Kruger, I M; Greeff, M; Fourie, C M T; Huisman, H W; Scheepers, J D W; Uys, A S; Kruger, R; Van Rooyen, J M; Schutte, R; Schutte, A E

2014-08-01

Simple, low-cost central obesity measures may help identify individuals with increased cardiometabolic disease risk, although it is unclear which measures perform best in African adults. We aimed to: 1) cross-sectionally compare the accuracy of existing waist-to-height ratio (WHtR) and waist circumference (WC) thresholds to identify individuals with hypertension, pre-diabetes, or dyslipidaemia; 2) identify optimal WC and WHtR thresholds to detect CVD risk in this African population; and 3) assess which measure best predicts 5-year CVD risk. Black South Africans (577 men, 942 women, aged >30years) were recruited by random household selection from four North West Province communities. Demographic and anthropometric measures were taken. Recommended diagnostic thresholds (WC > 80 cm for women, >94 cm for men; WHtR > 0.5) were evaluated to predict blood pressure, fasting blood glucose, lipids, and glycated haemoglobin measured at baseline and 5 year follow up. Women were significantly more overweight than men at baseline (mean body mass index (BMI) women 27.3 ± 7.4 kg/m(2), men 20.9 ± 4.3 kg/m(2)); median WC women 81.9 cm (interquartile range 61-103), men 74.7 cm (63-87 cm), all P < 0.001). In women, both WC and WHtR significantly predicted all cardiometabolic risk factors after 5 years. In men, even after adjusting WC threshold based on ROC analysis, WHtR better predicted overall 5-year risk. Neither measure predicted hypertension in men. The WHtR threshold of >0.5 appears to be more consistently supported and may provide a better predictor of future cardiometabolic risk in sub-Saharan Africa. Copyright © 2014 Elsevier B.V. All rights reserved.

What matters after sleeve gastrectomy: patient characteristics or surgical technique?

PubMed

Dhar, Vikrom K; Hanseman, Dennis J; Watkins, Brad M; Paquette, Ian M; Shah, Shimul A; Thompson, Jonathan R

2018-03-01

The impact of operative technique on outcomes in laparoscopic sleeve gastrectomy has been explored previously; however, the relative importance of patient characteristics remains unknown. Our aim was to characterize national variability in operative technique for laparoscopic sleeve gastrectomy and determine whether patient-specific factors are more critical to predicting outcomes. We queried the database of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program for laparoscopic sleeve gastrostomies performed in 2015 (n = 88,845). Logistic regression models were used to determine predictors of postoperative outcomes. In 2015, >460 variations of laparoscopic sleeve gastrectomy were performed based on combinations of bougie size, distance from the pylorus, use of staple line reinforcement, and oversewing of the staple line. Despite such substantial variability, technique variants were not predictive of outcomes, including perioperative morbidity, leak, or bleeding (all P ≥ .05). Instead, preoperative patient characteristics were found to be more predictive of these outcomes after laparoscopic sleeve gastrectomy. Only history of gastroesophageal disease (odds ratio 1.44, 95% confidence interval 1.08-1.91, P < .01) was associated with leak. Considerable variability exists in technique among surgeons nationally, but patient characteristics are more predictive of adverse outcomes after laparoscopic sleeve gastrectomy. Bundled payments and reimbursement policies should account for patient-specific factors in addition to current accreditation and volume thresholds when deciding risk-adjustment strategies. Copyright © 2018 Elsevier Inc. All rights reserved.

Optimized breast MRI functional tumor volume as a biomarker of recurrence-free survival following neoadjuvant chemotherapy.

PubMed

Jafri, Nazia F; Newitt, David C; Kornak, John; Esserman, Laura J; Joe, Bonnie N; Hylton, Nola M

2014-08-01

To evaluate optimal contrast kinetics thresholds for measuring functional tumor volume (FTV) by breast magnetic resonance imaging (MRI) for assessment of recurrence-free survival (RFS). In this Institutional Review Board (IRB)-approved retrospective study of 64 patients (ages 29-72, median age of 48.6) undergoing neoadjuvant chemotherapy (NACT) for breast cancer, all patients underwent pre-MRI1 and postchemotherapy MRI4 of the breast. Tumor was defined as voxels meeting thresholds for early percent enhancement (PEthresh) and early-to-late signal enhancement ratio (SERthresh); and FTV (PEthresh, SERthresh) by summing all voxels meeting threshold criteria and minimum connectivity requirements. Ranges of PEthresh from 50% to 220% and SERthresh from 0.0 to 2.0 were evaluated. A Cox proportional hazard model determined associations between change in FTV over treatment and RFS at different PE and SER thresholds. The plot of hazard ratios for change in FTV from MRI1 to MRI4 showed a broad peak with the maximum hazard ratio and highest significance occurring at PE threshold of 70% and SER threshold of 1.0 (hazard ratio = 8.71, 95% confidence interval 2.86-25.5, P < 0.00015), indicating optimal model fit. Enhancement thresholds affect the ability of MRI tumor volume to predict RFS. The value is robust over a wide range of thresholds, supporting the use of FTV as a biomarker. © 2013 Wiley Periodicals, Inc.

Crossing the Threshold From Porn Use to Porn Problem: Frequency and Modality of Porn Use as Predictors of Sexually Coercive Behaviors.

PubMed

Marshall, Ethan A; Miller, Holly A; Bouffard, Jeff A

2017-11-01

According to recent statistics, as many as one in five female college students are victims of sexual assault during their college career. To combat what has been called the "Campus Rape Crisis," researchers have attempted to understand what variables are associated with sexually coercive behaviors in college males. Although investigators have found support for the relationship between pornography consumption and sexually coercive behavior, researchers typically operationalize pornography use in terms of frequency of use. Furthermore, frequency of use has been assessed vaguely and inconsistently. The current study offered a more concrete assessment of frequency of use and an additional variable not yet included for pornography use: number of modalities. Beyond examining the relationship between pornography use and sexual coercion likelihood, the current study was the first to use pornography variables in a threshold analysis to test whether there is a cut point that is predictive of sexual coercion likelihood. Analyses were conducted with a sample of 463 college males. Results indicated that both pornography use variables were significantly related to a higher likelihood of sexually coercive behaviors. When both frequency of use and number of modalities were included in the model, modalities were significant and frequency was not. In addition, significant thresholds for both pornography variables that predicted sexual coercion likelihood were identified. These results imply that factors other than frequency of use, such as number of modalities, may be more important for the prediction of sexual coercive behaviors. Furthermore, threshold analyses revealed the most significant increase in risk occurred between one modality and two, indicating that it is not pornography use in general that is related to sexual coercion likelihood, but rather, specific aspects of pornography use.

Quantifying patterns of change in marine ecosystem response to multiple pressures.

PubMed

Large, Scott I; Fay, Gavin; Friedland, Kevin D; Link, Jason S

2015-01-01

The ability to understand and ultimately predict ecosystem response to multiple pressures is paramount to successfully implement ecosystem-based management. Thresholds shifts and nonlinear patterns in ecosystem responses can be used to determine reference points that identify levels of a pressure that may drastically alter ecosystem status, which can inform management action. However, quantifying ecosystem reference points has proven elusive due in large part to the multi-dimensional nature of both ecosystem pressures and ecosystem responses. We used ecological indicators, synthetic measures of ecosystem status and functioning, to enumerate important ecosystem attributes and to reduce the complexity of the Northeast Shelf Large Marine Ecosystem (NES LME). Random forests were used to quantify the importance of four environmental and four anthropogenic pressure variables to the value of ecological indicators, and to quantify shifts in aggregate ecological indicator response along pressure gradients. Anthropogenic pressure variables were critical defining features and were able to predict an average of 8-13% (up to 25-66% for individual ecological indicators) of the variation in ecological indicator values, whereas environmental pressures were able to predict an average of 1-5 % (up to 9-26% for individual ecological indicators) of ecological indicator variation. Each pressure variable predicted a different suite of ecological indicator's variation and the shapes of ecological indicator responses along pressure gradients were generally nonlinear. Threshold shifts in ecosystem response to exploitation, the most important pressure variable, occurred when commercial landings were 20 and 60% of total surveyed biomass. Although present, threshold shifts in ecosystem response to environmental pressures were much less important, which suggests that anthropogenic pressures have significantly altered the ecosystem structure and functioning of the NES LME. Gradient response curves provide ecologically informed transformations of pressure variables to explain patterns of ecosystem structure and functioning. By concurrently identifying thresholds for a suite of ecological indicator responses to multiple pressures, we demonstrate that ecosystem reference points can be evaluated and used to support ecosystem-based management.

Quantitative Sensory Testing Predicts Pregabalin Efficacy in Painful Chronic Pancreatitis

PubMed Central

Olesen, Søren S.; Graversen, Carina; Bouwense, Stefan A. W.; van Goor, Harry; Wilder-Smith, Oliver H. G.; Drewes, Asbjørn M.

2013-01-01

Background A major problem in pain medicine is the lack of knowledge about which treatment suits a specific patient. We tested the ability of quantitative sensory testing to predict the analgesic effect of pregabalin and placebo in patients with chronic pancreatitis. Methods Sixty-four patients with painful chronic pancreatitis received pregabalin (150–300 mg BID) or matching placebo for three consecutive weeks. Analgesic effect was documented in a pain diary based on a visual analogue scale. Responders were defined as patients with a reduction in clinical pain score of 30% or more after three weeks of study treatment compared to baseline recordings. Prior to study medication, pain thresholds to electric skin and pressure stimulation were measured in dermatomes T10 (pancreatic area) and C5 (control area). To eliminate inter-subject differences in absolute pain thresholds an index of sensitivity between stimulation areas was determined (ratio of pain detection thresholds in pancreatic versus control area, ePDT ratio). Pain modulation was recorded by a conditioned pain modulation paradigm. A support vector machine was used to screen sensory parameters for their predictive power of pregabalin efficacy. Results The pregabalin responders group was hypersensitive to electric tetanic stimulation of the pancreatic area (ePDT ratio 1.2 (0.9–1.3)) compared to non-responders group (ePDT ratio: 1.6 (1.5–2.0)) (P = 0.001). The electrical pain detection ratio was predictive for pregabalin effect with a classification accuracy of 83.9% (P = 0.007). The corresponding sensitivity was 87.5% and specificity was 80.0%. No other parameters were predictive of pregabalin or placebo efficacy. Conclusions The present study provides first evidence that quantitative sensory testing predicts the analgesic effect of pregabalin in patients with painful chronic pancreatitis. The method can be used to tailor pain medication based on patient’s individual sensory profile and thus comprises a significant step towards personalized pain medicine. PMID:23469256

Predicting potentially toxigenic Pseudo-nitzschia blooms in the Chesapeake Bay

USGS Publications Warehouse

Anderson, C.R.; Sapiano, M.R.P.; Prasad, M.B.K.; Long, W.; Tango, P.J.; Brown, C.W.; Murtugudde, R.

2010-01-01

Harmful algal blooms are now recognized as a significant threat to the Chesapeake Bay as they can severely compromise the economic viability of important recreational and commercial fisheries in the largest estuary of the United States. This study describes the development of empirical models for the potentially domoic acid-producing Pseudo-nitzschia species complex present in the Bay, developed from a 22-year time series of cell abundance and concurrent measurements of hydrographic and chemical properties. Using a logistic Generalized Linear Model (GLM) approach, model parameters and performance were compared over a range of Pseudo-nitzschia bloom thresholds relevant to toxin production by different species. Small-threshold blooms (???10cellsmL-1) are explained by time of year, location, and variability in surface values of phosphate, temperature, nitrate plus nitrite, and freshwater discharge. Medium- (100cellsmL-1) to large- threshold (1000cellsmL-1) blooms are further explained by salinity, silicic acid, dissolved organic carbon, and light attenuation (Secchi) depth. These predictors are similar to other models for Pseudo-nitzschia blooms on the west coast, suggesting commonalities across ecosystems. Hindcasts of bloom probabilities at a 19% bloom prediction point yield a Heidke Skill Score of -53%, a Probability of Detection ~75%, a False Alarm Ratio of ~52%, and a Probability of False Detection ~9%. The implication of possible future changes in Baywide nutrient stoichiometry on Pseudo-nitzschia blooms is discussed. ?? 2010 Elsevier B.V.

Identification of ecological thresholds from variations in phytoplankton communities among lakes: contribution to the definition of environmental standards.

PubMed

Roubeix, Vincent; Danis, Pierre-Alain; Feret, Thibaut; Baudoin, Jean-Marc

2016-04-01

In aquatic ecosystems, the identification of ecological thresholds may be useful for managers as it can help to diagnose ecosystem health and to identify key levers to enable the success of preservation and restoration measures. A recent statistical method, gradient forest, based on random forests, was used to detect thresholds of phytoplankton community change in lakes along different environmental gradients. It performs exploratory analyses of multivariate biological and environmental data to estimate the location and importance of community thresholds along gradients. The method was applied to a data set of 224 French lakes which were characterized by 29 environmental variables and the mean abundances of 196 phytoplankton species. Results showed the high importance of geographic variables for the prediction of species abundances at the scale of the study. A second analysis was performed on a subset of lakes defined by geographic thresholds and presenting a higher biological homogeneity. Community thresholds were identified for the most important physico-chemical variables including water transparency, total phosphorus, ammonia, nitrates, and dissolved organic carbon. Gradient forest appeared as a powerful method at a first exploratory step, to detect ecological thresholds at large spatial scale. The thresholds that were identified here must be reinforced by the separate analysis of other aquatic communities and may be used then to set protective environmental standards after consideration of natural variability among lakes.

Blood pressure-to-height ratio for screening prehypertension and hypertension in Chinese children.

PubMed

Dong, B; Wang, Z; Wang, H-J; Ma, J

2015-10-01

The diagnosis of hypertension in children is complicated because of the multiple age-, sex- and height-specific thresholds. To simplify the process of diagnosis, blood pressure-to-height ratio (BPHR) was employed in this study. Data were obtained from a Chinese national survey conducted in 2010, and 197 191 children aged 7-17 years were included. High normal and elevated blood pressure (BP) were defined according to the National High Blood Pressure Education Program (NHBPEP) Working Group definition. The optimal thresholds were selected by Youden's index. Sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and area under the curve (AUC) were assessed for the performance of these thresholds. The systolic and diastolic BPHR thresholds for identifying high normal BP were 0.84/0.55, 0.78/0.50 and 0.75/0.46 for children aged 7-8 years, 9-11 years and 12-17 years, respectively. The corresponding thresholds for identifying elevated BP were 0.87/0.57, 0.81/0.53 and 0.76/0.49, respectively. These proposed thresholds revealed high sensitivity and NPVs, all above 0.96, moderate to high specificity and AUCs, and low PPVs. Our finding suggested the proposed BPHR thresholds were accurate for identifying children without high normal or elevated BP, and could be employed to simplify the procedure of screening prehypertension and hypertension in children.

Evaluation of Maryland abutment scour equation through selected threshold velocity methods

USGS Publications Warehouse

Benedict, S.T.

2010-01-01

The U.S. Geological Survey, in cooperation with the Maryland State Highway Administration, used field measurements of scour to evaluate the sensitivity of the Maryland abutment scour equation to the critical (or threshold) velocity variable. Four selected methods for estimating threshold velocity were applied to the Maryland abutment scour equation, and the predicted scour to the field measurements were compared. Results indicated that performance of the Maryland abutment scour equation was sensitive to the threshold velocity with some threshold velocity methods producing better estimates of predicted scour than did others. In addition, results indicated that regional stream characteristics can affect the performance of the Maryland abutment scour equation with moderate-gradient streams performing differently from low-gradient streams. On the basis of the findings of the investigation, guidance for selecting threshold velocity methods for application to the Maryland abutment scour equation are provided, and limitations are noted.

Predicting coral bleaching hotspots: the role of regional variability in thermal stress and potential adaptation rates

NASA Astrophysics Data System (ADS)

Teneva, Lida; Karnauskas, Mandy; Logan, Cheryl A.; Bianucci, Laura; Currie, Jock C.; Kleypas, Joan A.

2012-03-01

Sea surface temperature fields (1870-2100) forced by CO2-induced climate change under the IPCC SRES A1B CO2 scenario, from three World Climate Research Programme Coupled Model Intercomparison Project Phase 3 (WCRP CMIP3) models (CCSM3, CSIRO MK 3.5, and GFDL CM 2.1), were used to examine how coral sensitivity to thermal stress and rates of adaption affect global projections of coral-reef bleaching. The focus of this study was two-fold, to: (1) assess how the impact of Degree-Heating-Month (DHM) thermal stress threshold choice affects potential bleaching predictions and (2) examine the effect of hypothetical adaptation rates of corals to rising temperature. DHM values were estimated using a conventional threshold of 1°C and a variability-based threshold of 2σ above the climatological maximum Coral adaptation rates were simulated as a function of historical 100-year exposure to maximum annual SSTs with a dynamic rather than static climatological maximum based on the previous 100 years, for a given reef cell. Within CCSM3 simulations, the 1°C threshold predicted later onset of mild bleaching every 5 years for the fraction of reef grid cells where 1°C > 2σ of the climatology time series of annual SST maxima (1961-1990). Alternatively, DHM values using both thresholds, with CSIRO MK 3.5 and GFDL CM 2.1 SSTs, did not produce drastically different onset timing for bleaching every 5 years. Across models, DHMs based on 1°C thermal stress threshold show the most threatened reefs by 2100 could be in the Central and Western Equatorial Pacific, whereas use of the variability-based threshold for DHMs yields the Coral Triangle and parts of Micronesia and Melanesia as bleaching hotspots. Simulations that allow corals to adapt to increases in maximum SST drastically reduce the rates of bleaching. These findings highlight the importance of considering the thermal stress threshold in DHM estimates as well as potential adaptation models in future coral bleaching projections.

Detection in fixed and random noise in foveal and parafoveal vision explained by template learning

NASA Technical Reports Server (NTRS)

Beard, B. L.; Ahumada, A. J. Jr; Watson, A. B. (Principal Investigator)

1999-01-01

Foveal and parafoveal contrast detection thresholds for Gabor and checkerboard targets were measured in white noise by means of a two-interval forced-choice paradigm. Two white-noise conditions were used: fixed and twin. In the fixed noise condition a single noise sample was presented in both intervals of all the trials. In the twin noise condition the same noise sample was used in the two intervals of a trial, but a new sample was generated for each trial. Fixed noise conditions usually resulted in lower thresholds than twin noise. Template learning models are presented that attribute this advantage of fixed over twin noise either to fixed memory templates' reducing uncertainty by incorporation of the noise or to the introduction, by the learning process itself, of more variability in the twin noise condition. Quantitative predictions of the template learning process show that it contributes to the accelerating nonlinear increase in performance with signal amplitude at low signal-to-noise ratios.

Poor outcome prediction by burst suppression ratio in adults with post-anoxic coma without hypothermia.

PubMed

Yang, Qinglin; Su, Yingying; Hussain, Mohammed; Chen, Weibi; Ye, Hong; Gao, Daiquan; Tian, Fei

2014-05-01

Burst suppression ratio (BSR) is a quantitative electroencephalography (qEEG) parameter. The purpose of our study was to compare the accuracy of BSR when compared to other EEG parameters in predicting poor outcomes in adults who sustained post-anoxic coma while not being subjected to therapeutic hypothermia. EEG was registered and recorded at least once within 7 days of post-anoxic coma onset. Electrodes were placed according to the international 10-20 system, using a 16-channel layout. Each EEG expert scored raw EEG using a grading scale adapted from Young and scored amplitude-integrated electroencephalography tracings, in addition to obtaining qEEG parameters defined as BSR with a defined threshold. Glasgow outcome scales of 1 and 2 at 3 months, determined by two blinded neurologists, were defined as poor outcome. Sixty patients with Glasgow coma scale score of 8 or less after anoxic accident were included. The sensitivity (97.1%), specificity (73.3%), positive predictive value (82.5%), and negative prediction value (95.0%) of BSR in predicting poor outcome were higher than other EEG variables. BSR1 and BSR2 were reliable in predicting death (area under the curve > 0.8, P < 0.05), with the respective cutoff points being 39.8% and 61.6%. BSR1 was reliable in predicting poor outcome (area under the curve  =  0.820, P < 0.05) with a cutoff point of 23.9%. BSR1 was also an independent predictor of increased risk of death (odds ratio  =  1.042, 95% confidence intervals: 1.012-1.073, P  =  0.006). BSR may be a better predictor in prognosticating poor outcomes in patients with post-anoxic coma who do not undergo therapeutic hypothermia when compared to other qEEG parameters.

Variability in expression of anadromy by female Oncorhynchus mykiss within a river network

USGS Publications Warehouse

Mills, Justin S.; Dunham, Jason B.; Reeves, Gordon H.; McMillan, John R.; Zimmerman, Christian E.; Jordan, Chris E.

2012-01-01

We described and predicted spatial variation in marine migration (anadromy) of female Oncorhynchus mykiss in the John Day River watershed, Oregon. We collected 149 juvenile O. mykiss across 72 sites and identified locations used by anadromous females by assigning maternal origin (anadromous versus non-anadromous) to each juvenile. These assignments used comparisons of strontium to calcium ratios in otolith primordia and freshwater growth regions to indicate maternal origin. We used logistic regression to predict probability of anadromy in relation to mean annual stream runoff using data from a subset of individuals. This model correctly predicted anadromy in a second sample of individuals with a moderate level of accuracy (e.g., 68% correctly predicted with a 0.5 classification threshold). Residuals from the models were not spatially autocorrelated, suggesting that remaining variability in the expression of anadromy was due to localized influences, as opposed to broad-scale gradients unrelated to mean annual stream runoff. These results are important for the management of O. mykiss because anadromous individuals (steelhead) within the John Day River watershed are listed as a threatened species, and it is difficult to discern juvenile steelhead from non-anadromous individuals (rainbow trout) in the field. Our results provide a broad-scale description and prediction of locations supporting anadromy, and new insight for habitat restoration, monitoring, and research to better manage and understand the expression of anadromy in O. mykiss.

A study of life prediction differences for a nickel-base Alloy 690 using a threshold and a non-threshold model

NASA Astrophysics Data System (ADS)

Young, B. A.; Gao, Xiaosheng; Srivatsan, T. S.

2009-10-01

In this paper we compare and contrast the crack growth rate of a nickel-base superalloy (Alloy 690) in the Pressurized Water Reactor (PWR) environment. Over the last few years, a preponderance of test data has been gathered on both Alloy 690 thick plate and Alloy 690 tubing. The original model, essentially based on a small data set for thick plate, compensated for temperature, load ratio and stress-intensity range but did not compensate for the fatigue threshold of the material. As additional test data on both plate and tube product became available the model was gradually revised to account for threshold properties. Both the original and revised models generated acceptable results for data that were above 1 × 10 -11 m/s. However, the test data at the lower growth rates were over-predicted by the non-threshold model. Since the original model did not take the fatigue threshold into account, this model predicted no operating stress below which the material would effectively undergo fatigue crack growth. Because of an over-prediction of the growth rate below 1 × 10 -11 m/s, due to a combination of low stress, small crack size and long rise-time, the model in general leads to an under-prediction of the total available life of the components.

Mean Platelet Volume (MPV), Platelet Distribution Width (PDW), Platelet Count and Plateletcrit (PCT) as predictors of in-hospital paediatric mortality: a case-control Study.

PubMed

Golwala, Zainab Mohammedi; Shah, Hardik; Gupta, Neeraj; Sreenivas, V; Puliyel, Jacob M

2016-06-01

Thrombocytopenia has been shown to predict mortality. We hypothesize that platelet indices may be more useful prognostic indicators. Our study subjects were children one month to 14 years old admitted to our hospital. To determine whether platelet count, plateletcrit (PCT), mean platelet volume (MPV) and platelet distribution width (PDW) and their ratios can predict mortality in hospitalised children. Children who died during hospital stay were the cases. Controls were age matched children admitted contemporaneously. The first blood sample after admission was used for analysis. Receiver operating characteristic (ROC) curve was used to identify the best threshold for measured variables and the ratios studied. Multiple regression analysis was done to identify independent predictors of mortality. Forty cases and forty controls were studied. Platelet count, PCT and the ratios of MPV/Platelet count, MPV/PCT, PDW/Platelet count, PDW/PCT and MPV × PDW/Platelet count × PCT were significantly different among children who survived compared to those who died. On multiple regression analysis the ratio of MPV/PCT, PDW/Platelet count and MPV/Platelet count were risk factors for mortality with an odds ratio of 4.31(95% CI, 1.69-10.99), 3.86 (95% CI, 1.53-9.75), 3.45 (95% CI, 1.38-8.64) respectively. In 67% of the patients who died MPV/PCT ratio was above 41.8 and PDW/Platelet count was above 3.86. In 65% of patients who died MPV/Platelet count was above 3.45. The MPV/PCT, PDW/Platelet count and MPV/Platelet count, in the first sample after admission in this case control study were predictors of mortality and could predict 65% to 67% of deaths accurately.

Physical Performance Measures Associated With Locomotive Syndrome in Middle-Aged and Older Japanese Women.

PubMed

Nakamura, Misa; Hashizume, Hiroshi; Oka, Hiroyuki; Okada, Morihiro; Takakura, Rie; Hisari, Ayako; Yoshida, Munehito; Utsunomiya, Hirotoshi

2015-01-01

The Japanese Orthopaedic Association proposed a concept called locomotive syndrome (LS) to identify middle-aged and older adults at high risk of requiring health care services because of problems with locomotion. It is important to identify factors associated with the development of LS. Physical performance measures such as walking speed and standing balance are highly predictive of subsequent disability and mortality in older adults. However, there is little evidence about the relationship between physical performance measures and LS. To determine the physical performance measures associated with LS, the threshold values for discriminating individuals with and without LS, and the odds ratio of LS according to performance greater than or less than these thresholds in middle-aged and older Japanese women. Participants were 126 Japanese women (mean age = 61.8 years). Locomotive syndrome was defined as a score of 16 or more on the 25-question Geriatric Locomotive Function Scale. Physical performance was evaluated using grip strength, unipedal stance time with eyes open, seated toe-touch, and normal and fast 6-m walk time (6 MWT). Variables were compared between LS and non-LS groups. Fourteen participants (11.1%) were classed as having LS. Unipedal stance time, normal 6 MWT, and fast 6 MWT were significantly different between the 2 groups. The LS group had a shorter unipedal stance time and a longer normal and fast 6 MWT than the non-LS group. For these 3 variables, the area under the receiver operating characteristic curve was greater than 0.7, and the threshold for discriminating the non-LS and LS groups was 15 s for unipedal stance time, 4.8 s for normal 6 MWT and 3.6 s for fast 6 MWT. These variables were entered into a multiple logistic regression analysis, which indicated that unipedal stance time less than 15 s was significantly related to LS (odds ratio = 8.46; P < .01). Unipedal stance time was the physical performance measure that was most strongly associated with LS. This measure may be useful for early detection of LS.

Predicting potentially toxigenic Pseudo-nitzschia blooms in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Anderson, Clarissa R.; Sapiano, Mathew R. P.; Prasad, M. Bala Krishna; Long, Wen; Tango, Peter J.; Brown, Christopher W.; Murtugudde, Raghu

2010-11-01

Harmful algal blooms are now recognized as a significant threat to the Chesapeake Bay as they can severely compromise the economic viability of important recreational and commercial fisheries in the largest estuary of the United States. This study describes the development of empirical models for the potentially domoic acid-producing Pseudo-nitzschia species complex present in the Bay, developed from a 22-year time series of cell abundance and concurrent measurements of hydrographic and chemical properties. Using a logistic Generalized Linear Model (GLM) approach, model parameters and performance were compared over a range of Pseudo-nitzschia bloom thresholds relevant to toxin production by different species. Small-threshold blooms (≥10 cells mL -1) are explained by time of year, location, and variability in surface values of phosphate, temperature, nitrate plus nitrite, and freshwater discharge. Medium- (100 cells mL -1) to large- threshold (1000 cells mL -1) blooms are further explained by salinity, silicic acid, dissolved organic carbon, and light attenuation (Secchi) depth. These predictors are similar to other models for Pseudo-nitzschia blooms on the west coast, suggesting commonalities across ecosystems. Hindcasts of bloom probabilities at a 19% bloom prediction point yield a Heidke Skill Score of ~53%, a Probability of Detection ˜ 75%, a False Alarm Ratio of ˜ 52%, and a Probability of False Detection ˜9%. The implication of possible future changes in Baywide nutrient stoichiometry on Pseudo-nitzschia blooms is discussed.

A principled approach to setting optimal diagnostic thresholds: where ROC and indifference curves meet.

PubMed

Irwin, R John; Irwin, Timothy C

2011-06-01

Making clinical decisions on the basis of diagnostic tests is an essential feature of medical practice and the choice of the decision threshold is therefore crucial. A test's optimal diagnostic threshold is the threshold that maximizes expected utility. It is given by the product of the prior odds of a disease and a measure of the importance of the diagnostic test's sensitivity relative to its specificity. Choosing this threshold is the same as choosing the point on the Receiver Operating Characteristic (ROC) curve whose slope equals this product. We contend that a test's likelihood ratio is the canonical decision variable and contrast diagnostic thresholds based on likelihood ratio with two popular rules of thumb for choosing a threshold. The two rules are appealing because they have clear graphical interpretations, but they yield optimal thresholds only in special cases. The optimal rule can be given similar appeal by presenting indifference curves, each of which shows a set of equally good combinations of sensitivity and specificity. The indifference curve is tangent to the ROC curve at the optimal threshold. Whereas ROC curves show what is feasible, indifference curves show what is desirable. Together they show what should be chosen. Copyright © 2010 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

A Continuous Threshold Expectile Model.

PubMed

Zhang, Feipeng; Li, Qunhua

2017-12-01

Expectile regression is a useful tool for exploring the relation between the response and the explanatory variables beyond the conditional mean. A continuous threshold expectile regression is developed for modeling data in which the effect of a covariate on the response variable is linear but varies below and above an unknown threshold in a continuous way. The estimators for the threshold and the regression coefficients are obtained using a grid search approach. The asymptotic properties for all the estimators are derived, and the estimator for the threshold is shown to achieve root-n consistency. A weighted CUSUM type test statistic is proposed for the existence of a threshold at a given expectile, and its asymptotic properties are derived under both the null and the local alternative models. This test only requires fitting the model under the null hypothesis in the absence of a threshold, thus it is computationally more efficient than the likelihood-ratio type tests. Simulation studies show that the proposed estimators and test have desirable finite sample performance in both homoscedastic and heteroscedastic cases. The application of the proposed method on a Dutch growth data and a baseball pitcher salary data reveals interesting insights. The proposed method is implemented in the R package cthreshER .

Predicting the susceptibility to gully initiation in data-poor regions

NASA Astrophysics Data System (ADS)

Dewitte, Olivier; Daoudi, Mohamed; Bosco, Claudio; Van Den Eeckhaut, Miet

2015-01-01

Permanent gullies are common features in many landscapes and quite often they represent the dominant soil erosion process. Once a gully has initiated, field evidence shows that gully channel formation and headcut migration rapidly occur. In order to prevent the undesired effects of gullying, there is a need to predict the places where new gullies might initiate. From detailed field measurements, studies have demonstrated strong inverse relationships between slope gradient of the soil surface (S) and drainage area (A) at the point of channel initiation across catchments in different climatic and morphological environments. Such slope-area thresholds (S-A) can be used to predict locations in the landscape where gullies might initiate. However, acquiring S-A requires detailed field investigations and accurate high resolution digital elevation data, which are usually difficult to acquire. To circumvent this issue, we propose a two-step method that uses published S-A thresholds and a logistic regression analysis (LR). S-A thresholds from the literature are used as proxies of field measurement. The method is calibrated and validated on a watershed, close to the town of Algiers, northern Algeria, where gully erosion affects most of the slopes. The gullies extend up to several kilometres in length and cover 16% of the study area. First we reconstruct the initiation areas of the existing gullies by applying S-A thresholds for similar environments. Then, using the initiation area map as the dependent variable with combinations of topographic and lithological predictor variables, we calibrate several LR models. It provides relevant results in terms of statistical reliability, prediction performance, and geomorphological significance. This method using S-A thresholds with data-driven assessment methods like LR proves to be efficient when applied to common spatial data and establishes a methodology that will allow similar studies to be undertaken elsewhere.

Clinical predictors of conversion to bipolar disorder in a prospective longitudinal familial high-risk sample: focus on depressive features.

PubMed

Frankland, Andrew; Roberts, Gloria; Holmes-Preston, Ellen; Perich, Tania; Levy, Florence; Lenroot, Rhoshel; Hadzi-Pavlovic, Dusan; Breakspear, Michael; Mitchell, Philip B

2017-11-07

Identifying clinical features that predict conversion to bipolar disorder (BD) in those at high familial risk (HR) would assist in identifying a more focused population for early intervention. In total 287 participants aged 12-30 (163 HR with a first-degree relative with BD and 124 controls (CONs)) were followed annually for a median of 5 years. We used the baseline presence of DSM-IV depressive, anxiety, behavioural and substance use disorders, as well as a constellation of specific depressive symptoms (as identified by the Probabilistic Approach to Bipolar Depression) to predict the subsequent development of hypo/manic episodes. At baseline, HR participants were significantly more likely to report ⩾4 Probabilistic features (40.4%) when depressed than CONs (6.7%; p < .05). Nineteen HR subjects later developed either threshold (n = 8; 4.9%) or subthreshold (n = 11; 6.7%) hypo/mania. The presence of ⩾4 Probabilistic features was associated with a seven-fold increase in the risk of 'conversion' to threshold BD (hazard ratio = 6.9, p < .05) above and beyond the fourteen-fold increase in risk related to major depressive episodes (MDEs) per se (hazard ratio = 13.9, p < .05). Individual depressive features predicting conversion were psychomotor retardation and ⩾5 MDEs. Behavioural disorders only predicted conversion to subthreshold BD (hazard ratio = 5.23, p < .01), while anxiety and substance disorders did not predict either threshold or subthreshold hypo/mania. This study suggests that specific depressive characteristics substantially increase the risk of young people at familial risk of BD going on to develop future hypo/manic episodes and may identify a more targeted HR population for the development of early intervention programs.

Auditory brainstem response to complex sounds predicts self-reported speech-in-noise performance.

PubMed

Anderson, Samira; Parbery-Clark, Alexandra; White-Schwoch, Travis; Kraus, Nina

2013-02-01

To compare the ability of the auditory brainstem response to complex sounds (cABR) to predict subjective ratings of speech understanding in noise on the Speech, Spatial, and Qualities of Hearing Scale (SSQ; Gatehouse & Noble, 2004) relative to the predictive ability of the Quick Speech-in-Noise test (QuickSIN; Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004) and pure-tone hearing thresholds. Participants included 111 middle- to older-age adults (range = 45-78) with audiometric configurations ranging from normal hearing levels to moderate sensorineural hearing loss. In addition to using audiometric testing, the authors also used such evaluation measures as the QuickSIN, the SSQ, and the cABR. Multiple linear regression analysis indicated that the inclusion of brainstem variables in a model with QuickSIN, hearing thresholds, and age accounted for 30% of the variance in the Speech subtest of the SSQ, compared with significantly less variance (19%) when brainstem variables were not included. The authors' results demonstrate the cABR's efficacy for predicting self-reported speech-in-noise perception difficulties. The fact that the cABR predicts more variance in self-reported speech-in-noise (SIN) perception than either the QuickSIN or hearing thresholds indicates that the cABR provides additional insight into an individual's ability to hear in background noise. In addition, the findings underscore the link between the cABR and hearing in noise.

Experimental evidence of a pathogen invasion threshold

PubMed Central

Krkošek, Martin

2018-01-01

Host density thresholds to pathogen invasion separate regions of parameter space corresponding to endemic and disease-free states. The host density threshold is a central concept in theoretical epidemiology and a common target of human and wildlife disease control programmes, but there is mixed evidence supporting the existence of thresholds, especially in wildlife populations or for pathogens with complex transmission modes (e.g. environmental transmission). Here, we demonstrate the existence of a host density threshold for an environmentally transmitted pathogen by combining an epidemiological model with a microcosm experiment. Experimental epidemics consisted of replicate populations of naive crustacean zooplankton (Daphnia dentifera) hosts across a range of host densities (20–640 hosts l−1) that were exposed to an environmentally transmitted fungal pathogen (Metschnikowia bicuspidata). Epidemiological model simulations, parametrized independently of the experiment, qualitatively predicted experimental pathogen invasion thresholds. Variability in parameter estimates did not strongly influence outcomes, though systematic changes to key parameters have the potential to shift pathogen invasion thresholds. In summary, we provide one of the first clear experimental demonstrations of pathogen invasion thresholds in a replicated experimental system, and provide evidence that such thresholds may be predictable using independently constructed epidemiological models. PMID:29410876

Variation of surface ozone in Campo Grande, Brazil: meteorological effect analysis and prediction.

PubMed

Pires, J C M; Souza, A; Pavão, H G; Martins, F G

2014-09-01

The effect of meteorological variables on surface ozone (O3) concentrations was analysed based on temporal variation of linear correlation and artificial neural network (ANN) models defined by genetic algorithms (GAs). ANN models were also used to predict the daily average concentration of this air pollutant in Campo Grande, Brazil. Three methodologies were applied using GAs, two of them considering threshold models. In these models, the variables selected to define different regimes were daily average O3 concentration, relative humidity and solar radiation. The threshold model that considers two O3 regimes was the one that correctly describes the effect of important meteorological variables in O3 behaviour, presenting also a good predictive performance. Solar radiation, relative humidity and rainfall were considered significant for both O3 regimes; however, wind speed (dispersion effect) was only significant for high concentrations. According to this model, high O3 concentrations corresponded to high solar radiation, low relative humidity and wind speed. This model showed to be a powerful tool to interpret the O3 behaviour, being useful to define policy strategies for human health protection regarding air pollution.

Assessing the detection capability of a dense infrasound network in the southern Korean Peninsula

NASA Astrophysics Data System (ADS)

Che, Il-Young; Le Pichon, Alexis; Kim, Kwangsu; Shin, In-Cheol

2017-08-01

The Korea Infrasound Network (KIN) is a dense seismoacoustic array network consisting of eight small-aperture arrays with an average interarray spacing of ∼100 km. The processing of the KIN historical recordings over 10 yr in the 0.05-5 Hz frequency band shows that the dominant sources of signals are microbaroms and human activities. The number of detections correlates well with the seasonal and daily variability of the stratospheric wind dynamics. The quantification of the spatiotemporal variability of the KIN detection performance is simulated using a frequency-dependent semi-empirical propagation modelling technique. The average detection thresholds predicted for the region of interest by using both the KIN arrays and the International Monitoring System (IMS) infrasound station network at a given frequency of 1.6 Hz are estimated to be 5.6 and 10.0 Pa for two- and three-station coverage, respectively, which was about three times lower than the thresholds predicted by using only the IMS stations. The network performance is significantly enhanced from May to August, with detection thresholds being one order of magnitude lower than the rest of the year due to prevailing steady stratospheric winds. To validate the simulations, the amplitudes of ground-truth repeated surface mining explosions at an open-pit limestone mine were measured over a 19-month period. Focusing on the spatiotemporal variability of the stratospheric winds which control to first order where infrasound signals are expected to be detected, the predicted detectable signal amplitude at the mine and the detection capability at one KIN array located at a distance of 175 km are found to be in good agreement with the observations from the measurement campaign. The detection threshold in summer is ∼2 Pa and increases up to ∼300 Pa in winter. Compared with the low and stable thresholds in summer, the high temporal variability of the KIN performance is well predicted throughout the year. Simulations show that the performance of the global infrasound network of the IMS is significantly improved by adding KIN. This study shows the usefulness of dense regional networks to enhance detection capability in regions of interest in the context of future verification of the Comprehensive Nuclear-Test-Ban Treaty.

Polarization asymmetry in two-electron photodetachment - A cogent test of the ionization threshold law

NASA Technical Reports Server (NTRS)

Temkin, A.; Bhatia, A. K.

1988-01-01

A very sensitive test of the electron-atom ionization threshold law is suggested: for spin-aligned heavy negative ions it consists of measuring the polarization asymmetry A(PA) coming from double detachment by left- versus right-circularly polarized light. The respective yields are worked out for the Te(-) (5p)5 2P(3/2) ion. The Coulomb-dipole theory predicts A(PA) to be the ratio of two oscillating functions in sharp contrast to any power law (specifically that of Wannier, 1953) for which the ratio is expected to be a smooth function of energy.

Erosive Augmentation of Solid Propellant Burning Rate: Motor Size Scaling Effect

NASA Technical Reports Server (NTRS)

Strand, L. D.; Cohen, Norman S.

1990-01-01

Two different independent variable forms, a difference form and a ratio form, were investigated for correlating the normalized magnitude of the measured erosive burning rate augmentation above the threshold in terms of the amount that the driving parameter (mass flux or Reynolds number) exceeds the threshold value for erosive augmentation at the test condition. The latter was calculated from the previously determined threshold correlation. Either variable form provided a correlation for each of the two motor size data bases individually. However, the data showed a motor size effect, supporting the general observation that the magnitude of erosive burning rate augmentation is reduced for larger rocket motors. For both independent variable forms, the required motor size scaling was attained by including the motor port radius raised to a power in the independent parameter. A boundary layer theory analysis confirmed the experimental finding, but showed that the magnitude of the scale effect is itself dependent upon scale, tending to diminish with increasing motor size.

Lymph node ratio predicts disease-specific survival in melanoma patients.

PubMed

Xing, Yan; Badgwell, Brian D; Ross, Merrick I; Gershenwald, Jeffrey E; Lee, Jeffrey E; Mansfield, Paul F; Lucci, Anthony; Cormier, Janice N

2009-06-01

The objectives of this analysis were to compare various measures associated with lymph node (LN) dissection and to identify threshold values associated with disease-specific survival (DSS) outcomes in patients with melanoma. Patients with lymph node-positive melanoma who underwent therapeutic LN dissection of the neck, axilla, and inguinal region were identified from the SEER database (1988-2005). We performed Cox multivariate analyses to determine the impact of the total number of LNs removed, number of negative LNs removed, and LN ratio on DSS. Multivariate cut-point analyses were conducted for each anatomic region to identify the threshold values associated with the largest improvement in DSS. The LN ratio was significantly associated with DSS for all LN regions. The LN ratio thresholds resulting in the greatest difference in 5-year DSS were .07, .13, and .18 for neck, axillary, and inguinal regions, respectively, corresponding to 15, 8, and 6 LNs removed per positive lymph node. After adjustment for other clinicopathologic factors, the hazard ratios (HRs) were .53 (95% confidence interval [CI], .40 to .71) in the neck, .52 (95% CI, .42 to .65) in the axillary, and .47 (95% CI, .36 to .61) in the inguinal regions for patients who met the LN ratio threshold. Among the prognostic factors examined, LN ratio was the best indicator of the extent of LN dissection, regardless of anatomic nodal region. These data provide evidence-based guidelines for defining adequate LN dissections in melanoma patients. (c) 2009 American Cancer Society.

Excitation-based and informational masking of a tonal signal in a four-tone masker.

PubMed

Leibold, Lori J; Hitchens, Jack J; Buss, Emily; Neff, Donna L

2010-04-01

This study examined contributions of peripheral excitation and informational masking to the variability in masking effectiveness observed across samples of multi-tonal maskers. Detection thresholds were measured for a 1000-Hz signal presented simultaneously with each of 25, four-tone masker samples. Using a two-interval, forced-choice adaptive task, thresholds were measured with each sample fixed throughout trial blocks for ten listeners. Average thresholds differed by as much as 26 dB across samples. An excitation-based model of partial loudness [Moore, B. C. J. et al. (1997). J. Audio Eng. Soc. 45, 224-237] was used to predict thresholds. These predictions accounted for a significant portion of variance in the data of several listeners, but no relation between the model and data was observed for many listeners. Moreover, substantial individual differences, on the order of 41 dB, were observed for some maskers. The largest individual differences were found for maskers predicted to produce minimal excitation-based masking. In subsequent conditions, one of five maskers was randomly presented in each interval. The difference in performance for samples with low versus high predicted thresholds was reduced in random compared to fixed conditions. These findings are consistent with a trading relation whereby informational masking is largest for conditions in which excitation-based masking is smallest.

Novel wavelet threshold denoising method in axle press-fit zone ultrasonic detection

NASA Astrophysics Data System (ADS)

Peng, Chaoyong; Gao, Xiaorong; Peng, Jianping; Wang, Ai

2017-02-01

Axles are important part of railway locomotives and vehicles. Periodic ultrasonic inspection of axles can effectively detect and monitor axle fatigue cracks. However, in the axle press-fit zone, the complex interface contact condition reduces the signal-noise ratio (SNR). Therefore, the probability of false positives and false negatives increases. In this work, a novel wavelet threshold function is created to remove noise and suppress press-fit interface echoes in axle ultrasonic defect detection. The novel wavelet threshold function with two variables is designed to ensure the precision of optimum searching process. Based on the positive correlation between the correlation coefficient and SNR and with the experiment phenomenon that the defect and the press-fit interface echo have different axle-circumferential correlation characteristics, a discrete optimum searching process for two undetermined variables in novel wavelet threshold function is conducted. The performance of the proposed method is assessed by comparing it with traditional threshold methods using real data. The statistic results of the amplitude and the peak SNR of defect echoes show that the proposed wavelet threshold denoising method not only maintains the amplitude of defect echoes but also has a higher peak SNR.

Effect of difference in occlusal contact area of mandibular free-end edentulous area implants on periodontal mechanosensitive threshold of adjacent premolars.

PubMed

Terauchi, Rie; Arai, Korenori; Tanaka, Masahiro; Kawazoe, Takayoshi; Baba, Shunsuke

2015-01-01

Implant treatment is believed to cause minimal invasion of remaining teeth. However, few studies have examined teeth adjacent to an implant region. Therefore, this study investigated the effect of occlusal contact size of implants on the periodontal mechanosensitive threshold of adjacent premolars. A cross-sectional study design was adopted. The Department of Oral Implantology, Osaka Dental University, was the setting where patients underwent implant treatment in the mandibular free-end edentulous area. The study population comprised of 87 patients (109 teeth) who underwent follow-up observation for at least 3 years following implant superstructure placement. As variables, age, sex, duration following superstructure placement, presence or absence of dental pulp, occlusal contact area, and periodontal mechanosensitive threshold were considered. The occlusal contact area was measured using Blue Silicone(®)and Bite Eye BE-I(®). Periodontal mechanosensitive threshold were measured using von Frey hair. As quantitative variables for periodontal mechanosensitive threshold, we divided subjects into two groups: normal (≤5 g) and high (≥5.1 g). For statistical analysis, we compared the two groups for the sensation thresholds using the Chi square test for categorical data and the Mann-Whitney U test for continuous volume data. For variables in which a significant difference was noted, we calculated the odds ratio (95 % confidence interval) and the effective dose. There were 93 teeth in the normal group and 16 teeth in the high group based on periodontal mechanosensitive threshold. Comparison of the two groups indicated no significant differences associated with age, sex, duration following superstructure placement, or presence or absence of dental pulp. A significant difference was noted with regard to occlusal contact area, with several high group subjects belonging to the small contact group (odds ratio: 4.75 [1.42-15.87]; effective dose: 0.29). The results of this study suggest an association between implant occlusal contact area and the periodontal mechanosensitive threshold of adjacent premolars. Smaller occlusal contact application resulted in an increased threshold. It appears that prosthodontic treatment should aim not only to improve occlusal function but also to maintain oromandibular function with regard to the preservation of remaining teeth.

Use of high-frequency peak in spectral analysis of heart rate increment to improve screening of obstructive sleep apnoea.

PubMed

Poupard, Laurent; Court-Fortune, Isabelle; Pichot, Vincent; Chouchou, Florian; Barthélémy, Jean-Claude; Roche, Frédéric

2011-12-01

Several studies have correlated the ratio of the very low frequency power spectral density of heart rate increment (%VLFI) with obstructive sleep apnoea syndrome (OSAS). However, patients with impaired heart rate variability may exhibit large variations of heart rate increment (HRI) spectral pattern and alter the screening accuracy of the method. To overcome this limitation, the present study uses the high-frequency increment (HFI) peak in the HRI spectrum, which corresponds to the respiratory influence on RR variations over the frequency range 0.2 to 0.4 Hz. We evaluated 288 consecutive patients referred for snoring, observed nocturnal breathing cessation and/or daytime sleepiness. Patients were classified as OSAS if their apnoea plus hypopnoea index (AHI) during polysomnography exceeded 15 events per hour. Synchronized electrocardiogram Holter monitoring allowed HRI analysis. Using a %VLFI threshold >2.4% for identifying the presence of OSAS, sensitivity for OSAS was 74.9%, specificity 51%, positive predictive value 54.9% and negative predictive value 71.7% (33 false negative subjects). Using threshold for %VLFI >2.4% and HFI peak position >0.4 Hz, negative predictive value increased to 78.2% while maintaining specificity at 50.6%. Among 11 subjects with %VLFI <2.4% and HFI peak >0.4 Hz, nine demonstrated moderate to severe OSAS (AHI >30). HFI represents a minimal physiological criterion for applying %VLFI by ensuring that heart rate variations are band frequency limited.

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis; Negri, Jacquelyn; Kean, Jason

2016-04-01

Population expansion into fire-prone steeplands has resulted in an increase in post-fire debris-flow risk in the western United States. Logistic regression methods for determining debris-flow likelihood and the calculation of empirical rainfall intensity-duration thresholds for debris-flow initiation represent two common approaches for characterizing hazard and reducing risk. Logistic regression models are currently being used to rapidly assess debris-flow hazard in response to design storms of known intensities (e.g. a 10-year recurrence interval rainstorm). Empirical rainfall intensity-duration thresholds comprise a major component of the United States Geological Survey (USGS) and the National Weather Service (NWS) debris-flow early warning system at a regional scale in southern California. However, these two modeling approaches remain independent, with each approach having limitations that do not allow for synergistic local-scale (e.g. drainage-basin scale) characterization of debris-flow hazard during intense rainfall. The current logistic regression equations consider rainfall a unique independent variable, which prevents the direct calculation of the relation between rainfall intensity and debris-flow likelihood. Regional (e.g. mountain range or physiographic province scale) rainfall intensity-duration thresholds fail to provide insight into the basin-scale variability of post-fire debris-flow hazard and require an extensive database of historical debris-flow occurrence and rainfall characteristics. Here, we present a new approach that combines traditional logistic regression and intensity-duration threshold methodologies. This method allows for local characterization of both the likelihood that a debris-flow will occur at a given rainfall intensity, the direct calculation of the rainfall rates that will result in a given likelihood, and the ability to calculate spatially explicit rainfall intensity-duration thresholds for debris-flow generation in recently burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

Monitoring Start of Season in Alaska

NASA Astrophysics Data System (ADS)

Robin, J.; Dubayah, R.; Sparrow, E.; Levine, E.

2006-12-01

In biomes that have distinct winter seasons, start of spring phenological events, specifically timing of budburst and green-up of leaves, coincides with transpiration. Seasons leave annual signatures that reflect the dynamic nature of the hydrologic cycle and link the different spheres of the Earth system. This paper evaluates whether continuity between AVHRR and MODIS normalized difference vegetation index (NDVI) is achievable for monitoring land surface phenology, specifically start of season (SOS), in Alaska. Additionally, two thresholds, one based on NDVI and the other on accumulated growing degree-days (GDD), are compared to determine which most accurately predicts SOS for Fairbanks. Ratio of maximum greenness at SOS was computed from biweekly AVHRR and MODIS composites for 2001 through 2004 for Anchorage and Fairbanks regions. SOS dates were determined from annual green-up observations made by GLOBE students. Results showed that different processing as well as spectral characteristics of each sensor restrict continuity between the two datasets. MODIS values were consistently higher and had less inter-annual variability during the height of the growing season than corresponding AVHRR values. Furthermore, a threshold of 131-175 accumulated GDD was a better predictor of SOS for Fairbanks than a NDVI threshold applied to AVHRR and MODIS datasets. The NDVI threshold was developed from biweekly AVHRR composites from 1982 through 2004 and corresponding annual green-up observations at University of Alaska-Fairbanks (UAF). The GDD threshold was developed from 20+ years of historic daily mean air temperature data and the same green-up observations. SOS dates computed with the GDD threshold most closely resembled actual green-up dates observed by GLOBE students and UAF researchers. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska.

Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.

USGS Publications Warehouse

Dudley, Robert W.; Hodgkins, Glenn A.; Dickinson, Jesse

2017-01-01

We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater-level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness-of-fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month-to-month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low-threshold events. We identified challenges in deriving probabilistic-forecasting models and possible approaches for addressing those challenges.

Linking Remotely Sensed Aerosol Types to Their Chemical Composition

NASA Technical Reports Server (NTRS)

Dawson, Kyle William; Kacenelenbogen, Meloe S.; Johnson, Matthew S.; Burton, Sharon P.; Hostetler, Chris A.; Meskhidze, Nicholas

2016-01-01

Aerosol types measured during the Ship-Aircraft Bio-Optical Research (SABOR) experiment are related to GEOS-Chem model chemical composition. The application for this procedure to link model chemical components to aerosol type is desirable for understanding aerosol evolution over time. The Mahalanobis distance (DM) statistic is used to cluster model groupings of five chemical components (organic carbon, black carbon, sea salt, dust and sulfate) in a way analogous to the methods used by Burton et al. [2012] and Russell et al. [2014]. First, model-to-measurement evaluation is performed by collocating vertically resolved aerosol extinction from SABOR High Spectral Resolution LiDAR (HSRL) to the GEOS-Chem nested high-resolution data. Comparisons of modeled-to-measured aerosol extinction are shown to be within 35% +/- 14%. Second, the model chemical components are calculation into five variables to calculate the DM and cluster means and covariances for each HSRL-retrieved aerosol type. The layer variables from the model are aerosol optical depth (AOD) ratios of (i) sea salt and (ii) dust to total AOD, mass ratios of (iii) total carbon (i.e. sum of organic and black carbon) to the sum of total carbon and sulfate (iv) organic carbon to black carbon, and (v) the natural log of the aerosol-to-molecular extinction ratio. Third, the layer variables and at most five out of twenty SABOR flights are used to form the pre-specified clusters for calculating DM and to assign an aerosol type. After determining the pre-specified clusters, model aerosol types are produced for the entire vertically resolved GEOS-Chem nested domain over the United States and the model chemical component distributions relating to each type are recorded. Resulting aerosol types are Dust/Dusty Mix, Maritime, Smoke, Urban and Fresh Smoke (separated into 'dark' and 'light' by a threshold of the organic to black carbon ratio). Model-calculated DM not belonging to a specific type (i.e. not meeting a threshold probability) is termed an outlier and those DM values that can belong to multiple types (i.e. showing weak probability of belonging to a specific cluster) are termed as Overlap. MODIS active fires are overlaid on the model domain to qualitatively evaluate the model-predicted Smoke aerosol types.

Linking remotely sensed aerosol types to their chemical composition

NASA Astrophysics Data System (ADS)

Dawson, K. W.; Kacenelenbogen, M. S.; Johnson, M. S.; Burton, S. P.; Hostetler, C. A.; Meskhidze, N.

2016-12-01

Aerosol types measured during the Ship-Aircraft Bio-Optical Research (SABOR) experiment are related to GEOS-Chem model chemical composition. The application for this procedure to link model chemical components to aerosol type is desirable for understanding aerosol evolution over time. The Mahalanobis distance (DM) statistic is used to cluster model groupings of five chemical components (organic carbon, black carbon, sea salt, dust and sulfate) in a way analogous to the methods used by Burton et al. [2012] and Russell et al. [2014]. First, model-to-measurement evaluation is performed by collocating vertically resolved aerosol extinction from SABOR High Spectral Resolution LiDAR (HSRL) to the GEOS-Chem nested high-resolution data. Comparisons of modeled-to-measured aerosol extinction are shown to be within 35% ± 14%. Second, the model chemical components are calculation into five variables to calculate the DM and cluster means and covariances for each HSRL-retrieved aerosol type. The layer variables from the model are aerosol optical depth (AOD) ratios of (i) sea salt and (ii) dust to total AOD, mass ratios of (iii) total carbon (i.e. sum of organic and black carbon) to the sum of total carbon and sulfate (iv) organic carbon to black carbon, and (v) the natural log of the aerosol-to-molecular extinction ratio. Third, the layer variables and at most five out of twenty SABOR flights are used to form the pre-specified clusters for calculating DM and to assign an aerosol type. After determining the pre-specified clusters, model aerosol types are produced for the entire vertically resolved GEOS-Chem nested domain over the United States and the model chemical component distributions relating to each type are recorded. Resulting aerosol types are Dust/Dusty Mix, Maritime, Smoke, Urban and Fresh Smoke (separated into `dark' and `light' by a threshold of the organic to black carbon ratio). Model-calculated DM not belonging to a specific type (i.e. not meeting a threshold probability) is termed an outlier and those DM values that can belong to multiple types (i.e. showing weak probability of belonging to a specific cluster) are termed as Overlap. MODIS active fires are overlaid on the model domain to qualitatively evaluate the model-predicted Smoke aerosol types.

Auditory sensitivity of seals and sea lions in complex listening scenarios.

PubMed

Cunningham, Kane A; Southall, Brandon L; Reichmuth, Colleen

2014-12-01

Standard audiometric data, such as audiograms and critical ratios, are often used to inform marine mammal noise-exposure criteria. However, these measurements are obtained using simple, artificial stimuli-i.e., pure tones and flat-spectrum noise-while natural sounds typically have more complex structure. In this study, detection thresholds for complex signals were measured in (I) quiet and (II) masked conditions for one California sea lion (Zalophus californianus) and one harbor seal (Phoca vitulina). In Experiment I, detection thresholds in quiet conditions were obtained for complex signals designed to isolate three common features of natural sounds: Frequency modulation, amplitude modulation, and harmonic structure. In Experiment II, detection thresholds were obtained for the same complex signals embedded in two types of masking noise: Synthetic flat-spectrum noise and recorded shipping noise. To evaluate how accurately standard hearing data predict detection of complex sounds, the results of Experiments I and II were compared to predictions based on subject audiograms and critical ratios combined with a basic hearing model. Both subjects exhibited greater-than-predicted sensitivity to harmonic signals in quiet and masked conditions, as well as to frequency-modulated signals in masked conditions. These differences indicate that the complex features of naturally occurring sounds enhance detectability relative to simple stimuli.

Percolation, phase separation, and gelation in fluids and mixtures of spheres and rods

NASA Astrophysics Data System (ADS)

Jadrich, Ryan; Schweizer, Kenneth S.

2011-12-01

The relationship between kinetic arrest, connectivity percolation, structure and phase separation in protein, nanoparticle, and colloidal suspensions is a rich and complex problem. Using a combination of integral equation theory, connectivity percolation methods, naïve mode coupling theory, and the activated dynamics nonlinear Langevin equation approach, we study this problem for isotropic one-component fluids of spheres and variable aspect ratio rigid rods, and also percolation in rod-sphere mixtures. The key control parameters are interparticle attraction strength and its (short) spatial range, total packing fraction, and mixture composition. For spherical particles, formation of a homogeneous one-phase kinetically stable and percolated physical gel is predicted to be possible, but depends on non-universal factors. On the other hand, the dynamic crossover to activated dynamics and physical bond formation, which signals discrete cluster formation below the percolation threshold, almost always occurs in the one phase region. Rods more easily gel in the homogeneous isotropic regime, but whether a percolation or kinetic arrest boundary is reached first upon increasing interparticle attraction depends sensitively on packing fraction, rod aspect ratio and attraction range. Overall, the connectivity percolation threshold is much more sensitive to attraction range than either the kinetic arrest or phase separation boundaries. Our results appear to be qualitatively consistent with recent experiments on polymer-colloid depletion systems and brush mediated attractive nanoparticle suspensions.

Female turtles from hot nests: is it duration of incubation or proportion of development at high temperatures that matters?

PubMed

Georges, Arthur

1989-11-01

Mean daily temperature in natural nests of freshwater turtles with temperature-dependent sex determination is known to be a poor predictor of hatchling sex ratios when nest temperatures fluctuate. To account for this, a model was developed on the assumption that females will emerge from eggs when more than half of embryonic development occurs above the threshold temperature for sex determination rather than from eggs that spend more than half their time above the threshold. The model is consistent with previously published data and in particular explains the phenomenon whereby the mean temperature that best distinguishes between male and female nests decreases with increasing variability in nest temperature. The model, if verified by controlled experiments, has important implications for our understanding of temperature-dependent sex determination in natural nests. Both mean nest temperature and "hours spent above the threshold" will be poor predictors of hatchling sex ratios. Studies designed to investigate latitudinal trends and inter-specific differences in the threshold temperature will need to consider latitudinal and inter-specific variation in the magnitude of diel fluctuations in nest temperature, and variation in factors influencing the magnitude of those fluctuations, such as nest depth. Furthermore, any factor that modifies the relationship between developmental rate and temperature can be expected to influence hatchling sex ratios in natural nests, especially when nest temperatures are close to the threshold.

Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data

DOE PAGES

Zhu, Lei; Gonder, Jeffrey; Lin, Lei

2017-08-16

With the development of and advances in smartphones and global positioning system (GPS) devices, travelers’ long-term travel behaviors are not impossible to obtain. This study investigates the pattern of individual travel behavior and its correlation with social-demographic features. For different social-demographic groups (e.g., full-time employees and students), the individual travel behavior may have specific temporal-spatial-mobile constraints. The study first extracts the home-based tours, including Home-to-Home and Home-to-Non-Home, from long-term raw GPS data. The travel behavior pattern is then delineated by home-based tour features, such as departure time, destination location entropy, travel time, and driving time ratio. The travel behavior variabilitymore » describes the variances of travelers’ activity behavior features for an extended period. After that, the variability pattern of an individual’s travel behavior is used for estimating the individual’s social-demographic information, such as social-demographic role, by a supervised learning approach, support vector machine. In this study, a long-term (18-month) recorded GPS data set from Puget Sound Regional Council is used. The experiment’s result is very promising. In conclusion, the sensitivity analysis shows that as the number of tours thresholds increases, the variability of most travel behavior features converges, while the prediction performance may not change for the fixed test data.« less

Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Gonder, Jeffrey; Lin, Lei

With the development of and advances in smartphones and global positioning system (GPS) devices, travelers’ long-term travel behaviors are not impossible to obtain. This study investigates the pattern of individual travel behavior and its correlation with social-demographic features. For different social-demographic groups (e.g., full-time employees and students), the individual travel behavior may have specific temporal-spatial-mobile constraints. The study first extracts the home-based tours, including Home-to-Home and Home-to-Non-Home, from long-term raw GPS data. The travel behavior pattern is then delineated by home-based tour features, such as departure time, destination location entropy, travel time, and driving time ratio. The travel behavior variabilitymore » describes the variances of travelers’ activity behavior features for an extended period. After that, the variability pattern of an individual’s travel behavior is used for estimating the individual’s social-demographic information, such as social-demographic role, by a supervised learning approach, support vector machine. In this study, a long-term (18-month) recorded GPS data set from Puget Sound Regional Council is used. The experiment’s result is very promising. In conclusion, the sensitivity analysis shows that as the number of tours thresholds increases, the variability of most travel behavior features converges, while the prediction performance may not change for the fixed test data.« less

Relations that affect the probability and prediction of nitrate concentration in private wells in the glacial aquifer system in the United States

USGS Publications Warehouse

Warner, Kelly L.; Arnold, Terri L.

2010-01-01

Nitrate in private wells in the glacial aquifer system is a concern for an estimated 17 million people using private wells because of the proximity of many private wells to nitrogen sources. Yet, less than 5 percent of private wells sampled in this study contained nitrate in concentrations that exceeded the U.S. Environmental Protection Agency (USEPA) Maximum Contaminant Level (MCL) of 10 mg/L (milligrams per liter) as N (nitrogen). However, this small group with nitrate concentrations above the USEPA MCL includes some of the highest nitrate concentrations detected in groundwater from private wells (77 mg/L). Median nitrate concentration measured in groundwater from private wells in the glacial aquifer system (0.11 mg/L as N) is lower than that in water from other unconsolidated aquifers and is not strongly related to surface sources of nitrate. Background concentration of nitrate is less than 1 mg/L as N. Although overall nitrate concentration in private wells was low relative to the MCL, concentrations were highly variable over short distances and at various depths below land surface. Groundwater from wells in the glacial aquifer system at all depths was a mixture of old and young water. Oxidation and reduction potential changes with depth and groundwater age were important influences on nitrate concentrations in private wells. A series of 10 logistic regression models was developed to estimate the probability of nitrate concentration above various thresholds. The threshold concentration (1 to 10 mg/L) affected the number of variables in the model. Fewer explanatory variables are needed to predict nitrate at higher threshold concentrations. The variables that were identified as significant predictors for nitrate concentration above 4 mg/L as N included well characteristics such as open-interval diameter, open-interval length, and depth to top of open interval. Environmental variables in the models were mean percent silt in soil, soil type, and mean depth to saturated soil. The 10-year mean (1992-2001) application rate of nitrogen fertilizer applied to farms was included as the potential source variable. A linear regression model also was developed to predict mean nitrate concentrations in well networks. The model is based on network averages because nitrate concentrations are highly variable over short distances. Using values for each of the predictor variables averaged by network (network mean value) from the logistic regression models, the linear regression model developed in this study predicted the mean nitrate concentration in well networks with a 95 percent confidence in predictions.

Predicting reactivity threshold in children with anaphylaxis to peanut.

PubMed

Reier-Nilsen, T; Michelsen, M M; Lødrup Carlsen, K C; Carlsen, K-H; Mowinckel, P; Nygaard, U C; Namork, E; Borres, M P; Håland, G

2018-04-01

Peanut allergy necessitates dietary restrictions, preferably individualized by determining reactivity threshold through an oral food challenge (OFC). However, risk of systemic reactions often precludes OFC in children with severe peanut allergy. We aimed to determine whether clinical and/or immunological characteristics were associated with reactivity threshold in children with anaphylaxis to peanut and secondarily, to investigate whether these characteristics were associated with severity of the allergic reaction during OFC. A double-blinded placebo-controlled food challenge (DBPCFC) with peanut was performed in 96 5- to 15-year-old children with a history of severe allergic reactions to peanut and/or sensitization to peanut (skin prick test [SPT] ≥3 mm or specific immunoglobulin E [s-IgE] ≥0.35 kUA/L). Investigations preceding the DBPCFC included a structured interview, SPT, lung function measurements, serological immunology assessment (IgE, IgG and IgG 4 ), basophil activation test (BAT) and conjunctival allergen provocation test (CAPT). International standards were used to define anaphylaxis and grade the allergic reaction during OFC. During DBPCFC, all 96 children (median age 9.3, range 5.1-15.2) reacted with anaphylaxis (moderate objective symptoms from at least two organ systems). Basophil activation (CD63 + basophils ≥15%), peanut SPT and the ratio of peanut s-IgE/total IgE were significantly associated with reactivity threshold and lowest observed adverse events level (LOAEL) (all P < .04). Basophil activation best predicted very low threshold level (<3 mg of peanut protein), with an optimal cut-off of 75.8% giving a 93.5% negative predictive value. None of the characteristics were significantly associated with the severity of allergic reaction. In children with anaphylaxis to peanut, basophil activation, peanut SPT and the ratio of peanut s-IgE/total IgE were associated with reactivity threshold and LOAEL, but not with allergy reaction severity. © 2017 John Wiley & Sons Ltd.

Discussion about different cut-off values of conventional hamstring-to-quadriceps ratio used in hamstring injury prediction among professional male football players

PubMed Central

Michałowska, Martyna; Walczak, Tomasz; Owen, Adam; Grabski, Jakub Krzysztof; Pyda, Andrzej; Piontek, Tomasz; Kotwicki, Tomasz

2017-01-01

Objective To measure the sensitivity and specificity of differences cut-off values for isokinetic Hcon/Qcon ratio in order to improve the capacity to evaluate (retrospectively) the injury of hamstring muscles in professional soccer screened with knee isokinetic tests. Design Retrospective study. Methods Medical and biomechanical data of professional football players playing for the same team for at least one season between 2010 and 2016 were analysed. Hamstring strain injury cases and the reports generated via isokinetic testing were investigated. Isokinetic concentric(con) hamstring(H) and quadriceps(Q) absolute strength in addition with Hcon/Qcon ratio were examined for the injured versus uninjured limbs among injured players, and for the injured and non-injured players. 2 x 2 contingency table was used for comparing variables: predicted injured or predicted uninjured with actual injured or actual uninjured. Sensitivity, specificity, accuracy, positive and negative predictive values, and positive and negative likelihood ratio were calculated for three different cut-off values (0.47 vs. 0.6 vs. 0.658) to compare the discriminative power of an isokinetic test, whilst examining the key value of Hcon/Qcon ratio which may indicate the highest level of ability to predispose a player to injury. McNemar’s chi2 test with Yates’s correction was used to determine agreement between the tests. PQStat software was used for all statistical analysis, and an alpha level of p <0.05 was used for all statistical comparisons. Results 340 isokinetic test reports on both limbs of 66 professional soccer players were analysed. Eleven players suffered hamstring injuries during the analysed period. None of these players sustained recurrence of hamstring injury. One player sustained hamstring strain injury on both legs, thus the total number of injuries was 12. Application of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic test used as a tool for muscle injury detection. The use of 0.47 of Hcon/Qcon as a discriminate value resulted in significantly lower sensitivity when compared to 0.658 threshold (sensitivity of 16.7% vs. 91.7%, respectively; t = 6.125,p = 0.0133). Calculated values of specificity (when three different cut-off were applied) were also significantly different. Threshold of 0.6 of Hcon/Qcon resulted with significantly lower specificity compared to 0.47 value (specificity of 46.9% vs. 94.5%, respectively; t = 153.0,p<0.0001), and significantly higher specificity when compared to 0.658 (specificity of 46.9% vs. 24.1%, respectively; t = 229.0, p<0.0001). Conclusion The use of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic testing. The interpretation of usefulness of isokinetic test as a screening tool in a group of male professional football players to predict hamstring injury occurrence within the next 12 months might be therefore significantly biased due to the different threshold values of Hcon/Qcon. Using one “normative” value as a cut-off (e.g. 0.47 or 0.60, or 0.658) to quantify soccer players (or not) to the group with a higher risk of knee injury might result in biased outcomes due to the natural strength asymmetry that is observed within the group of soccer players. PMID:29216241

Discussion about different cut-off values of conventional hamstring-to-quadriceps ratio used in hamstring injury prediction among professional male football players.

PubMed

Grygorowicz, Monika; Michałowska, Martyna; Walczak, Tomasz; Owen, Adam; Grabski, Jakub Krzysztof; Pyda, Andrzej; Piontek, Tomasz; Kotwicki, Tomasz

2017-01-01

To measure the sensitivity and specificity of differences cut-off values for isokinetic Hcon/Qcon ratio in order to improve the capacity to evaluate (retrospectively) the injury of hamstring muscles in professional soccer screened with knee isokinetic tests. Retrospective study. Medical and biomechanical data of professional football players playing for the same team for at least one season between 2010 and 2016 were analysed. Hamstring strain injury cases and the reports generated via isokinetic testing were investigated. Isokinetic concentric(con) hamstring(H) and quadriceps(Q) absolute strength in addition with Hcon/Qcon ratio were examined for the injured versus uninjured limbs among injured players, and for the injured and non-injured players. 2 x 2 contingency table was used for comparing variables: predicted injured or predicted uninjured with actual injured or actual uninjured. Sensitivity, specificity, accuracy, positive and negative predictive values, and positive and negative likelihood ratio were calculated for three different cut-off values (0.47 vs. 0.6 vs. 0.658) to compare the discriminative power of an isokinetic test, whilst examining the key value of Hcon/Qcon ratio which may indicate the highest level of ability to predispose a player to injury. McNemar's chi2 test with Yates's correction was used to determine agreement between the tests. PQStat software was used for all statistical analysis, and an alpha level of p <0.05 was used for all statistical comparisons. 340 isokinetic test reports on both limbs of 66 professional soccer players were analysed. Eleven players suffered hamstring injuries during the analysed period. None of these players sustained recurrence of hamstring injury. One player sustained hamstring strain injury on both legs, thus the total number of injuries was 12. Application of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic test used as a tool for muscle injury detection. The use of 0.47 of Hcon/Qcon as a discriminate value resulted in significantly lower sensitivity when compared to 0.658 threshold (sensitivity of 16.7% vs. 91.7%, respectively; t = 6.125,p = 0.0133). Calculated values of specificity (when three different cut-off were applied) were also significantly different. Threshold of 0.6 of Hcon/Qcon resulted with significantly lower specificity compared to 0.47 value (specificity of 46.9% vs. 94.5%, respectively; t = 153.0,p<0.0001), and significantly higher specificity when compared to 0.658 (specificity of 46.9% vs. 24.1%, respectively; t = 229.0, p<0.0001). The use of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic testing. The interpretation of usefulness of isokinetic test as a screening tool in a group of male professional football players to predict hamstring injury occurrence within the next 12 months might be therefore significantly biased due to the different threshold values of Hcon/Qcon. Using one "normative" value as a cut-off (e.g. 0.47 or 0.60, or 0.658) to quantify soccer players (or not) to the group with a higher risk of knee injury might result in biased outcomes due to the natural strength asymmetry that is observed within the group of soccer players.

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.

Discharge variability and bedrock river incision on the Hawaiian island of Kaua'i

NASA Astrophysics Data System (ADS)

Huppert, K.; Deal, E.; Perron, J. T.; Ferrier, K.; Braun, J.

2017-12-01

Bedrock river incision occurs during floods that generate sufficient shear stress to strip riverbeds of sediment cover and erode underlying bedrock. Thresholds for incision can prevent erosion at low flows and slow down erosion at higher flows that do generate excess shear stress. Because discharge distributions typically display power-law tails, with non-negligible frequencies of floods much greater than the mean, models incorporating stochastic discharge and incision thresholds predict that discharge variability can sometimes have greater effects on long-term incision rates than mean discharge. This occurs when the commonly observed inverse scalings between mean discharge and discharge variability are weak or when incision thresholds are high. Because the effects of thresholds and discharge variability have only been documented in a few locations, their influence on long-term river incision rates remains uncertain. The Hawaiian island of Kaua'i provides an ideal natural laboratory to evaluate the effects of discharge variability and thresholds on bedrock river incision because it has one of Earth's steepest spatial gradients in mean annual rainfall and it also experiences dramatic spatial variations in rainfall and discharge variability, spanning a wide range of the conditions reported on Earth. Kaua'i otherwise has minimal variations in lithology, vertical motion, and other factors that can influence erosion. River incision rates averaged over 1.5 - 4.5 Myr timescales can be estimated along the lengths of Kauaian channels from the depths of river canyons and lava flow ages. We characterize rainfall and discharge variability on Kaua'i using records from an extensive network of rain and stream gauges spanning the past century. We use these characterizations to model long-term bedrock river incision along Kauaian channels with a threshold-dependent incision law, modulated by site-specific discharge-channel width scalings. Our comparisons between modeled and observed erosion rates suggest that variations in river incision rates on Kaua'i are dominated by variations in mean rainfall and discharge, rather than by differences in storminess across the island. We explore the implications of this result for the threshold dependence of river incision across Earth's varied climates.

Long-term follow-up after near-infrared spectroscopy coronary imaging: Insights from the lipid cORe plaque association with CLinical events (ORACLE-NIRS) registry.

PubMed

Danek, Barbara Anna; Karatasakis, Aris; Karacsonyi, Judit; Alame, Aya; Resendes, Erica; Kalsaria, Pratik; Nguyen-Trong, Phuong-Khanh J; Rangan, Bavana V; Roesle, Michele; Abdullah, Shuaib; Banerjee, Subhash; Brilakis, Emmanouil S

Coronary lipid core plaque may be associated with the incidence of subsequent cardiovascular events. We analyzed outcomes of 239 patients who underwent near-infrared spectroscopy (NIRS) coronary imaging between 2009-2011. Multivariable Cox regression was used to identify variables independently associated with the incidence of major adverse cardiovascular events (MACE; cardiac mortality, acute coronary syndromes (ACS), stroke, and unplanned revascularization) during follow-up. Mean patient age was 64±9years, 99% were men, and 50% were diabetic, presenting with stable coronary artery disease (61%) or an acute coronary syndrome (ACS, 39%). Target vessel pre-stenting median lipid core burden index (LCBI) was 88 [interquartile range, IQR 50-130]. Median LCBI in non-target vessels was 57 [IQR 26-94]. Median follow-up was 5.3years. The 5-year MACE rate was 37.5% (cardiac mortality was 15.0%). On multivariable analysis the following variables were associated with MACE: diabetes mellitus, prior percutaneous coronary intervention performed at index angiography, and non-target vessel LCBI. Non-target vessel LCBI of 77 was determined using receiver-operating characteristic curve analysis to be a threshold for prediction of MACE in our cohort. The adjusted hazard ratio (HR) for non-target vessel LCBI ≥77 was 14.05 (95% confidence interval (CI) 2.47-133.51, p=0.002). The 5-year cumulative incidence of events in the above-threshold group was 58.0% vs. 13.1% in the below-threshold group. During long-term follow-up of patients who underwent NIRS imaging, high LCBI in a non-PCI target vessel was associated with increased incidence of MACE. Published by Elsevier Inc.

Considering the filler network as a third phase in polymer/CNT nanocomposites to predict the tensile modulus using Hashin-Hansen model

NASA Astrophysics Data System (ADS)

Kim, Sanghoon; Jamalzadeh, Navid; Zare, Yasser; Hui, David; Rhee, Kyong Yop

2018-07-01

In this paper, a conventional Hashin-Hansen model is developed to analyze the tensile modulus of polymer/CNT nanocomposites above the percolation threshold. This model for composites containing dispersed particles utilizes the aspect ratio of the nanofiller (α), the number of nanotubes per unit area (N), the percolation threshold (φp) and the modulus of the filler network (EN), assuming that the filler network constitutes a third phase in the nanocomposites. The experimental results and the predictions agree well, verifying the proposed relations between the modulus and the other parameters in the Hashin-Hansen model. Moreover, large values of "α", "N" and "EN" result in an improved modulus of the polymer/CNT nanocomposites, while a low percolation threshold results in a high modulus.

Wide brick tunnel randomization - an unequal allocation procedure that limits the imbalance in treatment totals.

PubMed

Kuznetsova, Olga M; Tymofyeyev, Yevgen

2014-04-30

In open-label studies, partial predictability of permuted block randomization provides potential for selection bias. To lessen the selection bias in two-arm studies with equal allocation, a number of allocation procedures that limit the imbalance in treatment totals at a pre-specified level but do not require the exact balance at the ends of the blocks were developed. In studies with unequal allocation, however, the task of designing a randomization procedure that sets a pre-specified limit on imbalance in group totals is not resolved. Existing allocation procedures either do not preserve the allocation ratio at every allocation or do not include all allocation sequences that comply with the pre-specified imbalance threshold. Kuznetsova and Tymofyeyev described the brick tunnel randomization for studies with unequal allocation that preserves the allocation ratio at every step and, in the two-arm case, includes all sequences that satisfy the smallest possible imbalance threshold. This article introduces wide brick tunnel randomization for studies with unequal allocation that allows all allocation sequences with imbalance not exceeding any pre-specified threshold while preserving the allocation ratio at every step. In open-label studies, allowing a larger imbalance in treatment totals lowers selection bias because of the predictability of treatment assignments. The applications of the technique in two-arm and multi-arm open-label studies with unequal allocation are described. Copyright © 2013 John Wiley & Sons, Ltd.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

PubMed

Reddy, Anupama; Growney, Joseph D; Wilson, Nick S; Emery, Caroline M; Johnson, Jennifer A; Ward, Rebecca; Monaco, Kelli A; Korn, Joshua; Monahan, John E; Stump, Mark D; Mapa, Felipa A; Wilson, Christopher J; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J; Myer, Vic E; Ettenberg, Seth A; Schlegel, Robert; Sellers, William R; Huet, Heather A; Lehár, Joseph

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages

PubMed Central

Reddy, Anupama; Growney, Joseph D.; Wilson, Nick S.; Emery, Caroline M.; Johnson, Jennifer A.; Ward, Rebecca; Monaco, Kelli A.; Korn, Joshua; Monahan, John E.; Stump, Mark D.; Mapa, Felipa A.; Wilson, Christopher J.; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J.; Myer, Vic E.; Ettenberg, Seth A.; Schlegel, Robert; Sellers, William R.

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response. PMID:26378449

Predicting pain relief: Use of pre-surgical trigeminal nerve diffusion metrics in trigeminal neuralgia.

PubMed

Hung, Peter S-P; Chen, David Q; Davis, Karen D; Zhong, Jidan; Hodaie, Mojgan

2017-01-01

Trigeminal neuralgia (TN) is a chronic neuropathic facial pain disorder that commonly responds to surgery. A proportion of patients, however, do not benefit and suffer ongoing pain. There are currently no imaging tools that permit the prediction of treatment response. To address this paucity, we used diffusion tensor imaging (DTI) to determine whether pre-surgical trigeminal nerve microstructural diffusivities can prognosticate response to TN treatment. In 31 TN patients and 16 healthy controls, multi-tensor tractography was used to extract DTI-derived metrics-axial (AD), radial (RD), mean diffusivity (MD), and fractional anisotropy (FA)-from the cisternal segment, root entry zone and pontine segment of trigeminal nerves for false discovery rate-corrected Student's t -tests. Ipsilateral diffusivities were bootstrap resampled to visualize group-level diffusivity thresholds of long-term response. To obtain an individual-level statistical classifier of surgical response, we conducted discriminant function analysis (DFA) with the type of surgery chosen alongside ipsilateral measurements and ipsilateral/contralateral ratios of AD and RD from all regions of interest as prediction variables. Abnormal diffusivity in the trigeminal pontine fibers, demonstrated by increased AD, highlighted non-responders (n = 14) compared to controls. Bootstrap resampling revealed three ipsilateral diffusivity thresholds of response-pontine AD, MD, cisternal FA-separating 85% of non-responders from responders. DFA produced an 83.9% (71.0% using leave-one-out-cross-validation) accurate prognosticator of response that successfully identified 12/14 non-responders. Our study demonstrates that pre-surgical DTI metrics can serve as a highly predictive, individualized tool to prognosticate surgical response. We further highlight abnormal pontine segment diffusivities as key features of treatment non-response and confirm the axiom that central pain does not commonly benefit from peripheral treatments.

EMG biofeedback: the effects of CRF, FR, VR, FI, and VI schedules of reinforcement on the acquisition and extinction of increases in forearm muscle tension.

PubMed

Cohen, S L; Richardson, J; Klebez, J; Febbo, S; Tucker, D

2001-09-01

Biofeedback was used to increase forearm-muscle tension. Feedback was delivered under continuous reinforcement (CRF), variable interval (VI), fixed interval (FI), variable ratio (VR), and fixed ratio (FR) schedules of reinforcement when college students increased their muscle tension (electromyograph, EMG) above a high threshold. There were three daily sessions of feedback, and Session 3 was immediately followed by a session without feedback (extinction). The CRF schedule resulted in the highest EMG, closely followed by the FR and VR schedules, and the lowest EMG scores were produced by the FI and VI schedules. Similarly, the CRF schedule resulted in the greatest amount of time-above-threshold and the VI and FI schedules produced the lowest time-above-threshold. The highest response rates were generated by the FR schedule, followed by the VR schedule. The CRF schedule produced relatively low response rates, comparable to the rates under the VI and FI schedules. Some of the data are consistent with the partial-reinforcement-extinction effect. The present data suggest that different schedules of feedback should be considered in muscle-strengthening-contexts such as during the rehabilitation of muscles following brain damage or peripheral nervous-system injury.

Compensation for red-green contrast loss in anomalous trichromats

PubMed Central

Boehm, A. E.; MacLeod, D. I. A.; Bosten, J. M.

2014-01-01

For anomalous trichromats, threshold contrasts for color differences captured by the L and M cones and their anomalous analogs are much higher than for normal trichromats. The greater spectral overlap of the cone sensitivities reduces chromatic contrast both at and above threshold. But above threshold, adaptively nonlinear processing might compensate for the chromatically impoverished photoreceptor inputs. Ratios of sensitivity for threshold variations and for color appearance along the two cardinal axes of MacLeod-Boynton chromaticity space were calculated for three groups: normals (N = 15), deuteranomals (N = 9), and protanomals (N = 5). Using a four-alternative forced choice (4AFC) task, threshold sensitivity was measured in four color-directions along the two cardinal axes. For the same participants, we reconstructed perceptual color spaces for the positions of 25 hues using multidimensional scaling (MDS). From the reconstructed color spaces we extracted “color difference ratios,” defined as ratios for the size of perceived color differences along the L/(L + M) axis relative to those along the S/(L + M) axis, analogous to “sensitivity ratios” extracted from the 4AFC task. In the 4AFC task, sensitivity ratios were 38% of normal for deuteranomals and 19% of normal for protanomals. Yet, in the MDS results, color difference ratios were 86% of normal for deuteranomals and 67% of normal for protanomals. Thus, the contraction along the L/(L + M) axis shown in the perceptual color spaces of anomalous trichromats is far smaller than predicted by their reduced sensitivity, suggesting that an adaptive adjustment of postreceptoral gain may magnify the cone signals of anomalous trichromats to exploit the range of available postreceptoral neural signals. PMID:25413625

How to determine an optimal threshold to classify real-time crash-prone traffic conditions?

PubMed

Yang, Kui; Yu, Rongjie; Wang, Xuesong; Quddus, Mohammed; Xue, Lifang

2018-08-01

One of the proactive approaches in reducing traffic crashes is to identify hazardous traffic conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold selection is one of the essential steps of real-time crash prediction. And it provides the cut-off point for the posterior probability which is used to separate potential crash warnings against normal traffic conditions, after the outcome of the probability of a crash occurring given a specific traffic condition on the basis of crash risk evaluation models. There is however a dearth of research that focuses on how to effectively determine an optimal threshold. And only when discussing the predictive performance of the models, a few studies utilized subjective methods to choose the threshold. The subjective methods cannot automatically identify the optimal thresholds in different traffic and weather conditions in real application. Thus, a theoretical method to select the threshold value is necessary for the sake of avoiding subjective judgments. The purpose of this study is to provide a theoretical method for automatically identifying the optimal threshold. Considering the random effects of variable factors across all roadway segments, the mixed logit model was utilized to develop the crash risk evaluation model and further evaluate the crash risk. Cross-entropy, between-class variance and other theories were employed and investigated to empirically identify the optimal threshold. And K-fold cross-validation was used to validate the performance of proposed threshold selection methods with the help of several evaluation criteria. The results indicate that (i) the mixed logit model can obtain a good performance; (ii) the classification performance of the threshold selected by the minimum cross-entropy method outperforms the other methods according to the criteria. This method can be well-behaved to automatically identify thresholds in crash prediction, by minimizing the cross entropy between the original dataset with continuous probability of a crash occurring and the binarized dataset after using the thresholds to separate potential crash warnings against normal traffic conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development and evaluation of a regression-based model to predict cesium-137 concentration ratios for saltwater fish.

PubMed

Pinder, John E; Rowan, David J; Smith, Jim T

2016-02-01

Data from published studies and World Wide Web sources were combined to develop a regression model to predict (137)Cs concentration ratios for saltwater fish. Predictions were developed from 1) numeric trophic levels computed primarily from random resampling of known food items and 2) K concentrations in the saltwater for 65 samplings from 41 different species from both the Atlantic and Pacific Oceans. A number of different models were initially developed and evaluated for accuracy which was assessed as the ratios of independently measured concentration ratios to those predicted by the model. In contrast to freshwater systems, were K concentrations are highly variable and are an important factor in affecting fish concentration ratios, the less variable K concentrations in saltwater were relatively unimportant in affecting concentration ratios. As a result, the simplest model, which used only trophic level as a predictor, had comparable accuracies to more complex models that also included K concentrations. A test of model accuracy involving comparisons of 56 published concentration ratios from 51 species of marine fish to those predicted by the model indicated that 52 of the predicted concentration ratios were within a factor of 2 of the observed concentration ratios. Copyright © 2015 Elsevier Ltd. All rights reserved.

Remodeling characteristics and collagen distribution in synthetic mesh materials explanted from human subjects after abdominal wall reconstruction: an analysis of remodeling characteristics by patient risk factors and surgical site classifications

PubMed Central

Cavallo, Jaime A.; Roma, Andres A.; Jasielec, Mateusz S.; Ousley, Jenny; Creamer, Jennifer; Pichert, Matthew D.; Baalman, Sara; Frisella, Margaret M.; Matthews, Brent D.

2014-01-01

Background The purpose of this study was to evaluate the associations between patient characteristics or surgical site classifications and the histologic remodeling scores of synthetic meshes biopsied from their abdominal wall repair sites in the first attempt to generate a multivariable risk prediction model of non-constructive remodeling. Methods Biopsies of the synthetic meshes were obtained from the abdominal wall repair sites of 51 patients during a subsequent abdominal re-exploration. Biopsies were stained with hematoxylin and eosin, and evaluated according to a semi-quantitative scoring system for remodeling characteristics (cell infiltration, cell types, extracellular matrix deposition, inflammation, fibrous encapsulation, and neovascularization) and a mean composite score (CR). Biopsies were also stained with Sirius Red and Fast Green, and analyzed to determine the collagen I:III ratio. Based on univariate analyses between subject clinical characteristics or surgical site classification and the histologic remodeling scores, cohort variables were selected for multivariable regression models using a threshold p value of ≤0.200. Results The model selection process for the extracellular matrix score yielded two variables: subject age at time of mesh implantation, and mesh classification (c-statistic = 0.842). For CR score, the model selection process yielded two variables: subject age at time of mesh implantation and mesh classification (r2 = 0.464). The model selection process for the collagen III area yielded a model with two variables: subject body mass index at time of mesh explantation and pack-year history (r2 = 0.244). Conclusion Host characteristics and surgical site assessments may predict degree of remodeling for synthetic meshes used to reinforce abdominal wall repair sites. These preliminary results constitute the first steps in generating a risk prediction model that predicts the patients and clinical circumstances for which non-constructive remodeling of an abdominal wall repair site with synthetic mesh reinforcement is most likely to occur. PMID:24442681

A ratiometric threshold for determining presence of cancer during fluorescence-guided surgery.

PubMed

Warram, Jason M; de Boer, Esther; Moore, Lindsay S; Schmalbach, Cecelia E; Withrow, Kirk P; Carroll, William R; Richman, Joshua S; Morlandt, Anthony B; Brandwein-Gensler, Margaret; Rosenthal, Eben L

2015-07-01

Fluorescence-guided imaging to assist in identification of malignant margins has the potential to dramatically improve oncologic surgery. However, a standardized method for quantitative assessment of disease-specific fluorescence has not been investigated. Introduced here is a ratiometric threshold derived from mean fluorescent tissue intensity that can be used to semi-quantitatively delineate tumor from normal tissue. Open-field and a closed-field imaging devices were used to quantify fluorescence in punch biopsy tissues sampled from primary tumors collected during a phase 1 trial evaluating the safety of cetuximab-IRDye800 in patients (n = 11) undergoing surgical intervention for head and neck cancer. Fluorescence ratios were calculated using mean fluorescence intensity (MFI) from punch biopsy normalized by MFI of patient-matched tissues. Ratios were compared to pathological assessment and a ratiometric threshold was established to predict presence of cancer. During open-field imaging using an intraoperative device, the threshold for muscle normalized tumor fluorescence was found to be 2.7, which produced a sensitivity of 90.5% and specificity of 78.6% for delineating disease tissue. The skin-normalized threshold generated greater sensitivity (92.9%) and specificity (81.0%). Successful implementation of a semi-quantitative threshold can provide a scientific methodology for delineating disease from normal tissue during fluorescence-guided resection of cancer. © 2015 Wiley Periodicals, Inc.

Spectrotemporal Modulation Sensitivity as a Predictor of Speech Intelligibility for Hearing-Impaired Listeners

PubMed Central

Bernstein, Joshua G.W.; Mehraei, Golbarg; Shamma, Shihab; Gallun, Frederick J.; Theodoroff, Sarah M.; Leek, Marjorie R.

2014-01-01

Background A model that can accurately predict speech intelligibility for a given hearing-impaired (HI) listener would be an important tool for hearing-aid fitting or hearing-aid algorithm development. Existing speech-intelligibility models do not incorporate variability in suprathreshold deficits that are not well predicted by classical audiometric measures. One possible approach to the incorporation of such deficits is to base intelligibility predictions on sensitivity to simultaneously spectrally and temporally modulated signals. Purpose The likelihood of success of this approach was evaluated by comparing estimates of spectrotemporal modulation (STM) sensitivity to speech intelligibility and to psychoacoustic estimates of frequency selectivity and temporal fine-structure (TFS) sensitivity across a group of HI listeners. Research Design The minimum modulation depth required to detect STM applied to an 86 dB SPL four-octave noise carrier was measured for combinations of temporal modulation rate (4, 12, or 32 Hz) and spectral modulation density (0.5, 1, 2, or 4 cycles/octave). STM sensitivity estimates for individual HI listeners were compared to estimates of frequency selectivity (measured using the notched-noise method at 500, 1000measured using the notched-noise method at 500, 2000, and 4000 Hz), TFS processing ability (2 Hz frequency-modulation detection thresholds for 500, 10002 Hz frequency-modulation detection thresholds for 500, 2000, and 4000 Hz carriers) and sentence intelligibility in noise (at a 0 dB signal-to-noise ratio) that were measured for the same listeners in a separate study. Study Sample Eight normal-hearing (NH) listeners and 12 listeners with a diagnosis of bilateral sensorineural hearing loss participated. Data Collection and Analysis STM sensitivity was compared between NH and HI listener groups using a repeated-measures analysis of variance. A stepwise regression analysis compared STM sensitivity for individual HI listeners to audiometric thresholds, age, and measures of frequency selectivity and TFS processing ability. A second stepwise regression analysis compared speech intelligibility to STM sensitivity and the audiogram-based Speech Intelligibility Index. Results STM detection thresholds were elevated for the HI listeners, but only for low rates and high densities. STM sensitivity for individual HI listeners was well predicted by a combination of estimates of frequency selectivity at 4000 Hz and TFS sensitivity at 500 Hz but was unrelated to audiometric thresholds. STM sensitivity accounted for an additional 40% of the variance in speech intelligibility beyond the 40% accounted for by the audibility-based Speech Intelligibility Index. Conclusions Impaired STM sensitivity likely results from a combination of a reduced ability to resolve spectral peaks and a reduced ability to use TFS information to follow spectral-peak movements. Combining STM sensitivity estimates with audiometric threshold measures for individual HI listeners provided a more accurate prediction of speech intelligibility than audiometric measures alone. These results suggest a significant likelihood of success for an STM-based model of speech intelligibility for HI listeners. PMID:23636210

Deriving the species richness distribution of Geotrupinae (Coleoptera: Scarabaeoidea) in Mexico from the overlap of individual model predictions.

PubMed

Trotta-Moreu, Nuria; Lobo, Jorge M

2010-02-01

Predictions from individual distribution models for Mexican Geotrupinae species were overlaid to obtain a total species richness map for this group. A database (GEOMEX) that compiles available information from the literature and from several entomological collections was used. A Maximum Entropy method (MaxEnt) was applied to estimate the distribution of each species, taking into account 19 climatic variables as predictors. For each species, suitability values ranging from 0 to 100 were calculated for each grid cell on the map, and 21 different thresholds were used to convert these continuous suitability values into binary ones (presence-absence). By summing all of the individual binary maps, we generated a species richness prediction for each of the considered thresholds. The number of species and faunal composition thus predicted for each Mexican state were subsequently compared with those observed in a preselected set of well-surveyed states. Our results indicate that the sum of individual predictions tends to overestimate species richness but that the selection of an appropriate threshold can reduce this bias. Even under the most optimistic prediction threshold, the mean species richness error is 61% of the observed species richness, with commission errors being significantly more common than omission errors (71 +/- 29 versus 18 +/- 10%). The estimated distribution of Geotrupinae species richness in Mexico in discussed, although our conclusions are preliminary and contingent on the scarce and probably biased available data.

Symmetry breaking, phase separation and anomalous fluctuations in driven granular gas

NASA Astrophysics Data System (ADS)

Meerson, Baruch; Pöschel, Thorsten; Sasorov, Pavel V.; Schwager, Thomas

2003-03-01

What is the role of noise, caused by the discrete nature of particles, in granular dynamics? We address this question by considering a simple driven granular system: an ensemble of nearly elastically colliding hard spheres in a rectangular box, driven by a rapidly vibrating side wall at zero gravity. The elementary state of this system is a strip of enhanced particle density away from the driving wall. Granular hydrodynamics (GHD) predicts a symmetry breaking instability of this state, when the aspect ratio of the confining box exceeds a threshold value, while the average density of the gas is within a ``spinodal interval". At large aspect ratios this instability leads to phase separation similar to that in van der Waals gas. In the present work (see cond-mat/0208286) we focus on the system behavior around the threshold of the symmetry-breaking instability. We put GHD into a quantitative test by performing extensive event-driven molecular dynamic simulations in 2D. Please watch the movies of the simulations at http://summa.physik.hu-berlin.de/ kies/HD/. We found that the supercritical bifurcation curve, predicted by GHD, agrees with the simulations well below and well above the instability threshold. In a wide region of aspect ratios around the threshold the system is dominated by fluctuations. We checked that the fluctuation strength goes down when the number of particles increases. However, fluctuations remain strong (and the critical region wide) even for as many as 4 ot 10^4 particles. We conclude by suggesting that fluctuations may put a severe limitation on the validity of continuum theories of granular flow in systems with a moderately large number of particles.

N-terminal pro-B-type Natriuretic Peptides' Prognostic Utility Is Overestimated in Meta-analyses Using Study-specific Optimal Diagnostic Thresholds.

PubMed

Potgieter, Danielle; Simmers, Dale; Ryan, Lisa; Biccard, Bruce M; Lurati-Buse, Giovanna A; Cardinale, Daniela M; Chong, Carol P W; Cnotliwy, Miloslaw; Farzi, Sylvia I; Jankovic, Radmilo J; Lim, Wen Kwang; Mahla, Elisabeth; Manikandan, Ramaswamy; Oscarsson, Anna; Phy, Michael P; Rajagopalan, Sriram; Van Gaal, William J; Waliszek, Marek; Rodseth, Reitze N

2015-08-01

N-terminal fragment B-type natriuretic peptide (NT-proBNP) prognostic utility is commonly determined post hoc by identifying a single optimal discrimination threshold tailored to the individual study population. The authors aimed to determine how using these study-specific post hoc thresholds impacts meta-analysis results. The authors conducted a systematic review of studies reporting the ability of preoperative NT-proBNP measurements to predict the composite outcome of all-cause mortality and nonfatal myocardial infarction at 30 days after noncardiac surgery. Individual patient-level data NT-proBNP thresholds were determined using two different methodologies. First, a single combined NT-proBNP threshold was determined for the entire cohort of patients, and a meta-analysis conducted using this single threshold. Second, study-specific thresholds were determined for each individual study, with meta-analysis being conducted using these study-specific thresholds. The authors obtained individual patient data from 14 studies (n = 2,196). Using a single NT-proBNP cohort threshold, the odds ratio (OR) associated with an increased NT-proBNP measurement was 3.43 (95% CI, 2.08 to 5.64). Using individual study-specific thresholds, the OR associated with an increased NT-proBNP measurement was 6.45 (95% CI, 3.98 to 10.46). In smaller studies (<100 patients) a single cohort threshold was associated with an OR of 5.4 (95% CI, 2.27 to 12.84) as compared with an OR of 14.38 (95% CI, 6.08 to 34.01) for study-specific thresholds. Post hoc identification of study-specific prognostic biomarker thresholds artificially maximizes biomarker predictive power, resulting in an amplification or overestimation during meta-analysis of these results. This effect is accentuated in small studies.

Chemical characterization of the acid alteration of diesel fuel: Non-targeted analysis by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry with tile-based Fisher ratio and combinatorial threshold determination

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parsons, Brendon A.; Pinkerton, David K.; Wright, Bob W.

The illicit chemical alteration of petroleum fuels is of scientific interest, particularly to regulatory agencies which set fuel specifications, or excises based on those specifications. One type of alteration is the reaction of diesel fuel with concentrated sulfuric acid. Such reactions are known to subtly alter the chemical composition of the fuel, particularly the aromatic species native to the fuel. Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC–TOFMS) is ideally suited for the analysis of diesel fuel, but may provide the analyst with an overwhelming amount of data, particularly in sample-class comparison experiments comprised of manymore » samples. The tile-based Fisher-ratio (F-ratio) method reduces the abundance of data in a GC × GC–TOFMS experiment to only the peaks which significantly distinguish the unaltered and acid altered sample classes. Three samples of diesel fuel from different filling stations were each altered to discover chemical features, i.e., analyte peaks, which were consistently changed by the acid reaction. Using different fuels prioritizes the discovery of features which are likely to be robust to the variation present between fuel samples and which will consequently be useful in determining whether an unknown sample has been acid altered. The subsequent analysis confirmed that aromatic species are removed by the acid alteration, with the degree of removal consistent with predicted reactivity toward electrophilic aromatic sulfonation. Additionally, we observed that alkenes and alkynes were also removed from the fuel, and that sulfur dioxide or compounds that degrade to sulfur dioxide are generated by the acid alteration. In addition to applying the previously reported tile-based F-ratio method, this report also expands null distribution analysis to algorithmically determine an F-ratio threshold to confidently select only the features which are sufficiently class-distinguishing. When applied to the acid alteration of diesel fuel, the suggested per-hit F-ratio threshold was 12.4, which is predicted to maintain the false discovery rate (FDR) below 0.1%. Using this F-ratio threshold, 107 of the 3362 preliminary hits were deemed significantly changing due to the acid alteration, with the number of false positives estimated to be about 3.« less

Large signal-to-noise ratio quantification in MLE for ARARMAX models

NASA Astrophysics Data System (ADS)

Zou, Yiqun; Tang, Xiafei

2014-06-01

It has been shown that closed-loop linear system identification by indirect method can be generally transferred to open-loop ARARMAX (AutoRegressive AutoRegressive Moving Average with eXogenous input) estimation. For such models, the gradient-related optimisation with large enough signal-to-noise ratio (SNR) can avoid the potential local convergence in maximum likelihood estimation. To ease the application of this condition, the threshold SNR needs to be quantified. In this paper, we build the amplitude coefficient which is an equivalence to the SNR and prove the finiteness of the threshold amplitude coefficient within the stability region. The quantification of threshold is achieved by the minimisation of an elaborately designed multi-variable cost function which unifies all the restrictions on the amplitude coefficient. The corresponding algorithm based on two sets of physically realisable system input-output data details the minimisation and also points out how to use the gradient-related method to estimate ARARMAX parameters when local minimum is present as the SNR is small. Then, the algorithm is tested on a theoretical AutoRegressive Moving Average with eXogenous input model for the derivation of the threshold and a gas turbine engine real system for model identification, respectively. Finally, the graphical validation of threshold on a two-dimensional plot is discussed.

Threshold models for genome-enabled prediction of ordinal categorical traits in plant breeding.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo; Eskridge, Kent; Crossa, José

2014-12-23

Categorical scores for disease susceptibility or resistance often are recorded in plant breeding. The aim of this study was to introduce genomic models for analyzing ordinal characters and to assess the predictive ability of genomic predictions for ordered categorical phenotypes using a threshold model counterpart of the Genomic Best Linear Unbiased Predictor (i.e., TGBLUP). The threshold model was used to relate a hypothetical underlying scale to the outward categorical response. We present an empirical application where a total of nine models, five without interaction and four with genomic × environment interaction (G×E) and genomic additive × additive × environment interaction (G×G×E), were used. We assessed the proposed models using data consisting of 278 maize lines genotyped with 46,347 single-nucleotide polymorphisms and evaluated for disease resistance [with ordinal scores from 1 (no disease) to 5 (complete infection)] in three environments (Colombia, Zimbabwe, and Mexico). Models with G×E captured a sizeable proportion of the total variability, which indicates the importance of introducing interaction to improve prediction accuracy. Relative to models based on main effects only, the models that included G×E achieved 9-14% gains in prediction accuracy; adding additive × additive interactions did not increase prediction accuracy consistently across locations. Copyright © 2015 Montesinos-López et al.

Patient No-Show Predictive Model Development using Multiple Data Sources for an Effective Overbooking Approach

PubMed Central

Hanauer, D.A.

2014-01-01

Summary Background Patient no-shows in outpatient delivery systems remain problematic. The negative impacts include underutilized medical resources, increased healthcare costs, decreased access to care, and reduced clinic efficiency and provider productivity. Objective To develop an evidence-based predictive model for patient no-shows, and thus improve overbooking approaches in outpatient settings to reduce the negative impact of no-shows. Methods Ten years of retrospective data were extracted from a scheduling system and an electronic health record system from a single general pediatrics clinic, consisting of 7,988 distinct patients and 104,799 visits along with variables regarding appointment characteristics, patient demographics, and insurance information. Descriptive statistics were used to explore the impact of variables on show or no-show status. Logistic regression was used to develop a no-show predictive model, which was then used to construct an algorithm to determine the no-show threshold that calculates a predicted show/no-show status. This approach aims to overbook an appointment where a scheduled patient is predicted to be a no-show. The approach was compared with two commonly-used overbooking approaches to demonstrate the effectiveness in terms of patient wait time, physician idle time, overtime and total cost. Results From the training dataset, the optimal error rate is 10.6% with a no-show threshold being 0.74. This threshold successfully predicts the validation dataset with an error rate of 13.9%. The proposed overbooking approach demonstrated a significant reduction of at least 6% on patient waiting, 27% on overtime, and 3% on total costs compared to other common flat-overbooking methods. Conclusions This paper demonstrates an alternative way to accommodate overbooking, accounting for the prediction of an individual patient’s show/no-show status. The predictive no-show model leads to a dynamic overbooking policy that could improve patient waiting, overtime, and total costs in a clinic day while maintaining a full scheduling capacity. PMID:25298821

Resonance Scattering of Fe XVII X-ray and EUV Lines

NASA Technical Reports Server (NTRS)

Bhatia, A. K.; Saba, J. L. R.; Fisher, Richard R. (Technical Monitor)

2001-01-01

Over the years a number of calculations have been carried out to derive intensities of various X-ray and EUV lines in Fe XVII to compare with observed spectra. The predicted intensities have not agreed with solar observations, particularly for the line at 1.5.02 Angstroms; resonance scattering has been suggested as the source for much of the disagreement. The atomic data calculated earlier used seven configurations having n=3 orbitals and the scattering calculations were carried out only for incident energies above the threshold of the highest fine-structure level. These calculations have now been extended to thirteen configurations having n=4 orbitals and the scattering calculations are carried out below as well as above the threshold of the highest fine structure level. These improved calculations of Fe XVII change the intensity ratios compared to those obtained earlier, bringing the optically thin F(15.02)/F(16.78) ratio and several other ratios closer to the observed values. However, some disagreement with the solar observations still persists, even thought the agreement of the presently calculated optically thin F(15.02)/F(15.26) ratio with the experimental results of Brown et al. (1998) and Laming et al. (2000) has improved. Some of the remaining discrepancy is still thought to be the effect of opacity, which is consistent with expected physical conditions for solar sources. EUV intensity ratios are also calculated and compared with observations. Level populations and intensity ratios are calculated, as a function of column density of Fe XVII, in the slab and cylindrical geometries. As found previously, the predicted intensities for the resonance lines at 15.02 and 15.26 Angstroms exhibit initial increases in flux relative to the forbidden line at 17.10 Angstroms and the resonance line at 16.78 Angstroms as optical thickness increases. The same behavior is predicted for the lines at 12.262 and 12.122 Angstroms. Predicted intensities for some of the allowed EUV lines are also affected by opacity.

A method for managing re-identification risk from small geographic areas in Canada

PubMed Central

2010-01-01

Background A common disclosure control practice for health datasets is to identify small geographic areas and either suppress records from these small areas or aggregate them into larger ones. A recent study provided a method for deciding when an area is too small based on the uniqueness criterion. The uniqueness criterion stipulates that an the area is no longer too small when the proportion of unique individuals on the relevant variables (the quasi-identifiers) approaches zero. However, using a uniqueness value of zero is quite a stringent threshold, and is only suitable when the risks from data disclosure are quite high. Other uniqueness thresholds that have been proposed for health data are 5% and 20%. Methods We estimated uniqueness for urban Forward Sortation Areas (FSAs) by using the 2001 long form Canadian census data representing 20% of the population. We then constructed two logistic regression models to predict when the uniqueness is greater than the 5% and 20% thresholds, and validated their predictive accuracy using 10-fold cross-validation. Predictor variables included the population size of the FSA and the maximum number of possible values on the quasi-identifiers (the number of equivalence classes). Results All model parameters were significant and the models had very high prediction accuracy, with specificity above 0.9, and sensitivity at 0.87 and 0.74 for the 5% and 20% threshold models respectively. The application of the models was illustrated with an analysis of the Ontario newborn registry and an emergency department dataset. At the higher thresholds considerably fewer records compared to the 0% threshold would be considered to be in small areas and therefore undergo disclosure control actions. We have also included concrete guidance for data custodians in deciding which one of the three uniqueness thresholds to use (0%, 5%, 20%), depending on the mitigating controls that the data recipients have in place, the potential invasion of privacy if the data is disclosed, and the motives and capacity of the data recipient to re-identify the data. Conclusion The models we developed can be used to manage the re-identification risk from small geographic areas. Being able to choose among three possible thresholds, a data custodian can adjust the definition of "small geographic area" to the nature of the data and recipient. PMID:20361870

A Novel Approach to Prediction of Mild Obstructive Sleep Disordered Breathing in a Population-Based Sample: The Sleep Heart Health Study

PubMed Central

Caffo, Brian; Diener-West, Marie; Punjabi, Naresh M.; Samet, Jonathan

2010-01-01

This manuscript considers a data-mining approach for the prediction of mild obstructive sleep disordered breathing, defined as an elevated respiratory disturbance index (RDI), in 5,530 participants in a community-based study, the Sleep Heart Health Study. The prediction algorithm was built using modern ensemble learning algorithms, boosting in specific, which allowed for assessing potential high-dimensional interactions between predictor variables or classifiers. To evaluate the performance of the algorithm, the data were split into training and validation sets for varying thresholds for predicting the probability of a high RDI (≥ 7 events per hour in the given results). Based on a moderate classification threshold from the boosting algorithm, the estimated post-test odds of a high RDI were 2.20 times higher than the pre-test odds given a positive test, while the corresponding post-test odds were decreased by 52% given a negative test (sensitivity and specificity of 0.66 and 0.70, respectively). In rank order, the following variables had the largest impact on prediction performance: neck circumference, body mass index, age, snoring frequency, waist circumference, and snoring loudness. Citation: Caffo B; Diener-West M; Punjabi NM; Samet J. A novel approach to prediction of mild obstructive sleep disordered breathing in a population-based sample: the Sleep Heart Health Study. SLEEP 2010;33(12):1641-1648. PMID:21120126

Physiological Correlates of Endurance Time Variability during Constant-Workrate Cycling Exercise in Patients with COPD

PubMed Central

Vivodtzev, Isabelle; Gagnon, Philippe; Pepin, Véronique; Saey, Didier; Laviolette, Louis; Brouillard, Cynthia; Maltais, François

2011-01-01

Rationale The endurance time (Tend) during constant-workrate cycling exercise (CET) is highly variable in COPD. We investigated pulmonary and physiological variables that may contribute to these variations in Tend. Methods Ninety-two patients with COPD completed a CET performed at 80% of peak workrate capacity (Wpeak). Patients were divided into tertiles of Tend [Group 1: <4 min; Group 2: 4–6 min; Group 3: >6 min]. Disease severity (FEV1), aerobic fitness (Wpeak, peak oxygen consumption [ peak], ventilatory threshold [ VT]), quadriceps strength (MVC), symptom scores at the end of CET and exercise intensity during CET (heart rate at the end of CET to heart rate at peak incremental exercise ratio [HRCET/HRpeak]) were analyzed as potential variables influencing Tend. Results Wpeak, peak, VT, MVC, leg fatigue at end of CET, and HRCET/HRpeak were lower in group 1 than in group 2 or 3 (p≤0.05). VT and leg fatigue at end of CET independently predicted Tend in multiple regression analysis (r = 0.50, p = 0.001). Conclusion Tend was independently related to the aerobic fitness and to tolerance to leg fatigue at the end of exercise. A large fraction of the variability in Tend was not explained by the physiological parameters assessed in the present study. Individualization of exercise intensity during CET should help in reducing variations in Tend among patients with COPD. PMID:21386991

Effect of patient age on blood product transfusion after cardiac surgery.

PubMed

Ad, Niv; Massimiano, Paul S; Burton, Nelson A; Halpin, Linda; Pritchard, Graciela; Shuman, Deborah J; Holmes, Sari D

2015-07-01

Blood product transfusion after cardiac surgery is associated with increased morbidity and mortality. Transfusion thresholds are often lower for the elderly, despite the lack of clinical evidence for this practice. This study examined the role of age as a predictor for blood transfusion. A total of 1898 patients were identified who had nonemergent cardiac surgery, between January 2007 and August 2013, without intra-aortic balloon pumps or reoperations, and with short (<24 hours) intensive care unit stays (age ≥75 years; n = 239). Patients age ≥75 years were propensity-score matched to those age <75 years to balance covariates, resulting in 222 patients per group. Analyses of the matched sample examined age as a continuous variable, scaled in 5-year increments. After matching, covariates were balanced between older and younger patients. Older age significantly predicted postoperative (odds ratio = 1.39, P = .028), but not intraoperative (odds ratio = 0.96, P = .559), blood transfusion. Older age predicted longer length of stay (B = 0.21, P < .001), even after adjustment for blood product transfusion (B = 0.20, P < .001). As expected, older age was a significant predictor for poorer survival, even with multivariate adjustment (hazard ratio = 1.34, P = .042). In patients with a routine postoperative course, older age was associated with more postoperative blood transfusion. Older age was also predictive of longer length of stay and poorer survival, even after accounting for clinical factors. Continued study into effects of transfusion, particularly in the elderly, should be directed toward hospital transfusion protocols to optimize perioperative care. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Mechanosensing of stem bending and its interspecific variability in five neotropical rainforest species.

PubMed

Coutand, Catherine; Chevolot, Malia; Lacointe, André; Rowe, Nick; Scotti, Ivan

2010-02-01

In rain forests, sapling survival is highly dependent on the regulation of trunk slenderness (height/diameter ratio): shade-intolerant species have to grow in height as fast as possible to reach the canopy but also have to withstand mechanical loadings (wind and their own weight) to avoid buckling. Recent studies suggest that mechanosensing is essential to control tree dimensions and stability-related morphogenesis. Differences in species slenderness have been observed among rainforest trees; the present study thus investigates whether species with different slenderness and growth habits exhibit differences in mechanosensitivity. Recent studies have led to a model of mechanosensing (sum-of-strains model) that predicts a quantitative relationship between the applied sum of longitudinal strains and the plant's responses in the case of a single bending. Saplings of five different neotropical species (Eperua falcata, E. grandiflora, Tachigali melinonii, Symphonia globulifera and Bauhinia guianensis) were subjected to a regimen of controlled mechanical loading phases (bending) alternating with still phases over a period of 2 months. Mechanical loading was controlled in terms of strains and the five species were subjected to the same range of sum of strains. The application of the sum-of-strain model led to a dose-response curve for each species. Dose-response curves were then compared between tested species. The model of mechanosensing (sum-of-strain model) applied in the case of multiple bending as long as the bending frequency was low. A comparison of dose-response curves for each species demonstrated differences in the stimulus threshold, suggesting two groups of responses among the species. Interestingly, the liana species B. guianensis exhibited a higher threshold than other Leguminosae species tested. This study provides a conceptual framework to study variability in plant mechanosensing and demonstrated interspecific variability in mechanosensing.

Tourism development and economic growth a nonlinear approach

NASA Astrophysics Data System (ADS)

Po, Wan-Chen; Huang, Bwo-Nung

2008-09-01

We use cross sectional data (1995-2005 yearly averages) for 88 countries to investigate the nonlinear relationship between tourism development and economic growth when a threshold variable is used. The degree of tourism specialization ( qi, defined as receipts from international tourism as a percentage of GDP) is used as the threshold variable. The results of the tests for nonlinearity indicate that the 88 countries’ data should be separated into three different groups or regimes to analyze the tourism-growth nexus. The results of the threshold regression show that when the qi is below 4.0488% (regime 1, 57 countries) or above 4.7337% (regime 3, 23 countries), there exists a significantly positive relationship between tourism growth and economic growth. However, when the qi is above 4.0488% and below 4.7337% (regime 2, 8 countries), we are unable to find evidence of such a significant relationship. Further in-depth analysis reveals that relatively low ratios of the value added of the service industry to GDP, and the forested area per country area are able to explain why we are unable to find a significant relationship between these two variables in regime 2’s countries.

Re-assess Vector Indices Threshold as an Early Warning Tool for Predicting Dengue Epidemic in a Dengue Non-endemic Country

PubMed Central

Hsu, Pi-Shan; Chen, Chaur-Dong; Lian, Ie-Bin; Chao, Day-Yu

2015-01-01

Background Despite dengue dynamics being driven by complex interactions between human hosts, mosquito vectors and viruses that are influenced by climate factors, an operational model that will enable health authorities to anticipate the outbreak risk in a dengue non-endemic area has not been developed. The objectives of this study were to evaluate the temporal relationship between meteorological variables, entomological surveillance indices and confirmed dengue cases; and to establish the threshold for entomological surveillance indices including three mosquito larval indices [Breteau (BI), Container (CI) and House indices (HI)] and one adult index (AI) as an early warning tool for dengue epidemic. Methodology/Principal Findings Epidemiological, entomological and meteorological data were analyzed from 2005 to 2012 in Kaohsiung City, Taiwan. The successive waves of dengue outbreaks with different magnitudes were recorded in Kaohsiung City, and involved a dominant serotype during each epidemic. The annual indigenous dengue cases usually started from May to June and reached a peak in October to November. Vector data from 2005–2012 showed that the peak of the adult mosquito population was followed by a peak in the corresponding dengue activity with a lag period of 1–2 months. Therefore, we focused the analysis on the data from May to December and the high risk district, where the inspection of the immature and mature mosquitoes was carried out on a weekly basis and about 97.9% dengue cases occurred. The two-stage model was utilized here to estimate the risk and time-lag effect of annual dengue outbreaks in Taiwan. First, Poisson regression was used to select the optimal subset of variables and time-lags for predicting the number of dengue cases, and the final results of the multivariate analysis were selected based on the smallest AIC value. Next, each vector index models with selected variables were subjected to multiple logistic regression models to examine the accuracy of predicting the occurrence of dengue cases. The results suggested that Model-AI, BI, CI and HI predicted the occurrence of dengue cases with 83.8, 87.8, 88.3 and 88.4% accuracy, respectively. The predicting threshold based on individual Model-AI, BI, CI and HI was 0.97, 1.16, 1.79 and 0.997, respectively. Conclusion/Significance There was little evidence of quantifiable association among vector indices, meteorological factors and dengue transmission that could reliably be used for outbreak prediction. Our study here provided the proof-of-concept of how to search for the optimal model and determine the threshold for dengue epidemics. Since those factors used for prediction varied, depending on the ecology and herd immunity level under different geological areas, different thresholds may be developed for different countries using a similar structure of the two-stage model. PMID:26366874

Mathematical Model Relating Uniaxial Compressive Behavior of Manufactured Sand Mortar to MIP-Derived Pore Structure Parameters

PubMed Central

Tian, Zhenghong; Bu, Jingwu

2014-01-01

The uniaxial compression response of manufactured sand mortars proportioned using different water-cement ratio and sand-cement ratio is examined. Pore structure parameters such as porosity, threshold diameter, mean diameter, and total amounts of macropores, as well as shape and size of micropores are quantified by using mercury intrusion porosimetry (MIP) technique. Test results indicate that strains at peak stress and compressive strength decreased with the increasing sand-cement ratio due to insufficient binders to wrap up entire sand. A compression stress-strain model of normal concrete extending to predict the stress-strain relationships of manufactured sand mortar is verified and agreed well with experimental data. Furthermore, the stress-strain model constant is found to be influenced by threshold diameter, mean diameter, shape, and size of micropores. A mathematical model relating stress-strain model constants to the relevant pore structure parameters of manufactured sand mortar is developed. PMID:25133257

Mathematical model relating uniaxial compressive behavior of manufactured sand mortar to MIP-derived pore structure parameters.

PubMed

Tian, Zhenghong; Bu, Jingwu

2014-01-01

The uniaxial compression response of manufactured sand mortars proportioned using different water-cement ratio and sand-cement ratio is examined. Pore structure parameters such as porosity, threshold diameter, mean diameter, and total amounts of macropores, as well as shape and size of micropores are quantified by using mercury intrusion porosimetry (MIP) technique. Test results indicate that strains at peak stress and compressive strength decreased with the increasing sand-cement ratio due to insufficient binders to wrap up entire sand. A compression stress-strain model of normal concrete extending to predict the stress-strain relationships of manufactured sand mortar is verified and agreed well with experimental data. Furthermore, the stress-strain model constant is found to be influenced by threshold diameter, mean diameter, shape, and size of micropores. A mathematical model relating stress-strain model constants to the relevant pore structure parameters of manufactured sand mortar is developed.

Identification of phreatophytic groundwater dependent ecosystems using geospatial technologies

NASA Astrophysics Data System (ADS)

Perez Hoyos, Isabel Cristina

The protection of groundwater dependent ecosystems (GDEs) is increasingly being recognized as an essential aspect for the sustainable management and allocation of water resources. Ecosystem services are crucial for human well-being and for a variety of flora and fauna. However, the conservation of GDEs is only possible if knowledge about their location and extent is available. Several studies have focused on the identification of GDEs at specific locations using ground-based measurements. However, recent progress in technologies such as remote sensing and their integration with geographic information systems (GIS) has provided alternative ways to map GDEs at much larger spatial extents. This study is concerned with the discovery of patterns in geospatial data sets using data mining techniques for mapping phreatophytic GDEs in the United States at 1 km spatial resolution. A methodology to identify the probability of an ecosystem to be groundwater dependent is developed. Probabilities are obtained by modeling the relationship between the known locations of GDEs and main factors influencing groundwater dependency, namely water table depth (WTD) and aridity index (AI). A methodology is proposed to predict WTD at 1 km spatial resolution using relevant geospatial data sets calibrated with WTD observations. An ensemble learning algorithm called random forest (RF) is used in order to model the distribution of groundwater in three study areas: Nevada, California, and Washington, as well as in the entire United States. RF regression performance is compared with a single regression tree (RT). The comparison is based on contrasting training error, true prediction error, and variable importance estimates of both methods. Additionally, remote sensing variables are omitted from the process of fitting the RF model to the data to evaluate the deterioration in the model performance when these variables are not used as an input. Research results suggest that although the prediction accuracy of a single RT is reduced in comparison with RFs, single trees can still be used to understand the interactions that might be taking place between predictor variables and the response variable. Regarding RF, there is a great potential in using the power of an ensemble of trees for prediction of WTD. The superior capability of RF to accurately map water table position in Nevada, California, and Washington demonstrate that this technique can be applied at scales larger than regional levels. It is also shown that the removal of remote sensing variables from the RF training process degrades the performance of the model. Using the predicted WTD, the probability of an ecosystem to be groundwater dependent (GDE probability) is estimated at 1 km spatial resolution. The modeling technique is evaluated in the state of Nevada, USA to develop a systematic approach for the identification of GDEs and it is then applied in the United States. The modeling approach selected for the development of the GDE probability map results from a comparison of the performance of classification trees (CT) and classification forests (CF). Predictive performance evaluation for the selection of the most accurate model is achieved using a threshold independent technique, and the prediction accuracy of both models is assessed in greater detail using threshold-dependent measures. The resulting GDE probability map can potentially be used for the definition of conservation areas since it can be translated into a binary classification map with two classes: GDE and NON-GDE. These maps are created by selecting a probability threshold. It is demonstrated that the choice of this threshold has dramatic effects on deterministic model performance measures.

The fragmentation threshold and implications for explosive eruptions

NASA Astrophysics Data System (ADS)

Kennedy, B.; Spieler, O.; Kueppers, U.; Scheu, B.; Mueller, S.; Taddeucci, J.; Dingwell, D.

2003-04-01

The fragmentation threshold is the minimum pressure differential required to cause a porous volcanic rock to form pyroclasts. This is a critical parameter when considering the shift from effusive to explosive eruptions. We fragmented a variety of natural volcanic rock samples at room temperature (20oC) and high temperature (850oC) using a shock tube modified after Aldibirov and Dingwell (1996). This apparatus creates a pressure differential which drives fragmentation. Pressurized gas in the vesicles of the rock suddenly expands, blowing the sample apart. For this reason, the porosity is the primary control on the fragmentation threshold. On a graph of porosity against fragmentation threshold, our results from a variety of natural samples at both low and high temperatures all plot on the same curve and show the threshold increasing steeply at low porosities. A sharp decrease in the fragmentation threshold occurs as porosity increases from 0- 15%, while a more gradual decrease is seen from 15- 85%. The high temperature experiments form a curve with less variability than the low temperature experiments. For this reason, we have chosen to model the high temperature thresholds. The curve can be roughly predicted by the tensile strength of glass (140 MPa) divided by the porosity. Fractured phenocrysts in the majority of our samples reduces the overall strength of the sample. For this reason, the threshold values can be more accurately predicted by % matrix x the tensile strength/ porosity. At very high porosities the fragmentation threshold varies significantly due to the effect of bubble shape and size distributions on the permeability (Mueller et al, 2003). For example, high thresholds are seen for samples with very high permeabilities, where gas flow reduces the local pressure differential. These results allow us to predict the fragmentation threshold for any volcanic rock for which the porosity and crystal contents are known. During explosive eruptions, the fragmentation threshold may be exceeded in two ways: (1) by building an overpressure within the vesicles above the fragmentation threshold or (2) by unloading and exposing lithostatically pressurised magma to lower pressures. Using this data, we can in principle estimate the height of dome collapse or amount of overpressure necessary to produce an explosive eruption.

Epidemiologic research using probabilistic outcome definitions.

PubMed

Cai, Bing; Hennessy, Sean; Lo Re, Vincent; Small, Dylan S

2015-01-01

Epidemiologic studies using electronic healthcare data often define the presence or absence of binary clinical outcomes by using algorithms with imperfect specificity, sensitivity, and positive predictive value. This results in misclassification and bias in study results. We describe and evaluate a new method called probabilistic outcome definition (POD) that uses logistic regression to estimate the probability of a clinical outcome using multiple potential algorithms and then uses multiple imputation to make valid inferences about the risk ratio or other epidemiologic parameters of interest. We conducted a simulation to evaluate the performance of the POD method with two variables that can predict the true outcome and compared the POD method with the conventional method. The simulation results showed that when the true risk ratio is equal to 1.0 (null), the conventional method based on a binary outcome provides unbiased estimates. However, when the risk ratio is not equal to 1.0, the traditional method, either using one predictive variable or both predictive variables to define the outcome, is biased when the positive predictive value is <100%, and the bias is very severe when the sensitivity or positive predictive value is poor (less than 0.75 in our simulation). In contrast, the POD method provides unbiased estimates of the risk ratio both when this measure of effect is equal to 1.0 and not equal to 1.0. Even when the sensitivity and positive predictive value are low, the POD method continues to provide unbiased estimates of the risk ratio. The POD method provides an improved way to define outcomes in database research. This method has a major advantage over the conventional method in that it provided unbiased estimates of risk ratios and it is easy to use. Copyright © 2014 John Wiley & Sons, Ltd.

A comparison of South Asian specific and established BMI thresholds for determining obesity prevalence in pregnancy and predicting pregnancy complications: findings from the Born in Bradford cohort.

PubMed

Bryant, M; Santorelli, G; Lawlor, D A; Farrar, D; Tuffnell, D; Bhopal, R; Wright, J

2014-03-01

To describe how maternal obesity prevalence varies by established international and South Asian specific body mass index (BMI) cut-offs in women of Pakistani origin and investigate whether different BMI thresholds can help to identify women at risk of adverse pregnancy and birth outcomes. Prospective bi-ethnic birth cohort study (the Born in Bradford (BiB) cohort). Bradford, a deprived city in the North of the UK. A total of 8478 South Asian and White British pregnant women participated in the BiB cohort study. Maternal obesity prevalence; prevalence of known obesity-related adverse pregnancy outcomes: mode of birth, hypertensive disorders of pregnancy (HDP), gestational diabetes, macrosomia and pre-term births. Application of South Asian BMI cut-offs increased prevalence of obesity in Pakistani women from 18.8 (95% confidence interval (CI) 17.6-19.9) to 30.9% (95% CI 29.5-32.2). With the exception of pre-term births, there was a positive linear relationship between BMI and prevalence of adverse pregnancy and birth outcomes, across almost the whole BMI distribution. Risk of gestational diabetes and HDP increased more sharply in Pakistani women after a BMI threshold of at least 30 kg m(-2), but there was no evidence of a sharp increase in any risk factors at the new, lower thresholds suggested for use in South Asian women. BMI was a good single predictor of outcomes (area under the receiver operating curve: 0.596-0.685 for different outcomes); prediction was more discriminatory and accurate with BMI as a continuous variable than as a binary variable for any possible cut-off point. Applying the new South Asian threshold to pregnant women would markedly increase those who were referred for monitoring and lifestyle advice. However, our results suggest that lowering the BMI threshold in South Asian women would not improve the predictive ability for identifying those who were at risk of adverse pregnancy outcomes.

A Ratiometric Threshold for Determining Presence of Cancer During Fluorescence-guided Surgery

PubMed Central

Warram, Jason M; de Boer, Esther; Moore, Lindsay S.; Schmalbach, Cecelia E; Withrow, Kirk P; Carroll, William R; Richman, Joshua S; Morlandt, Anthony B; Brandwein-Gensler, Margaret; Rosenthal, Eben L

2015-01-01

Background&Objective Fluorescence-guided imaging to assist in identification of malignant margins has the potential to dramatically improve oncologic surgery. However a standardized method for quantitative assessment of disease-specific fluorescence has not been investigated. Introduced here is a ratiometric threshold derived from mean fluorescent tissue intensity that can be used to semi-quantitatively delineate tumor from normal tissue. Methods Open-field and a closed-field imaging devices were used to quantify fluorescence in punch biopsy tissues sampled from primary tumors collected during a phase 1 trial evaluating the safety of cetuximab-IRDye800 in patients (n=11) undergoing surgical intervention for head and neck cancer. Fluorescence ratios were calculated using mean fluorescence intensity (MFI) from punch biopsy normalized by MFI of patient-matched tissues. Ratios were compared to pathological assessment and a ratiometric threshold was established to predict presence of cancer. Results During open-field imaging using an intraoperative device, the threshold for muscle normalized tumor fluorescence was found to be 2.7, which produced a sensitivity of 90.5% and specificity of 78.6% for delineating disease tissue. The skin-normalized threshold generated greater sensitivity (92.9%) and specificity (81.0%). Conclusion Successful implementation of a semi-quantitative threshold can provide a scientific methodology for delineating disease from normal tissue during fluorescence-guided resection of cancer. PMID:26074273

Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

2016-03-01

The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

NASA Astrophysics Data System (ADS)

Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

2015-11-01

One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

Chemical characterization of the acid alteration of diesel fuel: Non-targeted analysis by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry with tile-based Fisher ratio and combinatorial threshold determination.

PubMed

Parsons, Brendon A; Pinkerton, David K; Wright, Bob W; Synovec, Robert E

2016-04-01

The illicit chemical alteration of petroleum fuels is of keen interest, particularly to regulatory agencies that set fuel specifications, or taxes/credits based on those specifications. One type of alteration is the reaction of diesel fuel with concentrated sulfuric acid. Such reactions are known to subtly alter the chemical composition of the fuel, particularly the aromatic species native to the fuel. Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) is well suited for the analysis of diesel fuel, but may provide the analyst with an overwhelming amount of data, particularly in sample-class comparison experiments comprised of many samples. Tile-based Fisher-ratio (F-ratio) analysis reduces the abundance of data in a GC×GC-TOFMS experiment to only the peaks which significantly distinguish the unaltered and acid altered sample classes. Three samples of diesel fuel from differently branded filling stations were each altered to discover chemical features, i.e., analyte peaks, which were consistently changed by the acid reaction. Using different fuels prioritizes the discovery of features likely to be robust to the variation present between fuel samples and may consequently be useful in determining whether an unknown sample has been acid altered. The subsequent analysis confirmed that aromatic species are removed by the acid alteration, with the degree of removal consistent with predicted reactivity toward electrophilic aromatic sulfonation. Additionally, we observed that alkenes and alkynes were also removed from the fuel, and that sulfur dioxide or compounds that degrade to sulfur dioxide are generated by the acid alteration. In addition to applying the previously reported tile-based F-ratio method, this report also expands null distribution analysis to algorithmically determine an F-ratio threshold to confidently select only the features which are sufficiently class-distinguishing. When applied to the acid alteration of diesel fuel, the suggested per-hit F-ratio threshold was 12.4, which is predicted to maintain the false discovery rate (FDR) below 0.1%. Using this F-ratio threshold, 107 of the 3362 preliminary hits were deemed significantly changing due to the acid alteration, with the number of false positives estimated to be about 3. Validation of the F-ratio analysis was performed using an additional three fuels. Copyright © 2016 Elsevier B.V. All rights reserved.

Luminance-model-based DCT quantization for color image compression

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Peterson, Heidi A.

1992-01-01

A model is developed to approximate visibility thresholds for discrete cosine transform (DCT) coefficient quantization error based on the peak-to-peak luminance of the error image. Experimentally measured visibility thresholds for R, G, and B DCT basis functions can be predicted by a simple luminance-based detection model. This model allows DCT coefficient quantization matrices to be designed for display conditions other than those of the experimental measurements: other display luminances, other veiling luminances, and other spatial frequencies (different pixel spacings, viewing distances, and aspect ratios).

Effects of oxygen on responses to heating in two lizard species sampled along an elevational gradient.

PubMed

DuBois, P Mason; Shea, Tanner K; Claunch, Natalie M; Taylor, Emily N

2017-08-01

Thermal tolerance is an important variable in predictive models about the effects of global climate change on species distributions, yet the physiological mechanisms responsible for reduced performance at high temperatures in air-breathing vertebrates are not clear. We conducted an experiment to examine how oxygen affects three variables exhibited by ectotherms as they heat-gaping threshold, panting threshold, and loss of righting response (the latter indicating the critical thermal maximum)-in two lizard species along an elevational (and therefore environmental oxygen partial pressure) gradient. Oxygen partial pressure did not impact these variables in either species. We also exposed lizards at each elevation to severely hypoxic gas to evaluate their responses to hypoxia. Severely low oxygen partial pressure treatments significantly reduced the gaping threshold, panting threshold, and critical thermal maximum. Further, under these extreme hypoxic conditions, these variables were strongly and positively related to partial pressure of oxygen. In an elevation where both species overlapped, the thermal tolerance of the high elevation species was less affected by hypoxia than that of the low elevation species, suggesting the high elevation species may be adapted to lower oxygen partial pressures. In the high elevation species, female lizards had higher thermal tolerance than males. Our data suggest that oxygen impacts the thermal tolerance of lizards, but only under severely hypoxic conditions, possibly as a result of hypoxia-induced anapyrexia. Copyright © 2017. Published by Elsevier Ltd.

Neurofeedback in three patients in the state of unresponsive wakefulness.

PubMed

Keller, Ingo; Garbacenkaite, Ruta

2015-12-01

Some severely brain injured patients remain unresponsive, only showing reflex movements without any response to command. This syndrome has been named unresponsive wakefulness syndrome (UWS). The objective of the present study was to determine whether UWS patients are able to alter their brain activity using neurofeedback (NFB) technique. A small sample of three patients received a daily session of NFB for 3 weeks. We applied the ratio of theta and beta amplitudes as a feedback variable. Using an automatic threshold function, patients heard their favourite music whenever their theta/beta ratio dropped below the threshold. Changes in awareness were assessed weekly with the JFK Coma Recovery Scale-Revised for each treatment week, as well as 3 weeks before and after NFB. Two patients showed a decrease in their theta/beta ratio and theta-amplitudes during this period. The third patient showed no systematic changes in his EEG activity. The results of our study provide the first evidence that NFB can be used in patients in a state of unresponsive wakefulness.

Predictive Variables of Half-Marathon Performance for Male Runners.

PubMed

Gómez-Molina, Josué; Ogueta-Alday, Ana; Camara, Jesus; Stickley, Christoper; Rodríguez-Marroyo, José A; García-López, Juan

2017-06-01

The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48) was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30) to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO 2max , speed at the anaerobic threshold, peak speed) and biomechanical variables (contact and flight times, step length and step rate) were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1), 94.9% by physiological variables (Equation 2), 93.7% by biomechanical parameters (Equation 3) and 96.2% by a general equation (Equation 4). Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively). The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance.

An analytical method for predicting postwildfire peak discharges

USGS Publications Warehouse

Moody, John A.

2012-01-01

An analytical method presented here that predicts postwildfire peak discharge was developed from analysis of paired rainfall and runoff measurements collected from selected burned basins. Data were collected from 19 mountainous basins burned by eight wildfires in different hydroclimatic regimes in the western United States (California, Colorado, Nevada, New Mexico, and South Dakota). Most of the data were collected for the year of the wildfire and for 3 to 4 years after the wildfire. These data provide some estimate of the changes with time of postwildfire peak discharges, which are known to be transient but have received little documentation. The only required inputs for the analytical method are the burned area and a quantitative measure of soil burn severity (change in the normalized burn ratio), which is derived from Landsat reflectance data and is available from either the U.S. Department of Agriculture Forest Service or the U.S. Geological Survey. The method predicts the postwildfire peak discharge per unit burned area for the year of a wildfire, the first year after a wildfire, and the second year after a wildfire. It can be used at three levels of information depending on the data available to the user; each subsequent level requires either more data or more processing of the data. Level 1 requires only the burned area. Level 2 requires the burned area and the basin average value of the change in the normalized burn ratio. Level 3 requires the burned area and the calculation of the hydraulic functional connectivity, which is a variable that incorporates the sequence of soil burn severity along hillslope flow paths within the burned basin. Measurements indicate that the unit peak discharge response increases abruptly when the 30-minute maximum rainfall intensity is greater than about 5 millimeters per hour (0.2 inches per hour). This threshold may relate to a change in runoff generation from saturated-excess to infiltration-excess overland flow. The threshold value was about 7.6 millimeters per hour for the year of the wildfire and the first year after the wildfire, and it was about 11.1 millimeters per hour for the second year after the wildfire.

How to Assess the Value of Medicines?

PubMed Central

Simoens, Steven

2010-01-01

This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value. PMID:21607066

How to assess the value of medicines?

PubMed

Simoens, Steven

2010-01-01

This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value.

High Mid-Flow to Vital Capacity Ratio and the Response to Exercise in Children With Congenital Heart Disease.

PubMed

Vilozni, Daphna; Alcaneses-Ofek, Maria Rosario; Reuveny, Ronen; Rosenblum, Omer; Inbar, Omri; Katz, Uriel; Ziv-Baran, Tomer; Dubnov-Raz, Gal

2016-12-01

Pulmonary mechanics may play a role in exercise intolerance in patients with congenital heart disease (CHD). A reduced FVC volume could increase the ratio between mid-flow (FEF 25-75% ) and FVC, which is termed high dysanapsis. The relationship between high dysanapsis and the response to maximum-intensity exercise in children with CHD had not yet been studied. The aim of this work was to examine whether high dysanapsis is related to the cardiopulmonary response to maximum-intensity exercise in pediatric subjects with CHD. We retrospectively collected data from 42 children and adolescents with CHD who had either high dysanapsis (ratio >1.2; n = 21) or normal dysanapsis (control) (n = 21) as measured by spirometry. Data extracted from cardiopulmonary exercise test reports included peak values of heart rate, work load, V̇ O 2 , V̇ CO 2 , and ventilation parameters and submaximum values, including ventilatory threshold and ventilatory equivalents. There were no significant differences in demographic and clinical parameters between the groups. Participants with high dysanapsis differed from controls in lower median peak oxygen consumption (65.8% vs 83.0% of predicted, P = .02), peak oxygen pulse (78.6% vs 87.8% of predicted, P = .02), ventilatory threshold (73.8% vs 85.3% of predicted, P = .03), and maximum breathing frequency (106% vs 121% of predicted, P = .035). In the high dysanapsis group only, median peak ventilation and tidal volume were significantly lower than 80% of predicted values. In children and adolescents with corrected CHD, high dysanapsis was associated with a lower ventilatory capacity and reduced aerobic fitness, which may indicate respiratory muscle impairments. Copyright © 2016 by Daedalus Enterprises.

Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.

PubMed

Aliabadi, Mohsen; Farhadian, Maryam; Darvishi, Ebrahim

2015-08-01

Prediction of hearing loss in noisy workplaces is considered to be an important aspect of hearing conservation program. Artificial intelligence, as a new approach, can be used to predict the complex phenomenon such as hearing loss. Using artificial neural networks, this study aims to present an empirical model for the prediction of the hearing loss threshold among noise-exposed workers. Two hundred and ten workers employed in a steel factory were chosen, and their occupational exposure histories were collected. To determine the hearing loss threshold, the audiometric test was carried out using a calibrated audiometer. The personal noise exposure was also measured using a noise dosimeter in the workstations of workers. Finally, data obtained five variables, which can influence the hearing loss, were used for the development of the prediction model. Multilayer feed-forward neural networks with different structures were developed using MATLAB software. Neural network structures had one hidden layer with the number of neurons being approximately between 5 and 15 neurons. The best developed neural networks with one hidden layer and ten neurons could accurately predict the hearing loss threshold with RMSE = 2.6 dB and R(2) = 0.89. The results also confirmed that neural networks could provide more accurate predictions than multiple regressions. Since occupational hearing loss is frequently non-curable, results of accurate prediction can be used by occupational health experts to modify and improve noise exposure conditions.

Diagnostic accuracy of spot urinary protein and albumin to creatinine ratios for detection of significant proteinuria or adverse pregnancy outcome in patients with suspected pre-eclampsia: systematic review and meta-analysis

PubMed Central

Morris, R K; Riley, R D; Doug, M; Deeks, J J

2012-01-01

Objective To determine the diagnostic accuracy of two “spot urine” tests for significant proteinuria or adverse pregnancy outcome in pregnant women with suspected pre-eclampsia. Design Systematic review and meta-analysis. Data sources Searches of electronic databases 1980 to January 2011, reference list checking, hand searching of journals, and contact with experts. Inclusion criteria Diagnostic studies, in pregnant women with hypertension, that compared the urinary spot protein to creatinine ratio or albumin to creatinine ratio with urinary protein excretion over 24 hours or adverse pregnancy outcome. Study characteristics, design, and methodological and reporting quality were objectively assessed. Data extraction Study results relating to diagnostic accuracy were extracted and synthesised using multivariate random effects meta-analysis methods. Results Twenty studies, testing 2978 women (pregnancies), were included. Thirteen studies examining protein to creatinine ratio for the detection of significant proteinuria were included in the multivariate analysis. Threshold values for protein to creatinine ratio ranged between 0.13 and 0.5, with estimates of sensitivity ranging from 0.65 to 0.89 and estimates of specificity from 0.63 to 0.87; the area under the summary receiver operating characteristics curve was 0.69. On average, across all studies, the optimum threshold (that optimises sensitivity and specificity combined) seems to be between 0.30 and 0.35 inclusive. However, no threshold gave a summary estimate above 80% for both sensitivity and specificity, and considerable heterogeneity existed in diagnostic accuracy across studies at most thresholds. No studies looked at protein to creatinine ratio and adverse pregnancy outcome. For albumin to creatinine ratio, meta-analysis was not possible. Results from a single study suggested that the most predictive result, for significant proteinuria, was with the DCA 2000 quantitative analyser (>2 mg/mmol) with a summary sensitivity of 0.94 (95% confidence interval 0.86 to 0.98) and a specificity of 0.94 (0.87 to 0.98). In a single study of adverse pregnancy outcome, results for perinatal death were a sensitivity of 0.82 (0.48 to 0.98) and a specificity of 0.59 (0.51 to 0.67). Conclusion The maternal “spot urine” estimate of protein to creatinine ratio shows promising diagnostic value for significant proteinuria in suspected pre-eclampsia. The existing evidence is not, however, sufficient to determine how protein to creatinine ratio should be used in clinical practice, owing to the heterogeneity in test accuracy and prevalence across studies. Insufficient evidence is available on the use of albumin to creatinine ratio in this area. Insufficient evidence exists for either test to predict adverse pregnancy outcome. PMID:22777026

Dose-response relationships for the onset of avoidance of sonar by free-ranging killer whales.

PubMed

Miller, Patrick J O; Antunes, Ricardo N; Wensveen, Paul J; Samarra, Filipa I P; Alves, Ana Catarina; Tyack, Peter L; Kvadsheim, Petter H; Kleivane, Lars; Lam, Frans-Peter A; Ainslie, Michael A; Thomas, Len

2014-02-01

Eight experimentally controlled exposures to 1-2 kHz or 6-7 kHz sonar signals were conducted with four killer whale groups. The source level and proximity of the source were increased during each exposure in order to reveal response thresholds. Detailed inspection of movements during each exposure session revealed sustained changes in speed and travel direction judged to be avoidance responses during six of eight sessions. Following methods developed for Phase-I clinical trials in human medicine, response thresholds ranging from 94 to 164 dB re 1 μPa received sound pressure level (SPL) were fitted to Bayesian dose-response functions. Thresholds did not consistently differ by sonar frequency or whether a group had previously been exposed, with a mean SPL response threshold of 142 ± 15 dB (mean ± s.d.). High levels of between- and within-individual variability were identified, indicating that thresholds depended upon other undefined contextual variables. The dose-response functions indicate that some killer whales started to avoid sonar at received SPL below thresholds assumed by the U.S. Navy. The predicted extent of habitat over which avoidance reactions occur depends upon whether whales responded to proximity or received SPL of the sonar or both, but was large enough to raise concerns about biological consequences to the whales.

Predicting Vasovagal Syncope from Heart Rate and Blood Pressure: A Prospective Study in 140 Subjects.

PubMed

Virag, Nathalie; Erickson, Mark; Taraborrelli, Patricia; Vetter, Rolf; Lim, Phang Boon; Sutton, Richard

2018-04-28

We developed a vasovagal syncope (VVS) prediction algorithm for use during head-up tilt with simultaneous analysis of heart rate (HR) and systolic blood pressure (SBP). We previously tested this algorithm retrospectively in 1155 subjects, showing sensitivity 95%, specificity 93% and median prediction time of 59s. This study was prospective, single center, on 140 subjects to evaluate this VVS prediction algorithm and assess if retrospective results were reproduced and clinically relevant. Primary endpoint was VVS prediction: sensitivity and specificity >80%. In subjects, referred for 60° head-up tilt (Italian protocol), non-invasive HR and SBP were supplied to the VVS prediction algorithm: simultaneous analysis of RR intervals, SBP trends and their variability represented by low-frequency power generated cumulative risk which was compared with a predetermined VVS risk threshold. When cumulative risk exceeded threshold, an alert was generated. Prediction time was duration between first alert and syncope. Of 140 subjects enrolled, data was usable for 134. Of 83 tilt+ve (61.9%), 81 VVS events were correctly predicted and of 51 tilt-ve subjects (38.1%), 45 were correctly identified as negative by the algorithm. Resulting algorithm performance was sensitivity 97.6%, specificity 88.2%, meeting primary endpoint. Mean VVS prediction time was 2min 26s±3min16s with median 1min 25s. Using only HR and HR variability (without SBP) the mean prediction time reduced to 1min34s±1min45s with median 1min13s. The VVS prediction algorithm, is clinically-relevant tool and could offer applications including providing a patient alarm, shortening tilt-test time, or triggering pacing intervention in implantable devices. Copyright © 2018. Published by Elsevier Inc.

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test

PubMed Central

Ham, Joo-ho; Park, Hun-Young; Kim, Youn-ho; Bae, Sang-kon; Ko, Byung-hoon

2017-01-01

[Purpose] The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. [Methods] We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20–59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. [Results] Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. [Conclusion] These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. PMID:29036765

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test.

PubMed

Ham, Joo-Ho; Park, Hun-Young; Kim, Youn-Ho; Bae, Sang-Kon; Ko, Byung-Hoon; Nam, Sang-Seok

2017-09-30

The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20-59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. ©2017 The Korean Society for Exercise Nutrition

Self-Organization on Social Media: Endo-Exo Bursts and Baseline Fluctuations

PubMed Central

Oka, Mizuki; Hashimoto, Yasuhiro; Ikegami, Takashi

2014-01-01

A salient dynamic property of social media is bursting behavior. In this paper, we study bursting behavior in terms of the temporal relation between a preceding baseline fluctuation and the successive burst response using a frequency time series of 3,000 keywords on Twitter. We found that there is a fluctuation threshold up to which the burst size increases as the fluctuation increases and that above the threshold, there appears a variety of burst sizes. We call this threshold the critical threshold. Investigating this threshold in relation to endogenous bursts and exogenous bursts based on peak ratio and burst size reveals that the bursts below this threshold are endogenously caused and above this threshold, exogenous bursts emerge. Analysis of the 3,000 keywords shows that all the nouns have both endogenous and exogenous origins of bursts and that each keyword has a critical threshold in the baseline fluctuation value to distinguish between the two. Having a threshold for an input value for activating the system implies that Twitter is an excitable medium. These findings are useful for characterizing how excitable a keyword is on Twitter and could be used, for example, to predict the response to particular information on social media. PMID:25329610

Coupled soil respiration and transpiration dynamics from tree-scale to catchment scale in dry Rocky Mountain pine forests and the role of snowpack

NASA Astrophysics Data System (ADS)

Berryman, E.; Barnard, H. R.; Brooks, P. D.; Adams, H.; Burns, M. A.; Wilson, W.; Stielstra, C. M.

2013-12-01

A current ecohydrological challenge is quantifying the exact nature of carbon (C) and water couplings across landscapes. An emerging framework of understanding places plant physiological processes as a central control over soil respiration, the largest source of CO2 to the atmosphere. In dry montane forests, spatial and temporal variability in forest physiological processes are governed by hydrological patterns. Critical feedbacks involving respiration, moisture supply and tree physiology are poorly understood and must be quantified at the landscape level to better predict carbon cycle implications of regional drought under future climate change. We present data from an experiment designed to capture landscape variability in key coupled hydrological and C processes in forests of Colorado's Front Range. Sites encompass three catchments within the Boulder Creek watershed, range from 1480 m to 3021 m above sea level and are co-located with the DOE Niwot Ridge Ameriflux site and the Boulder Creek Critical Zone Observatory. Key hydrological measurements (soil moisture, transpiration) are coupled with soil respiration measurements within each catchment at different landscape positions. This three-dimensional study design also allows for the examination of the role of water subsidies from uplands to lowlands in controlling respiration. Initial findings from 2012 reveal a moisture threshold response of the sensitivity of soil respiration to temperature. This threshold may derive from tree physiological responses to variation in moisture availability, which in turn is controlled by the persistence of snowpack. Using data collected in 2013, first, we determine whether respiration moisture thresholds represent triggers for transpiration at the individual tree level. Next, using stable isotope ratios of soil respiration and xylem and soil water, we compare the depths of respiration to depths of water uptake to assign tree vs. understory sources of respiration. This will help determine whether tree root-zone respiration exhibits a similar moisture threshold. Lastly, we examine whether moisture thresholds to temperature sensitivity are consistent across a range of snowpack persistence. Findings are compared to data collected from sites in Arizona and New Mexico to better establish the role of winter precipitation in governing growing season respiration rates. The outcome of this study will contribute to a better understanding of linkages among water, tree physiology, and soil respiration with the ultimate goal of scaling plot-level respiration fluxes to entire catchments.

Monitoring and modeling to predict Escherichia coli at Presque Isle Beach 2, City of Erie, Erie County, Pennsylvania

USGS Publications Warehouse

Zimmerman, Tammy M.

2006-01-01

The Lake Erie shoreline in Pennsylvania spans nearly 40 miles and is a valuable recreational resource for Erie County. Nearly 7 miles of the Lake Erie shoreline lies within Presque Isle State Park in Erie, Pa. Concentrations of Escherichia coli (E. coli) bacteria at permitted Presque Isle beaches occasionally exceed the single-sample bathing-water standard, resulting in unsafe swimming conditions and closure of the beaches. E. coli concentrations and other water-quality and environmental data collected at Presque Isle Beach 2 during the 2004 and 2005 recreational seasons were used to develop models using tobit regression analyses to predict E. coli concentrations. All variables statistically related to E. coli concentrations were included in the initial regression analyses, and after several iterations, only those explanatory variables that made the models significantly better at predicting E. coli concentrations were included in the final models. Regression models were developed using data from 2004, 2005, and the combined 2-year dataset. Variables in the 2004 model and the combined 2004-2005 model were log10 turbidity, rain weight, wave height (calculated), and wind direction. Variables in the 2005 model were log10 turbidity and wind direction. Explanatory variables not included in the final models were water temperature, streamflow, wind speed, and current speed; model results indicated these variables did not meet significance criteria at the 95-percent confidence level (probabilities were greater than 0.05). The predicted E. coli concentrations produced by the models were used to develop probabilities that concentrations would exceed the single-sample bathing-water standard for E. coli of 235 colonies per 100 milliliters. Analysis of the exceedence probabilities helped determine a threshold probability for each model, chosen such that the correct number of exceedences and nonexceedences was maximized and the number of false positives and false negatives was minimized. Future samples with computed exceedence probabilities higher than the selected threshold probability, as determined by the model, will likely exceed the E. coli standard and a beach advisory or closing may need to be issued; computed exceedence probabilities lower than the threshold probability will likely indicate the standard will not be exceeded. Additional data collected each year can be used to test and possibly improve the model. This study will aid beach managers in more rapidly determining when waters are not safe for recreational use and, subsequently, when to issue beach advisories or closings.

Predicting emergency department volume using forecasting methods to create a "surge response" for noncrisis events.

PubMed

Chase, Valerie J; Cohn, Amy E M; Peterson, Timothy A; Lavieri, Mariel S

2012-05-01

This study investigated whether emergency department (ED) variables could be used in mathematical models to predict a future surge in ED volume based on recent levels of use of physician capacity. The models may be used to guide decisions related to on-call staffing in non-crisis-related surges of patient volume. A retrospective analysis was conducted using information spanning July 2009 through June 2010 from a large urban teaching hospital with a Level I trauma center. A comparison of significance was used to assess the impact of multiple patient-specific variables on the state of the ED. Physician capacity was modeled based on historical physician treatment capacity and productivity. Binary logistic regression analysis was used to determine the probability that the available physician capacity would be sufficient to treat all patients forecasted to arrive in the next time period. The prediction horizons used were 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 8 hours, and 12 hours. Five consecutive months of patient data from July 2010 through November 2010, similar to the data used to generate the models, was used to validate the models. Positive predictive values, Type I and Type II errors, and real-time accuracy in predicting noncrisis surge events were used to evaluate the forecast accuracy of the models. The ratio of new patients requiring treatment over total physician capacity (termed the care utilization ratio [CUR]) was deemed a robust predictor of the state of the ED (with a CUR greater than 1 indicating that the physician capacity would not be sufficient to treat all patients forecasted to arrive). Prediction intervals of 30 minutes, 8 hours, and 12 hours performed best of all models analyzed, with deviances of 1.000, 0.951, and 0.864, respectively. A 95% significance was used to validate the models against the July 2010 through November 2010 data set. Positive predictive values ranged from 0.738 to 0.872, true positives ranged from 74% to 94%, and true negatives ranged from 70% to 90% depending on the threshold used to determine the state of the ED with the 30-minute prediction model. The CUR is a new and robust indicator of an ED system's performance. The study was able to model the tradeoff of longer time to response versus shorter but more accurate predictions, by investigating different prediction intervals. Current practice would have been improved by using the proposed models and would have identified the surge in patient volume earlier on noncrisis days. © 2012 by the Society for Academic Emergency Medicine.

Predictive Models of the Hydrological Regime of Unregulated Streams in Arizona

USGS Publications Warehouse

Anning, David W.; Parker, John T.C.

2009-01-01

Three statistical models were developed by the U.S. Geological Survey in cooperation with the Arizona Department of Environmental Quality to improve the predictability of flow occurrence in unregulated streams throughout Arizona. The models can be used to predict the probabilities of the hydrological regime being one of four categories developed by this investigation: perennial, which has streamflow year-round; nearly perennial, which has streamflow 90 to 99.9 percent of the year; weakly perennial, which has streamflow 80 to 90 percent of the year; or nonperennial, which has streamflow less than 80 percent of the year. The models were developed to assist the Arizona Department of Environmental Quality in selecting sites for participation in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program. One model was developed for each of the three hydrologic provinces in Arizona - the Plateau Uplands, the Central Highlands, and the Basin and Range Lowlands. The models for predicting the hydrological regime were calibrated using statistical methods and explanatory variables of discharge, drainage-area, altitude, and location data for selected U.S. Geological Survey streamflow-gaging stations and a climate index derived from annual precipitation data. Models were calibrated on the basis of streamflow data from 46 stations for the Plateau Uplands province, 82 stations for the Central Highlands province, and 90 stations for the Basin and Range Lowlands province. The models were developed using classification trees that facilitated the analysis of mixed numeric and factor variables. In all three models, a threshold stream discharge was the initial variable to be considered within the classification tree and was the single most important explanatory variable. If a stream discharge value at a station was below the threshold, then the station record was determined as being nonperennial. If, however, the stream discharge was above the threshold, subsequent decisions were made according to the classification tree and explanatory variables to determine the hydrological regime of the reach as being perennial, nearly perennial, weakly perennial, or nonperennial. Using model calibration data, misclassification rates for each model were 17 percent for the Plateau Uplands, 15 percent for the Central Highlands, and 14 percent for the Basin and Range Lowlands models. The actual misclassification rate may be higher; however, the model has not been field verified for a full error assessment. The calibrated models were used to classify stream reaches for which the Arizona Department of Environmental Quality had collected miscellaneous discharge measurements. A total of 5,080 measurements at 696 sites were routed through the appropriate classification tree to predict the hydrological regime of the reaches in which the measurements were made. The predictions resulted in classification of all stream reaches as perennial or nonperennial; no reaches were predicted as nearly perennial or weakly perennial. The percentages of sites predicted as being perennial and nonperennial, respectively, were 77 and 23 for the Plateau Uplands, 87 and 13 for the Central Highlands, and 76 and 24 for the Basin and Range Lowlands.

Development and internal validation of a side-specific, multiparametric magnetic resonance imaging-based nomogram for the prediction of extracapsular extension of prostate cancer.

PubMed

Martini, Alberto; Gupta, Akriti; Lewis, Sara C; Cumarasamy, Shivaram; Haines, Kenneth G; Briganti, Alberto; Montorsi, Francesco; Tewari, Ashutosh K

2018-04-19

To develop a nomogram for predicting side-specific extracapsular extension (ECE) for planning nerve-sparing radical prostatectomy. We retrospectively analysed data from 561 patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015. To develop a side-specific predictive model, we considered the prostatic lobes separately. Four variables were included: prostate-specific antigen; highest ipsilateral biopsy Gleason grade; highest ipsilateral percentage core involvement; and ECE on multiparametric magnetic resonance imaging (mpMRI). A multivariable logistic regression analysis was fitted to predict side-specific ECE. A nomogram was built based on the coefficients of the logit function. Internal validation was performed using 'leave-one-out' cross-validation. Calibration was graphically investigated. The decision curve analysis was used to evaluate the net clinical benefit. The study population consisted of 829 side-specific cases, after excluding negative biopsy observations (n = 293). ECE was reported on mpMRI and final pathology in 115 (14%) and 142 (17.1%) cases, respectively. Among these, mpMRI was able to predict ECE correctly in 57 (40.1%) cases. All variables in the model except highest percentage core involvement were predictors of ECE (all P ≤ 0.006). All variables were considered for inclusion in the nomogram. After internal validation, the area under the curve was 82.11%. The model demonstrated excellent calibration and improved clinical risk prediction, especially when compared with relying on mpMRI prediction of ECE alone. When retrospectively applying the nomogram-derived probability, using a 20% threshold for performing nerve-sparing, nine out of 14 positive surgical margins (PSMs) at the site of ECE resulted above the threshold. We developed an easy-to-use model for the prediction of side-specific ECE, and hope it serves as a tool for planning nerve-sparing radical prostatectomy and in the reduction of PSM in future series. © 2018 The Authors BJU International © 2018 BJU International Published by John Wiley & Sons Ltd.

Dynamics of chromatic visual system processing differ in complexity between children and adults.

PubMed

Boon, Mei Ying; Suttle, Catherine M; Henry, Bruce I; Dain, Stephen J

2009-06-30

Measures of chromatic contrast sensitivity in children are lower than those of adults. This may be related to immaturities in signal processing at or near threshold. We have found that children's VEPs in response to low contrast supra-threshold chromatic stimuli are more intra-individually variable than those recorded from adults. Here, we report on linear and nonlinear analyses of chromatic VEPs recorded from children and adults. Two measures of signal-to-noise ratio are similar between the adults and children, suggesting that relatively high noise is unlikely to account for the poor clarity of negative and positive peak components in the children's VEPs. Nonlinear analysis indicates higher complexity of adults' than children's chromatic VEPs, at levels of chromatic contrast around and well above threshold.

Can the biomass-ratio hypothesis predict mixed-species litter decomposition along a climatic gradient?

PubMed Central

Tardif, Antoine; Shipley, Bill; Bloor, Juliette M. G.; Soussana, Jean-François

2014-01-01

Background and Aims The biomass-ratio hypothesis states that ecosystem properties are driven by the characteristics of dominant species in the community. In this study, the hypothesis was operationalized as community-weighted means (CWMs) of monoculture values and tested for predicting the decomposition of multispecies litter mixtures along an abiotic gradient in the field. Methods Decomposition rates (mg g−1 d−1) of litter from four herb species were measured using litter-bed experiments with the same soil at three sites in central France along a correlated climatic gradient of temperature and precipitation. All possible combinations from one to four species mixtures were tested over 28 weeks of incubation. Observed mixture decomposition rates were compared with those predicted by the biomass-ratio hypothesis. Variability of the prediction errors was compared with the species richness of the mixtures, across sites, and within sites over time. Key Results Both positive and negative prediction errors occurred. Despite this, the biomass-ratio hypothesis was true as an average claim for all sites (r = 0·91) and for each site separately, except for the climatically intermediate site, which showed mainly synergistic deviations. Variability decreased with increasing species richness and in less favourable climatic conditions for decomposition. Conclusions Community-weighted mean values provided good predictions of mixed-species litter decomposition, converging to the predicted values with increasing species richness and in climates less favourable to decomposition. Under a context of climate change, abiotic variability would be important to take into account when predicting ecosystem processes. PMID:24482152

Development of Thresholds and Exceedance Probabilities for Influent Water Quality to Meet Drinking Water Regulations

NASA Astrophysics Data System (ADS)

Reeves, K. L.; Samson, C.; Summers, R. S.; Balaji, R.

2017-12-01

Drinking water treatment utilities (DWTU) are tasked with the challenge of meeting disinfection and disinfection byproduct (DBP) regulations to provide safe, reliable drinking water under changing climate and land surface characteristics. DBPs form in drinking water when disinfectants, commonly chlorine, react with organic matter as measured by total organic carbon (TOC), and physical removal of pathogen microorganisms are achieved by filtration and monitored by turbidity removal. Turbidity and TOC in influent waters to DWTUs are expected to increase due to variable climate and more frequent fires and droughts. Traditional methods for forecasting turbidity and TOC require catchment specific data (i.e. streamflow) and have difficulties predicting them under non-stationary climate. A modelling framework was developed to assist DWTUs with assessing their risk for future compliance with disinfection and DBP regulations under changing climate. A local polynomial method was developed to predict surface water TOC using climate data collected from NOAA, Normalized Difference Vegetation Index (NDVI) data from the IRI Data Library, and historical TOC data from three DWTUs in diverse geographic locations. Characteristics from the DWTUs were used in the EPA Water Treatment Plant model to determine thresholds for influent TOC that resulted in DBP concentrations within compliance. Lastly, extreme value theory was used to predict probabilities of threshold exceedances under the current climate. Results from the utilities were used to produce a generalized TOC threshold approach that only requires water temperature and bromide concentration. The threshold exceedance model will be used to estimate probabilities of exceedances under projected climate scenarios. Initial results show that TOC can be forecasted using widely available data via statistical methods, where temperature, precipitation, Palmer Drought Severity Index, and NDVI with various lags were shown to be important predictors of TOC, and TOC thresholds can be determined using water temperature and bromide concentration. Results include a model to predict influent turbidity and turbidity thresholds, similar to the TOC models, as well as probabilities of threshold exceedances for TOC and turbidity under changing climate.

Summer temperature metrics for predicting brook trout (Salvelinus fontinalis) distribution in streams

USGS Publications Warehouse

Parrish, Donna; Butryn, Ryan S.; Rizzo, Donna M.

2012-01-01

We developed a methodology to predict brook trout (Salvelinus fontinalis) distribution using summer temperature metrics as predictor variables. Our analysis used long-term fish and hourly water temperature data from the Dog River, Vermont (USA). Commonly used metrics (e.g., mean, maximum, maximum 7-day maximum) tend to smooth the data so information on temperature variation is lost. Therefore, we developed a new set of metrics (called event metrics) to capture temperature variation by describing the frequency, area, duration, and magnitude of events that exceeded a user-defined temperature threshold. We used 16, 18, 20, and 22°C. We built linear discriminant models and tested and compared the event metrics against the commonly used metrics. Correct classification of the observations was 66% with event metrics and 87% with commonly used metrics. However, combined event and commonly used metrics correctly classified 92%. Of the four individual temperature thresholds, it was difficult to assess which threshold had the “best” accuracy. The 16°C threshold had slightly fewer misclassifications; however, the 20°C threshold had the fewest extreme misclassifications. Our method leveraged the volumes of existing long-term data and provided a simple, systematic, and adaptable framework for monitoring changes in fish distribution, specifically in the case of irregular, extreme temperature events.

Novel pre-therapeutic scoring system using patient and haematological data to predict facial palsy prognosis.

PubMed

Wasano, K; Ishikawa, T; Kawasaki, T; Yamamoto, S; Tomisato, S; Shinden, S; Minami, S; Wakabayashi, T; Ogawa, K

2017-12-01

We describe a novel scoring system, the facial Palsy Prognosis Prediction score (PPP score), which we test for reliability in predicting pre-therapeutic prognosis of facial palsy. We aimed to use readily available patient data that all clinicians have access to before starting treatment. Multicenter case series with chart review. Three tertiary care hospitals. We obtained haematological and demographic data from 468 facial palsy patients who were treated between 2010 and 2014 in three tertiary care hospitals. Patients were categorised as having Bell's palsy or Ramsey Hunt's palsy. We compared the data of recovered and unrecovered patients. PPP scores consisted of combinatorial threshold values of continuous patient data (eg platelet count) and categorical variables (eg gender) that best predicted recovery. We created separate PPP scores for Bell's palsy patients (PPP-B) and for Ramsey Hunt's palsy patients (PPP-H). The PPP-B score included age (≥65 years), gender (male) and neutrophil-to-lymphocyte ratio (≥2.9). The PPP-H score included age (≥50 years), monocyte rate (≥6.0%), mean corpuscular volume (≥95 fl) and platelet count (≤200 000 /μL). Patient recovery rate significantly decreased with increasing PPP scores (both PPP-B and PPP-H) in a step-wise manner. PPP scores (ie PPP-B score and PPP-H score) ≥2 were associated with worse than average prognosis. Palsy Prognosis Prediction scores are useful for predicting prognosis of facial palsy before beginning treatment. © 2017 John Wiley & Sons Ltd.

Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

PubMed Central

Melo, Manuel N.; Ferre, Rafael; Feliu, Lídia; Bardají, Eduard; Planas, Marta; Castanho, Miguel A. R. B.

2011-01-01

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations. PMID:22194847

Behavior of motor units in human biceps brachii during a submaximal fatiguing contraction.

PubMed

Garland, S J; Enoka, R M; Serrano, L P; Robinson, G A

1994-06-01

The activity of 50 single motor units was recorded in the biceps brachii muscle of human subjects while they performed submaximal isometric elbow flexion contractions that were sustained to induce fatigue. The purposes of this study were to examine the influence of fatigue on motor unit threshold force and to determine the relationship between the threshold force of recruitment and the initial interimpulse interval on the discharge rates of single motor units during a fatiguing contraction. The discharge rate of most motor units that were active from the beginning of the contraction declined during the fatiguing contraction, whereas the discharge rates of most newly recruited units were either constant or increased slightly. The absolute threshold forces of recruitment and derecruitment decreased, and the variability of interimpulse intervals increased after the fatigue task. The change in motor unit discharge rate during the fatigue task was related to the initial rate, but the direction of the change in discharge rate could not be predicted from the threshold force of recruitment or the variability in the interimpulse intervals. The discharge rate of most motor units declined despite an increase in the excitatory drive to the motoneuron pool during the fatigue task.

The Patient Protection and Affordable Care Act's provisions regarding medical loss ratios and quality: evidence from Texas.

PubMed

Quast, Troy

2013-01-01

The Patient Protection and Affordable Care Act (PPACA) includes a provision that penalizes insurance companies if their Medical Loss Ratio (MLR) falls below a specified threshold. The MLR is roughly measured as the ratio of health care expenses to premiums paid by enrollees. I investigate whether there is a relationship between MLRs and the quality of care provided by insurance companies. I employ a ten-year sample of market-level financial data and quality variables for Texas insurers, as well as relevant control variables, in regression analyses that utilize insurer and market fixed effects. Of the 15 quality measures, only one has a statistically significant relationship with the MLR. For this measure, the relationship is negative. Although the MLR provision may provide incentives for insurance companies to lower premiums, this sample does not suggest that there is likely to be a beneficial effect on quality.

Effects of urbanization on benthic macroinvertebrate communities in streams, Anchorage, Alaska

USGS Publications Warehouse

Ourso, Robert T.

2001-01-01

The effect of urbanization on stream macroinvertebrate communities was examined by using data gathered during a 1999 reconnaissance of 14 sites in the Municipality of Anchorage, Alaska. Data collected included macroinvertebrate abundance, water chemistry, and trace elements in bed sediments. Macroinvertebrate relative-abundance data were edited and used in metric and index calculations. Population density was used as a surrogate for urbanization. Cluster analysis (unweighted-paired-grouping method) using arithmetic means of macroinvertebrate presence-absence data showed a well-defined separation between urbanized and nonurbanized sites as well as extracted sites that did not cleanly fall into either category. Water quality in Anchorage generally declined with increasing urbanization (population density). Of 59 variables examined, 31 correlated with urbanization. Local regression analysis extracted 11 variables that showed a significant impairment threshold response and 6 that showed a significant linear response. Significant biological variables for determining the impairment threshold in this study were the Margalef diversity index, Ephemeroptera-Plecoptera-Trichoptera taxa richness, and total taxa richness. Significant thresholds were observed in the water-chemistry variables conductivity, dissolved organic carbon, potassium, and total dissolved solids. Significant thresholds in trace elements in bed sediments included arsenic, iron, manganese, and lead. Results suggest that sites in Anchorage that have ratios of population density to road density greater than 70, storm-drain densities greater than 0.45 miles per square mile, road densities greater than 4 miles per square mile, or population densities greater than 125-150 persons per square mile may require further monitoring to determine if the stream has become impaired. This population density is far less than the 1,000 persons per square mile used by the U.S. Census Bureau to define an urban area.

Impact of rainfall spatial variability on Flash Flood Forecasting

NASA Astrophysics Data System (ADS)

Douinot, Audrey; Roux, Hélène; Garambois, Pierre-André; Larnier, Kevin

2014-05-01

According to the United States National Hazard Statistics database, flooding and flash flooding have caused the largest number of deaths of any weather-related phenomenon over the last 30 years (Flash Flood Guidance Improvement Team, 2003). Like the storms that cause them, flash floods are very variable and non-linear phenomena in time and space, with the result that understanding and anticipating flash flood genesis is far from straightforward. In the U.S., the Flash Flood Guidance (FFG) estimates the average number of inches of rainfall for given durations required to produce flash flooding in the indicated county. In Europe, flash flood often occurred on small catchments (approximately 100 km2) and it has been shown that the spatial variability of rainfall has a great impact on the catchment response (Le Lay and Saulnier, 2007). Therefore, in this study, based on the Flash flood Guidance method, rainfall spatial variability information is introduced in the threshold estimation. As for FFG, the threshold is the number of millimeters of rainfall required to produce a discharge higher than the discharge corresponding to the first level (yellow) warning of the French flood warning service (SCHAPI: Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations). The indexes δ1 and δ2 of Zoccatelli et al. (2010), based on the spatial moments of catchment rainfall, are used to characterize the rainfall spatial distribution. Rainfall spatial variability impacts on warning threshold and on hydrological processes are then studied. The spatially distributed hydrological model MARINE (Roux et al., 2011), dedicated to flash flood prediction is forced with synthetic rainfall patterns of different spatial distributions. This allows the determination of a warning threshold diagram: knowing the spatial distribution of the rainfall forecast and therefore the 2 indexes δ1 and δ2, the threshold value is read on the diagram. A warning threshold diagram is built for each studied catchment. The proposed methodology is applied on three Mediterranean catchments often submitted to flash floods. The new forecasting method as well as the Flash Flood Guidance method (uniform rainfall threshold) are tested on 25 flash floods events that had occurred on those catchments. Results show a significant impact of rainfall spatial variability. Indeed, it appears that the uniform rainfall threshold (FFG threshold) always overestimates the observed rainfall threshold. The difference between the FFG threshold and the proposed threshold ranges from 8% to 30%. The proposed methodology allows the calculation of a threshold more representative of the observed one. However, results strongly depend on the related event duration and on the catchment properties. For instance, the impact of the rainfall spatial variability seems to be correlated with the catchment size. According to these results, it seems to be interesting to introduce information on the catchment properties in the threshold calculation. Flash Flood Guidance Improvement Team, 2003. River Forecast Center (RFC) Development Management Team. Final Report. Office of Hydrologic Development (OHD), Silver Spring, Mary-land. Le Lay, M. and Saulnier, G.-M., 2007. Exploring the signature of climate and landscape spatial variabilities in flash flood events: Case of the 8-9 September 2002 Cévennes-Vivarais catastrophic event. Geophysical Research Letters, 34(L13401), doi:10.1029/2007GL029746. Roux, H., Labat, D., Garambois, P.-A., Maubourguet, M.-M., Chorda, J. and Dartus, D., 2011. A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments. Nat. Hazards Earth Syst. Sci. J1 - NHESS, 11(9), 2567-2582. Zoccatelli, D., Borga, M., Zanon, F., Antonescu, B. and Stancalie, G., 2010. Which rainfall spatial information for flash flood response modelling? A numerical investigation based on data from the Carpathian range, Romania. Journal of Hydrology, 394(1-2), 148-161.

Simplified 4-item criteria for polycystic ovary syndrome: A bridge too far?

PubMed

Indran, Inthrani R; Huang, Zhongwei; Khin, Lay Wai; Chan, Jerry K Y; Viardot-Foucault, Veronique; Yong, Eu Leong

2018-05-30

Although the Rotterdam 2003 polycystic ovarian syndrome (PCOS) diagnostic criteria is widely used, the need to consider multiple variables makes it unwieldy in clinical practice. We propose a simplified PCOS criteria wherein diagnosis is made if two of the following three items were present: (i) oligomenorrhoea, (ii) anti-mullerian hormone (AMH) above threshold and/or (iii) hyperandrogenism defined as either testosterone above threshold and/or the presence of hirsutism. This prospective cross-sectional study consists of healthy women (n = 157) recruited at an annual hospital health screen for staff and volunteers from the university community, and a patient cohort (n = 174) comprising women referred for suspected PCOS. We used the healthy cohort to establish threshold values for serum testosterone, antral follicle counts (AFC), ovarian volume (OV) and AMH. Women from the patient cohort, classified as PCOS by simplified PCOS criteria, AMH alone and Rotterdam 2003, were compared with respect to prevalence of oligomenorrhoea, hyperandrogenism and metabolic indices. In healthy women, testosterone ≥1.89 nmol/L, AFC ≥22 follicles and OV ≥8.44 mL, best predicted oligomenorrhoea and were used as threshold values for PCOS criteria. An AMH level ≥37.0 pmol/L best predicted polycystic ovarian morphology. AMH alone as a single biomarker demonstrated poor specificity (58.9%) for PCOS compared to Rotterdam 2003. In contrast, there was a 94% overlap in women selected as PCOS by the simplified PCOS criteria and Rotterdam 2003. The population characteristics of these two groups of PCOS women showed no significant mean differences in androgenic, ovarian, AMH and metabolic (BMI, HOMA-IR) variables. Our data recommend the simplified PCOS criteria with population-specific thresholds for diagnosis of PCOS. Its ability to replace ovarian ultrasound biometry with the highly correlated variable AMH, and use of testosterone as a single marker for hyperandrogenaemia alongside the key symptoms of oligomenorrhoea and hirsutism confers significant clinical potential for the diagnosis of PCOS. © 2018 John Wiley & Sons Ltd.

Variable-Threshold Threshold Elements,

DTIC Science & Technology

A threshold element is a mathematical model of certain types of logic gates and of a biological neuron. Much work has been done on the subject of... threshold elements with fixed thresholds; this study concerns itself with elements in which the threshold may be varied, variable- threshold threshold ...elements. Physical realizations include resistor-transistor elements, in which the threshold is simply a voltage. Variation of the threshold causes the

Emergency department blood transfusion: the first two units are free.

PubMed

Ley, Eric J; Liou, Douglas Z; Singer, Matthew B; Mirocha, James; Melo, Nicolas; Chung, Rex; Bukur, Marko; Salim, Ali

2013-09-01

Studies on blood product transfusions after trauma recommend targeting specific ratios to reduce mortality. Although crystalloid volumes as little as 1.5 L predict increased mortality after trauma, little data is available regarding the threshold of red blood cell (RBC) transfusion volume that predicts increased mortality. Data from a level I trauma center between January 2000 and December 2008 were reviewed. Trauma patients who received at least 100 mL RBC in the emergency department (ED) were included. Each unit of RBC was defined as 300 mL. Demographics, RBC transfusion volume, and mortality were analyzed in the nonelderly (<70 y) and elderly (≥70 y). Multivariate logistic regression was performed at various volume cutoffs to determine whether there was a threshold transfusion volume that independently predicted mortality. A total of 560 patients received ≥100 mL RBC in the ED. Overall mortality was 24.3%, with 22.5% (104 deaths) in the nonelderly and 32.7% (32 deaths) in the elderly. Multivariate logistic regression demonstrated that RBC transfusion of ≥900 mL was associated with increased mortality in both the nonelderly (adjusted odds ratio 2.06, P = 0.008) and elderly (adjusted odds ratio 5.08, P = 0.006). Although transfusion of greater than 2 units in the ED was an independent predictor of mortality, transfusion of 2 units or less was not. Interestingly, unlike crystalloid volume, stepwise increases in blood volume were not associated with stepwise increases in mortality. The underlying etiology for mortality discrepancies, such as transfusion ratios, hypothermia, or immunosuppression, needs to be better delineated. Copyright © 2013 Elsevier Inc. All rights reserved.

The impact of aging, hearing loss, and body weight on mouse hippocampal redox state, measured in brain slices using fluorescence imaging.

PubMed

Stebbings, Kevin A; Choi, Hyun W; Ravindra, Aditya; Llano, Daniel Adolfo

2016-06-01

The relationships between oxidative stress in the hippocampus and other aging-related changes such as hearing loss, cortical thinning, or changes in body weight are not yet known. We measured the redox ratio in a number of neural structures in brain slices taken from young and aged mice. Hearing thresholds, body weight, and cortical thickness were also measured. We found striking aging-related increases in the redox ratio that were isolated to the stratum pyramidale, while such changes were not observed in thalamus or cortex. These changes were driven primarily by changes in flavin adenine dinucleotide, not nicotinamide adenine dinucleotide hydride. Multiple regression analysis suggested that neither hearing threshold nor cortical thickness independently contributed to this change in hippocampal redox ratio. However, body weight did independently contribute to predicted changes in hippocampal redox ratio. These data suggest that aging-related changes in hippocampal redox ratio are not a general reflection of overall brain oxidative state but are highly localized, while still being related to at least one marker of late aging, weight loss at the end of life. Copyright © 2016 Elsevier Inc. All rights reserved.

Is the Critical Shields Stress for Incipient Sediment Motion Dependent on Bed Slope in Natural Channels? No.

NASA Astrophysics Data System (ADS)

Phillips, C. B.; Jerolmack, D. J.

2017-12-01

Understanding when coarse sediment begins to move in a river is essential for linking rivers to the evolution of mountainous landscapes. Unfortunately, the threshold of surface particle motion is notoriously difficult to measure in the field. However, recent studies have shown that the threshold of surface motion is empirically correlated with channel slope, a property that is easy to measure and readily available from the literature. These studies have thoroughly examined the mechanistic underpinnings behind the observed correlation and produced suitably complex models. These models are difficult to implement for natural rivers using widely available data, and thus others have treated the empirical regression between slope and the threshold of motion as a predictive model. We note that none of the authors of the original studies exploring this correlation suggested their empirical regressions be used in a predictive fashion, nevertheless these regressions between slope and the threshold of motion have found their way into numerous recent studies engendering potentially spurious conclusions. We demonstrate that there are two significant problems with using these empirical equations for prediction: (1) the empirical regressions are based on a limited sampling of the phase space of bed-load rivers and (2) the empirical measurements of bankfull and critical shear stresses are paired. The upshot of these problems limits the empirical relations predictive capacity to field sites drawn from the same region of the bed-load river phase space and that the paired nature of the data introduces a spurious correlation when considering the ratio of bankfull to critical shear stress. Using a large compilation of bed-load river hydraulic geometry data, we demonstrate that the variation within independently measured values of the threshold of motion changes systematically with bankfull shields stress and not channel slope. Additionally, we highlight using several recent datasets the potential pitfalls that one can encounter when using simplistic empirical regressions to predict the threshold of motion showing that while these concerns could be construed as subtle the resulting implications can be substantial.

Accuracy of topographic index models at identifying ephemeral gully trajectories on agricultural fields

NASA Astrophysics Data System (ADS)

Sheshukov, Aleksey Y.; Sekaluvu, Lawrence; Hutchinson, Stacy L.

2018-04-01

Topographic index (TI) models have been widely used to predict trajectories and initiation points of ephemeral gullies (EGs) in agricultural landscapes. Prediction of EGs strongly relies on the selected value of critical TI threshold, and the accuracy depends on topographic features, agricultural management, and datasets of observed EGs. This study statistically evaluated the predictions by TI models in two paired watersheds in Central Kansas that had different levels of structural disturbances due to implemented conservation practices. Four TI models with sole dependency on topographic factors of slope, contributing area, and planform curvature were used in this study. The observed EGs were obtained by field reconnaissance and through the process of hydrological reconditioning of digital elevation models (DEMs). The Kernel Density Estimation analysis was used to evaluate TI distribution within a 10-m buffer of the observed EG trajectories. The EG occurrence within catchments was analyzed using kappa statistics of the error matrix approach, while the lengths of predicted EGs were compared with the observed dataset using the Nash-Sutcliffe Efficiency (NSE) statistics. The TI frequency analysis produced bi-modal distribution of topographic indexes with the pixels within the EG trajectory having a higher peak. The graphs of kappa and NSE versus critical TI threshold showed similar profile for all four TI models and both watersheds with the maximum value representing the best comparison with the observed data. The Compound Topographic Index (CTI) model presented the overall best accuracy with NSE of 0.55 and kappa of 0.32. The statistics for the disturbed watershed showed higher best critical TI threshold values than for the undisturbed watershed. Structural conservation practices implemented in the disturbed watershed reduced ephemeral channels in headwater catchments, thus producing less variability in catchments with EGs. The variation in critical thresholds for all TI models suggested that TI models tend to predict EG occurrence and length over a range of thresholds rather than find a single best value.

Prevalence and prediction of exercise-induced oxygen desaturation in patients with chronic obstructive pulmonary disease.

PubMed

van Gestel, A J R; Clarenbach, C F; Stöwhas, A C; Teschler, S; Russi, E W; Teschler, H; Kohler, M

2012-01-01

Previous studies with small sample sizes reported contradicting findings as to whether pulmonary function tests can predict exercise-induced oxygen desaturation (EID). To evaluate whether forced expiratory volume in one second (FEV(1)), resting oxygen saturation (SpO(2)) and diffusion capacity for carbon monoxide (DLCO) are predictors of EID in chronic obstructive pulmonary disease (COPD). We measured FEV(1), DLCO, SpO(2) at rest and during a 6-min walking test as well as physical activity by an accelerometer. A drop in SpO(2) of >4 to <90% was defined as EID. To evaluate associations between measures of lung function and EID univariate and multivariate analyses were used and positive/negative predictive values were calculated. Receiver operating characteristic curve analysis was performed to determine the most useful threshold in order to predict/exclude EID. We included 154 patients with COPD (87 females). The mean FEV(1) was 43.0% (19.2) predicted and the prevalence of EID was 61.7%. The only independent predictor of EID was FEV(1) and the optimal cutoff value of FEV(1) was at 50% predicted (area under ROC curve, 0.85; p < 0.001). The positive predictive value of a threshold of FEV(1) <50% was 0.83 with a likelihood ratio of 3.03 and the negative predicting value of a threshold of FEV(1) ≥80% was 1.0. The severity of EID was correlated with daily physical activity (r = -0.31, p = 0.008). EID is highly prevalent among patients with COPD and can be predicted by FEV(1). EID seems to be associated with impaired daily physical activity which supports its clinical importance. Copyright © 2012 S. Karger AG, Basel.

Baseline Tumor Lipiodol Uptake after Transarterial Chemoembolization for Hepatocellular Carcinoma: Identification of a Threshold Value Predicting Tumor Recurrence.

PubMed

Matsui, Yusuke; Horikawa, Masahiro; Jahangiri Noudeh, Younes; Kaufman, John A; Kolbeck, Kenneth J; Farsad, Khashayar

2017-12-01

The aim of the study was to evaluate the association between baseline Lipiodol uptake in hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE) with early tumor recurrence, and to identify a threshold baseline uptake value predicting tumor response. A single-institution retrospective database of HCC treated with Lipiodol-TACE was reviewed. Forty-six tumors in 30 patients treated with a Lipiodol-chemotherapy emulsion and no additional particle embolization were included. Baseline Lipiodol uptake was measured as the mean Hounsfield units (HU) on a CT within one week after TACE. Washout rate was calculated dividing the difference in HU between the baseline CT and follow-up CT by time (HU/month). Cox proportional hazard models were used to correlate baseline Lipiodol uptake and other variables with tumor response. A receiver operating characteristic (ROC) curve was used to identify the optimal threshold for baseline Lipiodol uptake predicting tumor response. During the follow-up period (mean 5.6 months), 19 (41.3%) tumors recurred (mean time to recurrence = 3.6 months). In a multivariate model, low baseline Lipiodol uptake and higher washout rate were significant predictors of early tumor recurrence ( P = 0.001 and < 0.0001, respectively). On ROC analysis, a threshold Lipiodol uptake of 270.2 HU was significantly associated with tumor response (95% sensitivity, 93% specificity). Baseline Lipiodol uptake and washout rate on follow-up were independent predictors of early tumor recurrence. A threshold value of baseline Lipiodol uptake > 270.2 HU was highly sensitive and specific for tumor response. These findings may prove useful for determining subsequent treatment strategies after Lipiodol TACE.

The Biological and Toxicological Activity of Gases and Vapors

PubMed Central

Sánchez-Moreno, Ricardo; Gil-Lostes, Javier; Acree, William E.; Cometto-Muñiz, J. Enrique; Cain, William S.

2010-01-01

A large amount of data on the biological and toxicological activity of gases and vapors has been collected from the literature. Processes include sensory irritation thresholds, the Alarie mouse test, inhalation anesthesia, etc. It is shown that a single equation using only five descriptors (properties of the gases and vapors) plus a set of indicator variables for the given processes can correlate 643 biological and non-lethal toxicological activities of ‘non-reactive’ compounds with a standard deviation of 0.36 log unit. The equation is scaled to sensory irritation thresholds obtained by the procedure of Cometto-Muñiz, and Cain, and provides a general equation for the prediction of sensory irritation thresholds in man. It is suggested that differences in biological/toxicological activity arise primarily from transport from the gas phase to a receptor phase or area, except for odor detection thresholds where interaction with a receptor(s) is important. PMID:19913608

Precipitation phase partitioning variability across the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Jennings, K. S.; Winchell, T. S.; Livneh, B.; Molotch, N. P.

2017-12-01

Precipitation phase drives myriad hydrologic, climatic, and biogeochemical processes. Despite its importance, many of the land surface models used to simulate such processes and their sensitivity to climate warming rely on simple, spatially uniform air temperature thresholds to partition rainfall and snowfall. Our analysis of a 29-year dataset with 18.7 million observations of precipitation phase from 12,143 stations across the Northern Hemisphere land surface showed marked spatial variability in the near-surface air temperature at which precipitation is equally likely to fall as rain and snow, the 50% rain-snow threshold. This value averaged 1.0°C and ranged from -0.4°C to 2.4°C for 95% of the stations analyzed. High-elevation continental areas such as the Rocky Mountains of the western U.S. and the Tibetan Plateau of central Asia generally exhibited the warmest thresholds, in some cases exceeding 3.0°C. Conversely, the coldest thresholds were observed on the Pacific Coast of North America, the southeast U.S., and parts of Eurasia, with values dropping below -0.5°C. Analysis of the meteorological conditions during storm events showed relative humidity exerted the strongest control on phase partitioning, with surface pressure playing a secondary role. Lower relative humidity and surface pressure were both associated with warmer 50% rain-snow thresholds. Additionally, we trained a binary logistic regression model on the observations to classify rain and snow events and found including relative humidity as a predictor variable significantly increased model performance between 0.6°C and 3.8°C when phase partitioning is most uncertain. We then used the optimized model and a spatially continuous reanalysis product to map the 50% rain-snow threshold across the Northern Hemisphere. The map reproduced patterns in the observed thresholds with a mean bias of 0.5°C relative to the station data. The above results suggest land surface models could be improved by incorporating relative humidity into their precipitation phase prediction schemes or by using a spatially variable, optimized rain-snow temperature threshold. This is particularly important for climate warming simulations where misdiagnosing a shift from snow to rain or inaccurately quantifying snowfall fraction would likely lead to biased results.

How to interpret a small increase in AUC with an additional risk prediction marker: decision analysis comes through.

PubMed

Baker, Stuart G; Schuit, Ewoud; Steyerberg, Ewout W; Pencina, Michael J; Vickers, Andrew; Vickers, Andew; Moons, Karel G M; Mol, Ben W J; Lindeman, Karen S

2014-09-28

An important question in the evaluation of an additional risk prediction marker is how to interpret a small increase in the area under the receiver operating characteristic curve (AUC). Many researchers believe that a change in AUC is a poor metric because it increases only slightly with the addition of a marker with a large odds ratio. Because it is not possible on purely statistical grounds to choose between the odds ratio and AUC, we invoke decision analysis, which incorporates costs and benefits. For example, a timely estimate of the risk of later non-elective operative delivery can help a woman in labor decide if she wants an early elective cesarean section to avoid greater complications from possible later non-elective operative delivery. A basic risk prediction model for later non-elective operative delivery involves only antepartum markers. Because adding intrapartum markers to this risk prediction model increases AUC by 0.02, we questioned whether this small improvement is worthwhile. A key decision-analytic quantity is the risk threshold, here the risk of later non-elective operative delivery at which a patient would be indifferent between an early elective cesarean section and usual care. For a range of risk thresholds, we found that an increase in the net benefit of risk prediction requires collecting intrapartum marker data on 68 to 124 women for every correct prediction of later non-elective operative delivery. Because data collection is non-invasive, this test tradeoff of 68 to 124 is clinically acceptable, indicating the value of adding intrapartum markers to the risk prediction model. Copyright © 2014 John Wiley & Sons, Ltd.

Four hundred or more participants needed for stable contingency table estimates of clinical prediction rule performance.

PubMed

Kent, Peter; Boyle, Eleanor; Keating, Jennifer L; Albert, Hanne B; Hartvigsen, Jan

2017-02-01

To quantify variability in the results of statistical analyses based on contingency tables and discuss the implications for the choice of sample size for studies that derive clinical prediction rules. An analysis of three pre-existing sets of large cohort data (n = 4,062-8,674) was performed. In each data set, repeated random sampling of various sample sizes, from n = 100 up to n = 2,000, was performed 100 times at each sample size and the variability in estimates of sensitivity, specificity, positive and negative likelihood ratios, posttest probabilities, odds ratios, and risk/prevalence ratios for each sample size was calculated. There were very wide, and statistically significant, differences in estimates derived from contingency tables from the same data set when calculated in sample sizes below 400 people, and typically, this variability stabilized in samples of 400-600 people. Although estimates of prevalence also varied significantly in samples below 600 people, that relationship only explains a small component of the variability in these statistical parameters. To reduce sample-specific variability, contingency tables should consist of 400 participants or more when used to derive clinical prediction rules or test their performance. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation of the stability indices for the thunderstorm forecasting in the region of Belgrade, Serbia

NASA Astrophysics Data System (ADS)

Vujović, D.; Paskota, M.; Todorović, N.; Vučković, V.

2015-07-01

The pre-convective atmosphere over Serbia during the ten-year period (2001-2010) was investigated using the radiosonde data from one meteorological station and the thunderstorm observations from thirteen SYNOP meteorological stations. In order to verify their ability to forecast a thunderstorm, several stability indices were examined. Rank sum scores (RSSs) were used to segregate indices and parameters which can differentiate between a thunderstorm and no-thunderstorm event. The following indices had the best RSS values: Lifted index (LI), K index (KI), Showalter index (SI), Boyden index (BI), Total totals (TT), dew-point temperature and mixing ratio. The threshold value test was used in order to determine the appropriate threshold values for these variables. The threshold with the best skill scores was chosen as the optimal. The thresholds were validated in two ways: through the control data set, and comparing the calculated indices thresholds with the values of indices for a randomly chosen day with an observed thunderstorm. The index with the highest skill for thunderstorm forecasting was LI, and then SI, KI and TT. The BI had the poorest skill scores.

Investigation of quartz diagenesis in mudstones of the Spraberry and Wolfcamp Formations

NASA Astrophysics Data System (ADS)

Eakin, A.; Reece, J. S.

2016-12-01

Here we present preliminary core analysis of the diagenetic variability existing within a siliceous mudstone facies of the Permian Spraberry and Wolfcamp Formations in the Midland Basin, Texas. Within this mudstone facies, the carbonate content varies from absent in several Wolfcamp Formation samples to >40 wt. % in the Spraberry Formation. A normalized ratio of quartz to clay content with carbonate removed reveals a systematic decrease in quartz content with increasing clay content. This relationship is typical of rocks with variable amounts of detrital quartz content. However, in this siliceous mudstone facies, the abundance of detrital quartz silt grains does not vary widely. Additionally, for the same clay content, the Wolfcamp Formation shows a higher concentration of quartz than the Spraberry Formation. Scanning electron microscopy (SEM) reveals the presence of microcrystalline quartz cement that likely accounts for the increased quartz content in the Wolfcamp Formation. This research tests the hypothesis that the increased quartz cement in the Wolfcamp Formation may occur at the expense of the carbonate cement present in the overlying Spraberry Formation. Furthermore, the deviation in quartz content for the same clay concentration only occurs once the ratio of quartz to clay content increases beyond 1.2. This ratio may represent a threshold of detrital quartz in the clay matrix required to have enough porosity and nucleation surface area for authigenic quartz growth. The presence of matrix cement may impact the mechanical properties to favor fracturing and cataclasis over more ductile deformation. This would enhance development of secondary porosity, while also increasing permeability through the connection of primary pores. Acquiring a fundamental understanding of diagenesis in the Spraberry and Wolfcamp Formations will aid in better prediction of mechanical behavior during drilling and optimized resource recovery.

Numerical investigation of the inertial cavitation threshold by dual-frequency excitation in the fluid and tissue.

PubMed

Wang, Mingjun; Zhou, Yufeng

2018-04-01

Inertial cavitation thresholds, which are defined as bubble growth by 2-fold from the equilibrium radius, by two types of ultrasonic excitation (at the classical single-frequency mode and dual-frequency mode) were calculated. The effect of the dual-frequency excitation on the inertial cavitation threshold in the different surrounding media (fluid and tissue) was studied, and the paramount parameters (driving frequency, amplitude ratio, phase difference, and frequency ratio) were also optimized to maximize the inertial cavitation. The numerical prediction confirms the previous experimental results that the dual-frequency excitation is capable of reducing the inertial cavitation threshold in comparison to the single-frequency one at the same output power. The dual-frequency excitation at the high frequency (i.e., 3.1 + 3.5 MHz vs. 1.1 + 1.3 MHz) is preferred in this study. The simulation results suggest that the same amplitudes of individual components, zero phase difference, and large frequency difference are beneficial for enhancing the bubble cavitation. Overall, this work may provide a theoretical model for further investigation of dual-frequency excitation and guidance of its applications for a better outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Pre-operative Thresholds for Achieving Meaningful Clinical Improvement after Arthroscopic Treatment of Femoroacetabular Impingement

PubMed Central

Nwachukwu, Benedict U.; Fields, Kara G.; Nawabi, Danyal H.; Kelly, Bryan T.; Ranawat, Anil S.

2016-01-01

Objectives: Knowledge of the thresholds and determinants for successful femoroacetabular impingement (FAI) treatment is evolving. The primary purpose of this study was to define pre-operative outcome score thresholds that can be used to predict patients most likely to achieve meaningful clinically important difference (MCID) after arthroscopic FAI treatment. Secondarily determinants of achieving MCID were evaluated. Methods: A prospective institutional hip arthroscopy registry was reviewed to identify patients with FAI treated with arthroscopic labral surgery, acetabular rim trimming, and femoral osteochondroplasty. The modified Harris Hip Score (mHHS), the Hip Outcome Score (HOS) and the international Hip Outcome Tool (iHOT-33) tools were administered at baseline and at one year post-operatively. MCID was calculated using a distribution-based method. A receiver operating characteristic (ROC) analysis was used to calculate cohort-based threshold values predictive of achieving MCID. Area under the curve (AUC) was used to define predictive ability (strength of association) with AUC >0.7 considered acceptably predictive. Univariate and multivariable analyses were used to analyze demographic, radiographic and intra-operative factors associated with achieving MCID. Results: There were 374 patients (mean + SD age, 32.9 + 10.5) and 56.4% were female. The MCID for mHHS, HOS activities of daily living (HOS-ADL), HOS Sports, and iHOT-33 was 8.2, 8.4,14.5, and 12.0 respectively. ROC analysis (threshold, % achieving MCID, strength of association) for these tools in our population was: mHHS (61.6, 78%, 0.68), HOS-ADL (83.8, 68%, 0.84), HOS-Sports (63.9, 64%, 0.74), and iHOT-33 (54.3, 82%, 0.65). Likelihood for achieving MCID declined above and increased below these thresholds. In univariate analysis female sex, femoral version, lower acetabular outerbridge score and increasing CT sagittal center edge angle (CEA) were predictive of achieving MCID. In multivariable analysis sagittal CEA was the only variable maintaining significance (p = 0.032). Conclusion: We used a large prospective hip arthroscopy database to identify pre-operative patient outcome score thresholds predictive of meaningful post-operative outcome improvement after arthroscopic FAI treatment. This is the largest reported hip arthroscopy cohort to define MCID and the first to do so for iHOT-33. The HOS-ADL may have the best predictive ability for achieving MCID after hip arthroscopy. Patients with relatively high pre-operative ADL, quality of life and functional status appear to have a high chance for achieveing MCID up to our defined thresholds. Hip dysplasia is an important outcome modifier. The findings of this study may be useful for managing preoperative expectation for patients undergoing arthroscopic FAI surgery.

Computed Tomography Aortic Valve Calcium Scoring in Patients With Aortic Stenosis.

PubMed

Pawade, Tania; Clavel, Marie-Annick; Tribouilloy, Christophe; Dreyfus, Julien; Mathieu, Tiffany; Tastet, Lionel; Renard, Cedric; Gun, Mesut; Jenkins, William Steven Arthur; Macron, Laurent; Sechrist, Jacob W; Lacomis, Joan M; Nguyen, Virginia; Galian Gay, Laura; Cuéllar Calabria, Hug; Ntalas, Ioannis; Cartlidge, Timothy Robert Graham; Prendergast, Bernard; Rajani, Ronak; Evangelista, Arturo; Cavalcante, João L; Newby, David E; Pibarot, Philippe; Messika Zeitoun, David; Dweck, Marc R

2018-03-01

Computed tomography aortic valve calcium scoring (CT-AVC) holds promise for the assessment of patients with aortic stenosis (AS). We sought to establish the clinical utility of CT-AVC in an international multicenter cohort of patients. Patients with AS who underwent ECG-gated CT-AVC within 3 months of echocardiography were entered into an international, multicenter, observational registry. Optimal CT-AVC thresholds for diagnosing severe AS were determined in patients with concordant echocardiographic assessments, before being used to arbitrate disease severity in those with discordant measurements. In patients with long-term follow-up, we assessed whether CT-AVC thresholds predicted aortic valve replacement and death. In 918 patients from 8 centers (age, 77±10 years; 60% men; peak velocity, 3.88±0.90 m/s), 708 (77%) patients had concordant echocardiographic assessments, in whom CT-AVC provided excellent discrimination for severe AS (C statistic: women 0.92, men 0.89). Our optimal sex-specific CT-AVC thresholds (women 1377 Agatston unit and men 2062 Agatston unit) were nearly identical to those previously reported (women 1274 Agatston unit and men 2065 Agatston unit). Clinical outcomes were available in 215 patients (follow-up 1029 [126-2251] days). Sex-specific CT-AVC thresholds independently predicted aortic valve replacement and death (hazard ratio, 3.90 [95% confidence interval, 2.19-6.78]; P <0.001) after adjustment for age, sex, peak velocity, and aortic valve area. Among 210 (23%) patients with discordant echocardiographic assessments, there was considerable heterogeneity in CT-AVC scores, which again were an independent predictor of clinical outcomes (hazard ratio, 3.67 [95% confidence interval, 1.39-9.73]; P =0.010). Sex-specific CT-AVC thresholds accurately identify severe AS and provide powerful prognostic information. These findings support their integration into routine clinical practice. URL: http://www.clinicaltrials.gov. Unique identifiers: NCT01358513, NCT02132026, NCT00338676, NCT00647088, NCT01679431. © 2018 American Heart Association, Inc.

Evaluation of NO2 predictions by the plume volume molar ratio method (PVMRM) and ozone limiting method (OLM) in AERMOD using new field observations.

PubMed

Hendrick, Elizabeth M; Tino, Vincent R; Hanna, Steven R; Egan, Bruce A

2013-07-01

The U.S. Environmental Protection Agency (EPA) plume volume molar ratio method (PVMRM) and the ozone limiting method (OLM) are in the AERMOD model to predict the 1-hr average NO2/NO(x) concentration ratio. These ratios are multiplied by the AERMOD predicted NO(x) concentration to predict the 1-hr average NO2 concentration. This paper first briefly reviews PVMRM and OLM and points out some scientific parameterizations that could be improved (such as specification of relative dispersion coefficients) and then discusses an evaluation of the PVMRM and OLM methods as implemented in AERMOD using a new data set. While AERMOD has undergone many model evaluation studies in its default mode, PVMRM and OLM are nondefault options, and to date only three NO2 field data sets have been used in their evaluations. Here AERMOD/PVMRM and AERMOD/OLM codes are evaluated with a new data set from a northern Alaskan village with a small power plant. Hourly pollutant concentrations (NO, NO2, ozone) as well as meteorological variables were measured at a single monitor 500 m from the plant. Power plant operating parameters and emissions were calculated based on hourly operator logs. Hourly observations covering 1 yr were considered, but the evaluations only used hours when the wind was in a 60 degrees sector including the monitor and when concentrations were above a threshold. PVMRM is found to have little bias in predictions of the C(NO2)/C(NO(x)) ratio, which mostly ranged from 0.2 to 0.4 at this site. OLM overpredicted the ratio. AERMOD overpredicts the maximum NO(x) concentration but has an underprediction bias for lower concentrations. AERMOD/PVMRM overpredicts the maximum C(NO2) by about 50%, while AERMOD/OLM overpredicts by a factor of 2. For 381 hours evaluated, there is a relative mean bias in C(NO2) predictions of near zero for AERMOD/PVMRM, while the relative mean bias reflects a factor of 2 overprediction for AERMOD/OLM. This study was initiated because the new stringent 1-hr NO2 NAAQS has prompted modelers to more widely use the PVMRM and OLM methods for conversion of NO(x) to NO2 in the AERMOD regulatory model. To date these methods have been evaluated with a limited number of data sets. This study identified a new data set of ambient pollutant and meteorological monitoring near an isolated power plant in Wainwright, Alaska. To supplement the existing evaluations, this new data were used to evaluate PVMRM and OLM. This new data set has been and will be made available to other scientists for future investigations.

Using instrumental (CIE and reflectance) measures to predict consumers' acceptance of beef colour.

PubMed

Holman, Benjamin W B; van de Ven, Remy J; Mao, Yanwei; Coombs, Cassius E O; Hopkins, David L

2017-05-01

We aimed to establish colorimetric thresholds based upon the capacity for instrumental measures to predict consumer satisfaction with beef colour. A web-based survey was used to distribute standardised photographs of beef M. longissimus lumborum with known colorimetrics (L*, a*, b*, hue, chroma, ratio of reflectance at 630nm and 580nm, and estimated deoxymyoglobin, oxymyoglobin and metmyoglobin concentrations) for scrutiny. Consumer demographics and perceived importance of colour to beef value were also evaluated. It was found that a* provided the most simple and robust prediction of beef colour acceptability. Beef colour was considered acceptable (with 95% acceptance) when a* values were equal to or above 14.5. Demographic effects on this threshold were negligible, but consumer nationality and gender did contribute to variation in the relative importance of colour to beef value. These results provide future beef colour studies with context to interpret objective colour measures in terms of consumer acceptance and market appeal. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable.

PubMed

Austin, Peter C; Steyerberg, Ewout W

2012-06-20

When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population.

Predictive Variables of Half-Marathon Performance for Male Runners

PubMed Central

Gómez-Molina, Josué; Ogueta-Alday, Ana; Camara, Jesus; Stickley, Christoper; Rodríguez-Marroyo, José A.; García-López, Juan

2017-01-01

The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48) was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30) to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO2max, speed at the anaerobic threshold, peak speed) and biomechanical variables (contact and flight times, step length and step rate) were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1), 94.9% by physiological variables (Equation 2), 93.7% by biomechanical parameters (Equation 3) and 96.2% by a general equation (Equation 4). Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively). The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance. Key points The present study obtained four equations involving anthropometric, training, physiological and biomechanical variables to estimate half-marathon performance. These equations were validated in a different population, demonstrating narrows ranges of prediction than previous studies and also their consistency. As a novelty, some biomechanical variables (i.e. step length and step rate at RCT, and maximal step length) have been related to half-marathon performance. PMID:28630571

Speckle Noise Reduction in Optical Coherence Tomography Using Two-dimensional Curvelet-based Dictionary Learning.

PubMed

Esmaeili, Mahdad; Dehnavi, Alireza Mehri; Rabbani, Hossein; Hajizadeh, Fedra

2017-01-01

The process of interpretation of high-speed optical coherence tomography (OCT) images is restricted due to the large speckle noise. To address this problem, this paper proposes a new method using two-dimensional (2D) curvelet-based K-SVD algorithm for speckle noise reduction and contrast enhancement of intra-retinal layers of 2D spectral-domain OCT images. For this purpose, we take curvelet transform of the noisy image. In the next step, noisy sub-bands of different scales and rotations are separately thresholded with an adaptive data-driven thresholding method, then, each thresholded sub-band is denoised based on K-SVD dictionary learning with a variable size initial dictionary dependent on the size of curvelet coefficients' matrix in each sub-band. We also modify each coefficient matrix to enhance intra-retinal layers, with noise suppression at the same time. We demonstrate the ability of the proposed algorithm in speckle noise reduction of 100 publically available OCT B-scans with and without non-neovascular age-related macular degeneration (AMD), and improvement of contrast-to-noise ratio from 1.27 to 5.12 and mean-to-standard deviation ratio from 3.20 to 14.41 are obtained.

Between-airport heterogeneity in air toxics emissions associated with individual cancer risk thresholds and population risks

PubMed Central

2009-01-01

Background Airports represent a complex source type of increasing importance contributing to air toxics risks. Comprehensive atmospheric dispersion models are beyond the scope of many applications, so it would be valuable to rapidly but accurately characterize the risk-relevant exposure implications of emissions at an airport. Methods In this study, we apply a high resolution atmospheric dispersion model (AERMOD) to 32 airports across the United States, focusing on benzene, 1,3-butadiene, and benzo [a]pyrene. We estimate the emission rates required at these airports to exceed a 10-6 lifetime cancer risk for the maximally exposed individual (emission thresholds) and estimate the total population risk at these emission rates. Results The emission thresholds vary by two orders of magnitude across airports, with variability predicted by proximity of populations to the airport and mixing height (R2 = 0.74–0.75 across pollutants). At these emission thresholds, the population risk within 50 km of the airport varies by two orders of magnitude across airports, driven by substantial heterogeneity in total population exposure per unit emissions that is related to population density and uncorrelated with emission thresholds. Conclusion Our findings indicate that site characteristics can be used to accurately predict maximum individual risk and total population risk at a given level of emissions, but that optimizing on one endpoint will be non-optimal for the other. PMID:19426510

Proton MR spectroscopy in predicting the increase of perfusion MR imaging for WHO grade II gliomas.

PubMed

Guillevin, Remy; Menuel, Carole; Abud, Lucas; Costalat, Robert; Capelle, Laurent; Hoang-Xuan, Khê; Habas, Christophe; Chiras, Jacques; Vallée, Jean-Noel

2012-03-01

To investigate the correlation between the metabolite ratios obtained from proton magnetic resonance (MR) spectroscopy and those obtained from MR perfusion parameters (relative cerebral blood volume [rCBV]) in a cohort of low-grade glioma (LGG). Patients underwent prospectively conventional MR, proton magnetic resonance spectroscopy ((1) HMRS), and perfusion-weighted images (PWI). Statistical analyses were performed to determine the correlative and independent predictive factors of rCBVmax and the metabolite ratio thresholds with optimum sensitivity and specificity. Thirty-one patients were included in this study. Linear correlations were observed between the metabolic ratios (lactate [Lac]/creatine [Cr], choline [Cho]/N-acetyl-aspartate [NAA], free-lipids/Cr) and rCBVmax (P < 0.05). These metabolic ratios were determined to be independent predictive factors of rCBVmax (P = 0.027, 0.011 and 0.032, respectively). According to the receiver operating characteristic curves, the cutoff values of the metabolic ratios to discriminate between the two populations of rCBVmax (<1.7 versus = 1.7) were 1.72, 1.54, and 1.40, respectively, with a sensitivity = 75% and a specificity >95% for Lac/Cr. This study demonstrated consistent correlations between the data from (1) HMRS and PWI. The Lac/Cr ratio predicts regional hemodynamic changes, which are themselves a useful biomarker of clinical prognosis in patients with LGG. As such, this ratio may provide a new parameter for making improved clinical decisions. Copyright © 2011 Wiley-Liss, Inc.

Physical function interfering with pain and symptoms in fibromyalgia patients.

PubMed

Assumpção, A; Sauer, J F; Mango, P C; Pascual Marques, A

2010-01-01

The aim of this study was to assess the relationship between variables of physical assessment - muscular strength, flexibility and dynamic balance - with pain, pain threshold, and fibromyalgia symptoms (FM). Our sample consists of 55 women, with age ranging from 30 to 55 years (mean of 46.5, (standard deviation, SD=6.6)), mean body mass index (BMI) of 28.7 (3.8) and diagnosed for FM according to the American College of Rheumatology criteria. Pain intensity was measured using a visual analogue scale (VAS) and pain threshold (PT) using Fisher's dolorimeter. FM symptoms were assessed by the Fibromyalgia Impact Questionnaire (FIQ); flexibility by the third finger to floor test (3FF); the muscular strength index (MSI) by the maximum volunteer isometric contraction at flexion and extension of right knee and elbow using a force transducer, dynamic balance by the time to get up and go (TUG) test and the functional reach test (FRT). Data were analysed using Pearson's correlation, as well as simple and multivariate regression tests, with significance level of 5%. PT and FIQ were weakly but significantly correlated with the TUG, MSI and 3FF as well as VAS with the TUG and MSI (p<0.05). VAS, PT and FIQ was not correlated with FRT. Simple regression suggests that, alone, TUG, FR, MSI and 3FF are low predictors of VAS, PT and FIQ. For the VAS, the best predictive model includes TUG and MSI, explaining 12.6% of pain variability. For TP and total symptoms, as obtained by the FIQ, most predictive model includes 3FF and MSI, which respectively respond by 30% and 21% of the variability. Muscular strength, flexibility and balance are associated with pain, pain threshold, and symptoms in FM patients.

Sex allocation and interactions between relatives in the bean beetle, Callosobruchus maculatus.

PubMed

Reece, Sarah E; Wherry, Ruth N; Bloor, Juliette M G

2005-11-01

When a small number of females contribute offspring to a discrete mating group, sex allocation (Local Mate Competition: LMC) theory predicts that females should bias their offspring sex ratio towards daughters, which avoids the fitness costs of their sons competing with each other. Conversely, when a large number of females contribute offspring to a patch, they are expected to invest equally in sons and daughters. Furthermore, sex ratios of species that regularly experience variable foundress numbers are closer to those predicted by LMC theory than species that encounter less variable foundress number scenarios. Due to their patterns of resource use, female Callosobruchus maculatus are likely to experience a broad range of foundress number scenarios. We carried out three experiments to test whether female C. maculatus adjust their sex ratios in response to foundress number and two other indicators of LMC: ovipositing on pre-parasitised patches and ovipositing with sisters. We did not find any evidence of the predicted sex ratio adjustment, but we did find evidence of kin biased behaviour.

Cannabinoid-induced effects on the nociceptive system: a neurophysiological study in patients with secondary progressive multiple sclerosis.

PubMed

Conte, Antonella; Bettolo, Chiara Marini; Onesti, Emanuela; Frasca, Vittorio; Iacovelli, Elisa; Gilio, Francesca; Giacomelli, Elena; Gabriele, Maria; Aragona, Massimiliano; Tomassini, Valentina; Pantano, Patrizia; Pozzilli, Carlo; Inghilleri, Maurizio

2009-05-01

Although clinical studies show that cannabinoids improve central pain in patients with multiple sclerosis (MS) neurophysiological studies are lacking to investigate whether they also suppress these patients' electrophysiological responses to noxious stimulation. The flexion reflex (FR) in humans is a widely used technique for assessing the pain threshold and for studying spinal and supraspinal pain pathways and the neurotransmitter system involved in pain control. In a randomized, double-blind, placebo-controlled, cross-over study we investigated cannabinoid-induced changes in RIII reflex variables (threshold, latency and area) in a group of 18 patients with secondary progressive MS. To investigate whether cannabinoids act indirectly on the nociceptive reflex by modulating lower motoneuron excitability we also evaluated the H-reflex size after tibial nerve stimulation and calculated the H wave/M wave (H/M) ratio. Of the 18 patients recruited and randomized 17 completed the study. After patients used a commercial delta-9-tetrahydrocannabinol (THC) and cannabidiol mixture as an oromucosal spray the RIII reflex threshold increased and RIII reflex area decreased. The visual analogue scale score for pain also decreased, though not significantly. Conversely, the H/M ratio measured before patients received cannabinoids remained unchanged after therapy. In conclusion, the cannabinoid-induced changes in the RIII reflex threshold and area in patients with MS provide objective neurophysiological evidence that cannabinoids modulate the nociceptive system in patients with MS.

The fecal hemoglobin concentration, age and sex test score: Development and external validation of a simple prediction tool for colorectal cancer detection in symptomatic patients.

PubMed

Cubiella, Joaquín; Digby, Jayne; Rodríguez-Alonso, Lorena; Vega, Pablo; Salve, María; Díaz-Ondina, Marta; Strachan, Judith A; Mowat, Craig; McDonald, Paula J; Carey, Francis A; Godber, Ian M; Younes, Hakim Ben; Rodriguez-Moranta, Francisco; Quintero, Enrique; Álvarez-Sánchez, Victoria; Fernández-Bañares, Fernando; Boadas, Jaume; Campo, Rafel; Bujanda, Luis; Garayoa, Ana; Ferrandez, Ángel; Piñol, Virginia; Rodríguez-Alcalde, Daniel; Guardiola, Jordi; Steele, Robert J C; Fraser, Callum G

2017-05-15

Prediction models for colorectal cancer (CRC) detection in symptomatic patients, based on easily obtainable variables such as fecal haemoglobin concentration (f-Hb), age and sex, may simplify CRC diagnosis. We developed, and then externally validated, a multivariable prediction model, the FAST Score, with data from five diagnostic test accuracy studies that evaluated quantitative fecal immunochemical tests in symptomatic patients referred for colonoscopy. The diagnostic accuracy of the Score in derivation and validation cohorts was compared statistically with the area under the curve (AUC) and the Chi-square test. 1,572 and 3,976 patients were examined in these cohorts, respectively. For CRC, the odds ratio (OR) of the variables included in the Score were: age (years): 1.03 (95% confidence intervals (CI): 1.02-1.05), male sex: 1.6 (95% CI: 1.1-2.3) and f-Hb (0-<20 µg Hb/g feces): 2.0 (95% CI: 0.7-5.5), (20-<200 µg Hb/g): 16.8 (95% CI: 6.6-42.0), ≥200 µg Hb/g: 65.7 (95% CI: 26.3-164.1). The AUC for CRC detection was 0.88 (95% CI: 0.85-0.90) in the derivation and 0.91 (95% CI: 0.90-093; p = 0.005) in the validation cohort. At the two Score thresholds with 90% (4.50) and 99% (2.12) sensitivity for CRC, the Score had equivalent sensitivity, although the specificity was higher in the validation cohort (p < 0.001). Accordingly, the validation cohort was divided into three groups: high (21.4% of the cohort, positive predictive value-PPV: 21.7%), intermediate (59.8%, PPV: 0.9%) and low (18.8%, PPV: 0.0%) risk for CRC. The FAST Score is an easy to calculate prediction tool, highly accurate for CRC detection in symptomatic patients. © 2017 UICC.

An assessment of thromboelastometry to monitor blood coagulation and guide transfusion support in liver transplantation.

PubMed

Blasi, Annabel; Beltran, Joan; Pereira, Arturo; Martinez-Palli, Graciela; Torrents, Abiguei; Balust, Jaume; Zavala, Elizabeth; Taura, Pilar; Garcia-Valdecasas, Juan-Carlos

2012-09-01

Rotation thromboelastometry (TEM) has been proposed as a convenient alternative to standard coagulation tests in guiding the treatment of coagulopathy during orthotopic liver transplantation (OLT). This study was aimed at assessing the value of TEM in monitoring blood coagulation and guide transfusion support in OLT. Standard coagulation and TEM (EXTEM and FIBTEM) tests were performed at four preestablished intraoperative time points in 236 OLTs and prospectively recorded in a dedicated database together with the main operative and transfusion data. Transfusion thresholds were based on standard coagulation tests. Spearman's rank correlation (ρ), linear regression, and receiver operating characteristic curves were used when appropriate. EXTEM maximum clot firmness (MCF(EXTEM)) was the TEM variable that best correlated with the platelet (PLT) and fibrinogen levels (ρ = 0.62 and ρ = 0.69, respectively). MCF(FIBTEM) correlated with fibrinogen level (ρ = 0.70). EXTEM clot amplitude at 10 minutes (A10(EXTEM)) was a good linear predictor of MCF(EXTEM) (R(2) =0.93). The cutoff values that best predicted the transfusion threshold for PLTs and fibrinogen were A10(EXTEM) = 35 mm and A10(FIBTEM) = 8 mm. At these values, the negative and positive predictive accuracies of TEM to predict the transfusion thresholds were 95 and 27%, respectively. A10(EXTEM) is an adequate TEM variable to guide therapeutic decisions during OLT. Patients with A10(EXTEM) of greater than 35 mm are unlikely to bleed because of coagulation deficiencies, but using A10(EXTEM) of not more than 35 mm as the sole transfusion criterion can lead to unnecessary utilization of PLTs and fibrinogen-rich products. © 2012 American Association of Blood Banks.

Seabirds as indicators of marine food supplies: Cairns revisited

USGS Publications Warehouse

Piatt, John F.; Harding, Ann M.A.; Shultz, Michael T.; Speckman, Suzann G.; van Pelt, Thomas I.; Drew, Gary S.; Kettle, Arthur B.

2007-01-01

In his seminal paper about using seabirds as indicators of marine food supplies, Cairns (1987, Biol Oceanogr 5:261–271) predicted that (1) parameters of seabird biology and behavior would vary in curvilinear fashion with changes in food supply, (2) the threshold of prey density over which birds responded would be different for each parameter, and (3) different seabird species would respond differently to variation in food availability depending on foraging behavior and ability to adjust time budgets. We tested these predictions using data collected at colonies of common murre Uria aalge and black-legged kittiwake Rissa tridactyla in Cook Inlet, Alaska. (1) Of 22 seabird responses fitted with linear and non-linear functions, 16 responses exhibited significant curvilinear shapes, and Akaike’s information criterion (AIC) analysis indicated that curvilinear functions provided the best-fitting model for 12 of those. (2) However, there were few differences among parameters in their threshold to prey density, presumably because most responses ultimately depend upon a single threshold for prey acquisition at sea. (3) There were similarities and some differences in how species responded to variability in prey density. Both murres and kittiwakes minimized variability (CV < 15%) in their own body condition and growth of chicks in the face of high annual variability (CV = 69%) in local prey density. Whereas kittiwake breeding success (CV = 63%, r2 = 0.89) reflected prey variability, murre breeding success did not (CV = 29%, r2< 0.00). It appears that murres were able to buffer breeding success by reallocating discretionary ‘loafing’ time to foraging effort in response (r2 = 0.64) to declining prey density. Kittiwakes had little or no discretionary time, so fledging success was a more direct function of local prey density. Implications of these results for using ‘seabirds as indicators’ are discussed.

Drug Concentration Thresholds Predictive of Therapy Failure and Death in Children With Tuberculosis: Bread Crumb Trails in Random Forests

PubMed Central

Swaminathan, Soumya; Pasipanodya, Jotam G.; Ramachandran, Geetha; Hemanth Kumar, A. K.; Srivastava, Shashikant; Deshpande, Devyani; Nuermberger, Eric; Gumbo, Tawanda

2016-01-01

Background. The role of drug concentrations in clinical outcomes in children with tuberculosis is unclear. Target concentrations for dose optimization are unknown. Methods. Plasma drug concentrations measured in Indian children with tuberculosis were modeled using compartmental pharmacokinetic analyses. The children were followed until end of therapy to ascertain therapy failure or death. An ensemble of artificial intelligence algorithms, including random forests, was used to identify predictors of clinical outcome from among 30 clinical, laboratory, and pharmacokinetic variables. Results. Among the 143 children with known outcomes, there was high between-child variability of isoniazid, rifampin, and pyrazinamide concentrations: 110 (77%) completed therapy, 24 (17%) failed therapy, and 9 (6%) died. The main predictors of therapy failure or death were a pyrazinamide peak concentration <38.10 mg/L and rifampin peak concentration <3.01 mg/L. The relative risk of these poor outcomes below these peak concentration thresholds was 3.64 (95% confidence interval [CI], 2.28–5.83). Isoniazid had concentration-dependent antagonism with rifampin and pyrazinamide, with an adjusted odds ratio for therapy failure of 3.00 (95% CI, 2.08–4.33) in antagonism concentration range. In regard to death alone as an outcome, the same drug concentrations, plus z scores (indicators of malnutrition), and age <3 years, were highly ranked predictors. In children <3 years old, isoniazid 0- to 24-hour area under the concentration-time curve <11.95 mg/L × hour and/or rifampin peak <3.10 mg/L were the best predictors of therapy failure, with relative risk of 3.43 (95% CI, .99–11.82). Conclusions. We have identified new antibiotic target concentrations, which are potential biomarkers associated with treatment failure and death in children with tuberculosis. PMID:27742636

Exposure–response relationships for the ACGIH threshold limit value for hand-activity level: results from a pooled data study of carpal tunnel syndrome

PubMed Central

Kapellusch, Jay M; Gerr, Frederic E; Malloy, Elizabeth J; Garg, Arun; Harris-Adamson, Carisa; Bao, Stephen S; Burt, Susan E; Dale, Ann Marie; Eisen, Ellen A; Evanoff, Bradley A; Hegmann, Kurt T; Silverstein, Barbara A; Theise, Matthew S; Rempel, David M

2014-01-01

Objective This paper aimed to quantify exposure–response relationships between the American Conference of Governmental Industrial Hygienists’ (ACGIH) threshold limit value (TLV) for hand-activity level (HAL) and incidence of carpal tunnel syndrome (CTS). Methods Manufacturing and service workers previously studied by six research institutions had their data combined and re-analyzed. CTS cases were defined by symptoms and abnormal nerve conduction. Hazard ratios (HR) were calculated using proportional hazards regression after adjusting for age, gender, body mass index, and CTS predisposing conditions. Results The longitudinal study comprised 2751 incident-eligible workers, followed prospectively for up to 6.4 years and contributing 6243 person-years of data. Associations were found between CTS and TLV for HAL both as a continuous variable [HR 1.32 per unit, 95% confidence interval (95% CI) 1.11–1.57] and when categorized using the ACGIH action limit (AL) and TLV. Those between the AL and TLV and above the TLV had HR of 1.7 (95% CI 1.2–2.5) and 1.5 (95% CI 1.0–2.1), respectively. As independent variables (in the same adjusted model) the HR for peak force (PF) and HAL were 1.14 per unit (95% CI 1.05–1.25), and 1.04 per unit (95% CI 0.93–1.15), respectively. Conclusion Those with exposures above the AL were at increased risk of CTS, but there was no further increase in risk for workers above the TLV. This suggests that the current AL may not be sufficiently protective of workers. Combinations of PF and HAL are useful for predicting risk of CTS. PMID:25266844

Prediction of composite fatigue life under variable amplitude loading using artificial neural network trained by genetic algorithm

NASA Astrophysics Data System (ADS)

Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung

2018-04-01

Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

Prediction of clinical infection in women with preterm labour with intact membranes: a score based on ultrasonographic, clinical and biological markers.

PubMed

Kayem, Gilles; Maillard, Françoise; Schmitz, Thomas; Jarreau, Pierre H; Cabrol, Dominique; Breart, Gérard; Goffinet, François

2009-07-01

To predict maternal and neonatal clinical infection at admission in women hospitalized for preterm labour (PTL) with intact membranes. Prospective study of 371 women hospitalized for preterm labour with intact membranes. The primary outcome was clinical infection, defined by clinical chorioamnionitis at delivery or early-onset neonatal infection. Clinical infection was identified in 21 cases (5.7%) and was associated with earlier gestational age at admission for PTL, elevated maternal C-reactive protein (CRP) and white blood cell count (WBC), shorter cervical length, and a cervical funnelling on ultrasound. We used ROC curves to determine the cut-off values that minimized the number of false positives and false negatives. The cut-off points chosen were 30 weeks for gestational age at admission, 25 mm for cervical length, 8 mg/l for CRP and 12,000 c/mm(3) for WBC. Each of these variables was assigned a weight on the basis of the adjusted odds ratios in a clinical infection risk score (CIRS). We set a threshold corresponding to a specificity close to 90%, and calculated the positive and negative predictive values and likelihood ratios of each marker and of the CIRS. The CIRS had a sensitivity of 61.9%, while the sensitivity of the other markers ranged from 19.0% to 42.9%. Internal cross-validation was used to estimate the performance of the CIRS in new subjects. The diagnostic values found remained close to the initial values. A clinical infection risk score built from data known at admission for preterm labour helps to identify women and newborns at high risk of clinical infection.

Neural activity in cortical area V4 underlies fine disparity discrimination.

PubMed

Shiozaki, Hiroshi M; Tanabe, Seiji; Doi, Takahiro; Fujita, Ichiro

2012-03-14

Primates are capable of discriminating depth with remarkable precision using binocular disparity. Neurons in area V4 are selective for relative disparity, which is the crucial visual cue for discrimination of fine disparity. Here, we investigated the contribution of V4 neurons to fine disparity discrimination. Monkeys discriminated whether the center disk of a dynamic random-dot stereogram was in front of or behind its surrounding annulus. We first behaviorally tested the reference frame of the disparity representation used for performing this task. After learning the task with a set of surround disparities, the monkey generalized its responses to untrained surround disparities, indicating that the perceptual decisions were generated from a disparity representation in a relative frame of reference. We then recorded single-unit responses from V4 while the monkeys performed the task. On average, neuronal thresholds were higher than the behavioral thresholds. The most sensitive neurons reached thresholds as low as the psychophysical thresholds. For subthreshold disparities, the monkeys made frequent errors. The variable decisions were predictable from the fluctuation in the neuronal responses. The predictions were based on a decision model in which each V4 neuron transmits the evidence for the disparity it prefers. We finally altered the disparity representation artificially by means of microstimulation to V4. The decisions were systematically biased when microstimulation boosted the V4 responses. The bias was toward the direction predicted from the decision model. We suggest that disparity signals carried by V4 neurons underlie precise discrimination of fine stereoscopic depth.

Diagnostic capability of scanning laser polarimetry with variable cornea compensator in Indian patients with early primary open-angle glaucoma.

PubMed

Parikh, Rajul S; Parikh, Shefali R; Kumar, Rajesh S; Prabakaran, S; Babu, J Gansesh; Thomas, Ravi

2008-07-01

To evaluate the diagnostic ability of scanning laser polarimetry (GDx variable corneal compensator [VCC]) for early glaucoma in Asian Indian eyes. Cross-sectional observational study. Two groups of patients (early glaucoma and normal) who satisfied the inclusion and exclusion criteria were included. Early glaucoma was diagnosed in presence of open angles, characteristic glaucomatous optic disc changes correlating with the visual field (VF) on automated perimetry (VF defect fulfilling at least 2 of 3 Anderson and Patella's criteria with mean deviation >or= -6 decibels). Normal subjects had visual acuity >or= 20/30 and intraocular pressure < 22 mmHg, with a normal optic disc and fields and no ocular abnormality. All patients underwent complete ophthalmic evaluation, including VF examination (24-2/30-2 Swedish interactive threshold algorithm standard program) and imaging with GDx VCC. Sensitivity, specificity, positive predictive value and negative predictive value, area under the receiving operating characteristic curve, and likelihood ratios (LRs) were calculated for various GDx VCC parameters. Seventy-four eyes (74 patients) with early glaucoma and 104 eyes (104 normal subjects) were enrolled. TSNIT Std Dev (temporal-superior-nasal-inferior-temporal standard deviation) had the best combination of sensitivity and specificity-61.3 and 95.2, respectively-followed by nerve fiber index score > 50 (sensitivity, 52.7%; specificity, 99%). Nerve fiber index score > 50 had positive and negative predictive values of 74.3% and 97.6%, respectively, for an assumed glaucoma prevalence of 5%. Nerve fiber index score > 50 had a positive LR (+LR) of 54.8 for early glaucoma. GDx VCC has moderate sensitivity, with high specificity, in the diagnosis of early glaucoma. The high +LR for the nerve fiber index score can provide valuable diagnostic information for individual patients.

A masking level difference due to harmonicity.

PubMed

Treurniet, W C; Boucher, D R

2001-01-01

The role of harmonicity in masking was studied by comparing the effect of harmonic and inharmonic maskers on the masked thresholds of noise probes using a three-alternative, forced-choice method. Harmonic maskers were created by selecting sets of partials from a harmonic series with an 88-Hz fundamental and 45 consecutive partials. Inharmonic maskers differed in that the partial frequencies were perturbed to nearby values that were not integer multiples of the fundamental frequency. Average simultaneous-masked thresholds were as much as 10 dB lower with the harmonic masker than with the inharmonic masker, and this difference was unaffected by masker level. It was reduced or eliminated when the harmonic partials were separated by more than 176 Hz, suggesting that the effect is related to the extent to which the harmonics are resolved by auditory filters. The threshold difference was not observed in a forward-masking experiment. Finally, an across-channel mechanism was implicated when the threshold difference was found between a harmonic masker flanked by harmonic bands and a harmonic masker flanked by inharmonic bands. A model developed to explain the observed difference recognizes that an auditory filter output envelope is modulated when the filter passes two or more sinusoids, and that the modulation rate depends on the differences among the input frequencies. For a harmonic masker, the frequency differences of adjacent partials are identical, and all auditory filters have the same dominant modulation rate. For an inharmonic masker, however, the frequency differences are not constant and the envelope modulation rate varies across filters. The model proposes that a lower variability facilitates detection of a probe-induced change in the variability, thus accounting for the masked threshold difference. The model was supported by significantly improved predictions of observed thresholds when the predictor variables included envelope modulation rate variance measured using simulated auditory filters.

Comparison of KRAS genotype: therascreen assay vs. LNA-mediated qPCR clamping assay.

PubMed

Chang, Shao-Chun; Denne, Jonathan; Zhao, Luping; Horak, Christine; Green, George; Khambata-Ford, Shirin; Bray, Christopher; Celik, Ilhan; Van Cutsem, Eric; Harbison, Christopher

2013-09-01

Kirsten rat sarcoma virus (KRAS) wild-type status determined using a locked nucleic acid (LNA)-mediated quantitative polymerase chain reaction (qPCR) clamping assay (LNA assay) predicted response to therapy in the CRYSTAL (Cetuximab Combined With Irinotecan in First-Line Therapy for Metastatic Colorectal Cancer) study. A companion KRAS diagnostic tool has been developed for routine clinical use (QIAGEN therascreen kit) (QIAGEN Manchester Ltd, Manchester, UK). We wanted to assess the concordance between the validated US Food and Drug Administration (FDA)-approved therascreen assay and the LNA assay in determining the KRAS status of a subset of patients enrolled in the CRYSTAL study. DNA extracted from paraffin-embedded tumor sections was tested for KRAS status using the therascreen assay. Efficacy data from the CRYSTAL study were assessed to determine if the overall survival (OS) hazard ratio for cetuximab in patients identified as having KRAS wild-type status using the therascreen assay was equivalent to that in patients identified as KRAS wild-type using the LNA assay. This was determined by assessing if the concordance between the therascreen assay and the LNA assay met the minimum threshold (prespecified as 0.8) to achieve a significant difference in the OS hazard ratio in favor of the cetuximab + FOLFIRI (5-fluorouracil, leucovorin [folinic acid], irinotecan) arm in the KRAS wild-type population as identified using the therascreen assay. Of the 148 samples determined to be KRAS wild-type (therascreen assay), 141 (95.3%) samples were also KRAS wild-type (LNA assay) and 7 samples (4.7%) were KRAS mutant (LNA assay). The prespecified primary concordance measure p was 141/148 = 0.953 (95% confidence interval [CI], 0.905-0.981). The concordance was statistically significantly higher than the prespecified threshold of 0.8 for concordance between the therascreen assay and the LNA assay. Consistent with the concordance exceeding the prespecified threshold, the OS hazard ratio (cetuximab + FOLFIRI arm vs. FOLFIRI arm) in the KRAS wild-type population, determined by the therascreen assay, supported a significant benefit for cetuximab (ie, the 95% CI excluded 1) and was comparable to the OS hazard ratio observed in the CRYSTAL study KRAS wild-type population (LNA assay) even after adjustment for potentially confounding baseline variables. These results support the utility of the therascreen assay for identifying patients who may benefit from cetuximab therapy for metastatic colorectal cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

Preoperative Magnetic Resonance Volumetry in Predicting Myometrial Invasion, Lymphovascular Space Invasion, and Tumor Grade: Is It Valuable in International Federation of Gynecology and Obstetrics Stage I Endometrial Cancer?

PubMed

Sahin, Hilal; Sarioglu, Fatma Ceren; Bagci, Mustafa; Karadeniz, Tugba; Uluer, Hatice; Sanci, Muzaffer

2018-05-01

The aim of this retrospective single-center study was to evaluate the relationship between maximum tumor size, tumor volume, tumor volume ratio (TVR) based on preoperative magnetic resonance (MR) volumetry, and negative histological prognostic parameters (deep myometrial invasion [MI], lymphovascular space invasion, tumor histological grade, and subtype) in International Federation of Gynecology and Obstetrics stage I endometrial cancer. Preoperative pelvic MR imaging studies of 68 women with surgical-pathologic diagnosis of International Federation of Gynecology and Obstetrics stage I endometrial cancer were reviewed for assessment of MR volumetry and qualitative assessment of MI. Volume of the tumor and uterus was measured with manual tracing of each section on sagittal T2-weighted images. Tumor volume ratio was calculated according to the following formula: TVR = (total tumor volume/total uterine volume) × 100. Receiver operating characteristics curve was performed to investigate a threshold for TVR associated with MI. The Mann-Whitney U test, Kruskal-Wallis test, and linear regression analysis were applied to evaluate possible differences between tumor size, tumor volume, TVR, and negative prognostic parameters. Receiver operating characteristics curve analysis of TVR for prediction of deep MI was statistically significant (P = 0.013). An optimal TVR threshold of 7.3% predicted deep myometrial invasion with 85.7% sensitivity, 46.8% specificity, 41.9% positive predictive value, and 88.0% negative predictive value. Receiver operating characteristics curve analyses of TVR, tumor size, and tumor volume for prediction of tumor histological grade or lymphovascular space invasion were not significant. The concordance between radiologic and pathologic assessment for MI was almost excellent (κ value, 0.799; P < 0.001). Addition of TVR to standard radiologic assessment of deep MI increased the sensitivity from 90.5% to 95.2%. Tumor volume ratio, based on preoperative MR volumetry, seems to predict deep MI independently in stage I endometrial cancer with insufficient sensitivity and specificity. Its value in clinical practice for risk stratification models in endometrial cancer has to be studied in larger cohort of patients.

Singers' phonation threshold pressure and ratings of self-perceived effort on vocal tasks.

PubMed

McHenry, Monica; Evans, Joseph; Powitzky, Eric

2013-05-01

This study was designed to determine if singers' self-ratings of vocal effort could predict phonation threshold pressure (PTP). It was hypothesized that effort ratings on the more complex task of singing "Happy Birthday" would best predict PTP. A multiple regression analysis was performed with PTP as the predicted variable and self-ratings on four phonatory tasks as the predictor variables. Participants were 48 undergraduate and graduate students majoring in vocal performance. They produced /pi/ syllable trains as softly as possible for the measurement of PTP. They then rated their self-perceived vocal effort while softly producing the following: (1) sustained "ah" (comfortable, midrange pitch); (2) "ah" glide (chest to head voice); (3) Staccato "ah" in head voice (not falsetto); and (4) Happy Birthday in head voice (not falsetto). No ratings of vocal effort predicted PTP. The lack of correlation between PTP and ratings of Happy Birthday remained when separately evaluating graduate versus undergraduate students or males versus females. Informal evaluation of repeated ratings over time suggested the potential for effective self-monitoring. Students' ratings of self-perceived vocal effort were poor predictors of PTP. This may be because of the use of "effortless" imagery during singing instruction or consistent positive feedback regarding vocal performance. It is possible that self-rating could become an effective tool to predict vocal health if task elicitation instructions were more precise, and the student and voice teacher worked collaboratively to improve self-evaluation. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Perceived pitch of vibrotactile stimuli: effects of vibration amplitude, and implications for vibration frequency coding.

PubMed

Morley, J W; Rowe, M J

1990-12-01

1. The effect of changes in amplitude on the perceived pitch of cutaneous vibratory stimuli was studied in psychophysical experiments designed to test whether the coding of information about the frequency of the vibration might be based on the ratio of recruitment of the PC (Pacinian corpuscle-associated) and RA (rapidly adapting) classes of tactile sensory fibres. The study was based on previous data which show that at certain vibration frequencies (e.g. 150 Hz) the ratio of recruitment of the PC and RA classes should vary as a function of vibration amplitude. 2. Sinusoidal vibration at either 30 Hz or 150 Hz, and at an amplitude 10 dB above subjective detection thresholds was delivered in a 1 s train to the distal phalangeal pad of the index finger in eight human subjects. This standard vibration was followed after 0.5 s by a 1 s comparison train of vibration which (unknown to the subject) was at the same frequency as the standard but at a range of amplitudes from 2 to 50 dB above the detection threshold. A two-alternative forced-choice procedure was used in which the subject had to indicate whether the comparison stimulus was higher or lower in pitch (frequency) than the standard. 3. Marked differences were seen from subject to subject in the effect of amplitude on perceived pitch at both 30 Hz and 150 Hz. At 150 Hz, five out of the eight subjects reported an increase in pitch as the amplitude of the comparison vibration increased, one experienced no change, and only two experienced the fall in perceived pitch that is predicted if the proposed ratio code contributes to vibrotactile pitch judgements. At 30 Hz similar intersubject variability was seen in the pitch-amplitude functions. 4. The results do not support the hypothesis that a ratio code contributes to vibrotactile pitch perception. We conclude that temporal patterning of impulse activity remains the major candidate code for pitch perception, at least over a substantial part of the vibrotactile frequency bandwidth.

Using a visual discrimination model for the detection of compression artifacts in virtual pathology images.

PubMed

Johnson, Jeffrey P; Krupinski, Elizabeth A; Yan, Michelle; Roehrig, Hans; Graham, Anna R; Weinstein, Ronald S

2011-02-01

A major issue in telepathology is the extremely large and growing size of digitized "virtual" slides, which can require several gigabytes of storage and cause significant delays in data transmission for remote image interpretation and interactive visualization by pathologists. Compression can reduce this massive amount of virtual slide data, but reversible (lossless) methods limit data reduction to less than 50%, while lossy compression can degrade image quality and diagnostic accuracy. "Visually lossless" compression offers the potential for using higher compression levels without noticeable artifacts, but requires a rate-control strategy that adapts to image content and loss visibility. We investigated the utility of a visual discrimination model (VDM) and other distortion metrics for predicting JPEG 2000 bit rates corresponding to visually lossless compression of virtual slides for breast biopsy specimens. Threshold bit rates were determined experimentally with human observers for a variety of tissue regions cropped from virtual slides. For test images compressed to their visually lossless thresholds, just-noticeable difference (JND) metrics computed by the VDM were nearly constant at the 95th percentile level or higher, and were significantly less variable than peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics. Our results suggest that VDM metrics could be used to guide the compression of virtual slides to achieve visually lossless compression while providing 5-12 times the data reduction of reversible methods.

Electrically evoked compound action potential amplitude growth functions and HiResolution programming levels in pediatric CII implant subjects.

PubMed

Eisen, Marc D; Franck, Kevin H

2004-12-01

To characterize the amplitude growth functions of the electrically evoked compound action potential (ECAP) in pediatric subjects implanted with the Clarion HiFocus electrode array with respect to electrode position and the presence or absence of a Silastic positioner. Electrophysiologic growth function data are compared with HiResolution (HiRes) psychophysical programming levels. ECAP growth functions were measured for all electrodes along the implant's array in 16 pediatric subjects. Nine of the patients were implanted with a Silastic positioner, whereas seven had no positioner. ECAP thresholds and growth function slopes were calculated. Fifteen of the 16 patients had psychophysical threshold and maximum comfort levels available. Programming levels and ECAP thresholds were compared within and among the subjects. ECAP thresholds showed variability among patients, ranging from 178 to 920 nA at 32 musec pulse width. ECAP thresholds did not depend on electrode position along the cochlea but were lower in the presence of the Silastic positioner (p < 0.001). Thresholds determined with the masker-probe versus the alternating polarity paradigms revealed moderate (r = 0.76) correlation. Growth function slopes also showed considerable variation among patients. Unlike thresholds, slopes decreased from apical to basal cochlear locations (p < 0.001) but showed no difference between the absence and presence of the positioner. Programming levels in HiRes were correlated with ECAP threshold levels. When ECAP thresholds were adjusted for each patient by the difference between M level and ECAP threshold at electrode 9, however, overall correlation between the two measurements was excellent (r = 0.98, N = 224). In pediatric subjects with the Clarion HiFocus electrode, ECAP growth function thresholds appear to decrease with the presence of the Silastic positioner but are unaffected by electrode position along the array. Growth function slope, however, depends on electrode position along the array but not on the presence of the positioner. ECAP programming levels can reliably predict stimulus intensities within the patients' dynamic ranges, but considerable variability is seen between ECAP thresholds and HiRes programming levels.

Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening.

PubMed

Katki, Hormuzd A; Kovalchik, Stephanie A; Petito, Lucia C; Cheung, Li C; Jacobs, Eric; Jemal, Ahmedin; Berg, Christine D; Chaturvedi, Anil K

2018-05-15

Lung cancer screening guidelines recommend using individualized risk models to refer ever-smokers for screening. However, different models select different screening populations. The performance of each model in selecting ever-smokers for screening is unknown. To compare the U.S. screening populations selected by 9 lung cancer risk models (the Bach model; the Spitz model; the Liverpool Lung Project [LLP] model; the LLP Incidence Risk Model [LLPi]; the Hoggart model; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 [PLCOM2012]; the Pittsburgh Predictor; the Lung Cancer Risk Assessment Tool [LCRAT]; and the Lung Cancer Death Risk Assessment Tool [LCDRAT]) and to examine their predictive performance in 2 cohorts. Population-based prospective studies. United States. Models selected U.S. screening populations by using data from the National Health Interview Survey from 2010 to 2012. Model performance was evaluated using data from 337 388 ever-smokers in the National Institutes of Health-AARP Diet and Health Study and 72 338 ever-smokers in the CPS-II (Cancer Prevention Study II) Nutrition Survey cohort. Model calibration (ratio of model-predicted to observed cases [expected-observed ratio]) and discrimination (area under the curve [AUC]). At a 5-year risk threshold of 2.0%, the models chose U.S. screening populations ranging from 7.6 million to 26 million ever-smokers. These disagreements occurred because, in both validation cohorts, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) were well-calibrated (expected-observed ratio range, 0.92 to 1.12) and had higher AUCs (range, 0.75 to 0.79) than 5 models that generally overestimated risk (expected-observed ratio range, 0.83 to 3.69) and had lower AUCs (range, 0.62 to 0.75). The 4 best-performing models also had the highest sensitivity at a fixed specificity (and vice versa) and similar discrimination at a fixed risk threshold. These models showed better agreement on size of the screening population (7.6 million to 10.9 million) and achieved consensus on 73% of persons chosen. No consensus on risk thresholds for screening. The 9 lung cancer risk models chose widely differing U.S. screening populations. However, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) most accurately predicted risk and performed best in selecting ever-smokers for screening. Intramural Research Program of the National Institutes of Health/National Cancer Institute.

Biodiversity response to natural gradients of multiple stressors on continental margins

PubMed Central

Sperling, Erik A.; Frieder, Christina A.; Levin, Lisa A.

2016-01-01

Sharp increases in atmospheric CO2 are resulting in ocean warming, acidification and deoxygenation that threaten marine organisms on continental margins and their ecological functions and resulting ecosystem services. The relative influence of these stressors on biodiversity remains unclear, as well as the threshold levels for change and when secondary stressors become important. One strategy to interpret adaptation potential and predict future faunal change is to examine ecological shifts along natural gradients in the modern ocean. Here, we assess the explanatory power of temperature, oxygen and the carbonate system for macrofaunal diversity and evenness along continental upwelling margins using variance partitioning techniques. Oxygen levels have the strongest explanatory capacity for variation in species diversity. Sharp drops in diversity are seen as O2 levels decline through the 0.5–0.15 ml l−1 (approx. 22–6 µM; approx. 21–5 matm) range, and as temperature increases through the 7–10°C range. pCO2 is the best explanatory variable in the Arabian Sea, but explains little of the variance in diversity in the eastern Pacific Ocean. By contrast, very little variation in evenness is explained by these three global change variables. The identification of sharp thresholds in ecological response are used here to predict areas of the seafloor where diversity is most at risk to future marine global change, noting that the existence of clear regional differences cautions against applying global thresholds. PMID:27122565

Intercenter Differences in Bronchopulmonary Dysplasia or Death Among Very Low Birth Weight Infants

PubMed Central

Walsh, Michele; Bobashev, Georgiy; Das, Abhik; Levine, Burton; Carlo, Waldemar A.; Higgins, Rosemary D.

2011-01-01

OBJECTIVES: To determine (1) the magnitude of clustering of bronchopulmonary dysplasia (36 weeks) or death (the outcome) across centers of the Eunice Kennedy Shriver National Institute of Child and Human Development National Research Network, (2) the infant-level variables associated with the outcome and estimate their clustering, and (3) the center-specific practices associated with the differences and build predictive models. METHODS: Data on neonates with a birth weight of <1250 g from the cluster-randomized benchmarking trial were used to determine the magnitude of clustering of the outcome according to alternating logistic regression by using pairwise odds ratio and predictive modeling. Clinical variables associated with the outcome were identified by using multivariate analysis. The magnitude of clustering was then evaluated after correction for infant-level variables. Predictive models were developed by using center-specific and infant-level variables for data from 2001 2004 and projected to 2006. RESULTS: In 2001–2004, clustering of bronchopulmonary dysplasia/death was significant (pairwise odds ratio: 1.3; P < .001) and increased in 2006 (pairwise odds ratio: 1.6; overall incidence: 52%; range across centers: 32%–74%); center rates were relatively stable over time. Variables that varied according to center and were associated with increased risk of outcome included lower body temperature at NICU admission, use of prophylactic indomethacin, specific drug therapy on day 1, and lack of endotracheal intubation. Center differences remained significant even after correction for clustered variables. CONCLUSION: Bronchopulmonary dysplasia/death rates demonstrated moderate clustering according to center. Clinical variables associated with the outcome were also clustered. Center differences after correction of clustered variables indicate presence of as-yet unmeasured center variables. PMID:21149431

Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset.

PubMed

Watson, Nathanial E; Parsons, Brendon A; Synovec, Robert E

2016-08-12

Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified. Copyright © 2016 Elsevier B.V. All rights reserved.

Threshold for the destabilisation of the ion-temperature-gradient mode in magnetically confined toroidal plasmas

NASA Astrophysics Data System (ADS)

Zocco, A.; Xanthopoulos, P.; Doerk, H.; Connor, J. W.; Helander, P.

2018-02-01

The threshold for the resonant destabilisation of ion-temperature-gradient (ITG) driven instabilities that render the modes ubiquitous in both tokamaks and stellarators is investigated. We discover remarkably similar results for both confinement concepts if care is taken in the analysis of the effect of the global shear . We revisit, analytically and by means of gyrokinetic simulations, accepted tokamak results and discover inadequacies of some aspects of their theoretical interpretation. In particular, for standard tokamak configurations, we find that global shear effects on the critical gradient cannot be attributed to the wave-particle resonance destabilising mechanism of Hahm & Tang (Phys. Plasmas, vol. 1, 1989, pp. 1185-1192), but are consistent with a stabilising contribution predicted by Biglari et al. (Phys. Plasmas, vol. 1, 1989, pp. 109-118). Extensive analytical and numerical investigations show that virtually no previous tokamak theoretical predictions capture the temperature dependence of the mode frequency at marginality, thus leading to incorrect instability thresholds. In the asymptotic limit , where is the rotational transform, and such a threshold should be solely determined by the resonant toroidal branch of the ITG mode, we discover a family of unstable solutions below the previously known threshold of instability. This is true for a tokamak case described by a local local equilibrium, and for the stellarator Wendelstein 7-X, where these unstable solutions are present even for configurations with a small trapped-particle population. We conjecture they are of the Floquet type and derive their properties from the Fourier analysis of toroidal drift modes of Connor & Taylor (Phys. Fluids, vol. 30, 1987, pp. 3180-3185), and to Hill's theory of the motion of the lunar perigee (Acta Math., vol. 8, 1886, pp. 1-36). The temperature dependence of the newly determined threshold is given for both confinement concepts. In the first case, the new temperature-gradient threshold is found to be rather insensitive to the temperature ratio i/Te$ , at least for i/Te\\lesssim 1$ , and to be a growing function of the density gradient scale for i/Te\\gtrsim 1$ . For Wendelstein 7-X, the new critical temperature gradient is a growing function of the temperature ratio. The importance of these findings for the assessment of turbulence in stellarators and low-shear tokamak configurations is discussed.

The role of NT-proBNP in explaining the variance in anaerobic threshold and VE/VCO(2) slope.

PubMed

Athanasopoulos, Leonidas V; Dritsas, Athanasios; Doll, Helen A; Cokkinos, Dennis V

2011-01-01

We investigated whether anaerobic threshold (AT) and ventilatory efficiency (minute ventilation/carbon dioxide production slope, VE/VCO2 slope), both significantly associated with mortality, can be predicted by questionnaire scores and/or other laboratory measurements. Anaerobic threshold and VE/VCO(2) slope, plasma N-terminal pro-brain natriuretic peptide (NT-proBNP), and the echocardiographic markers left ventricular ejection fraction (LVEF) and left atrial (LA) diameter were measured in 62 patients with heart failure (HF), who also completed the Minnesota Living with Heart Failure Questionnaire (MLHF), and the Specific Activity Questionnaire (SAQ). Linear regression models, adjusting for age and gender, were fitted. While the etiology of HF, SAQ score, MLHF score, LVEF, LA diameter, and logNT-proBNP were each significantly predictive of both AT and VE/VCO2 slope on stepwise multiple linear regression, only SAQ score (P < .001) and logNT-proBNP (P = .001) were significantly predictive of AT, explaining 56% of the variability (adjusted R(2) = 0.525), while logNT-proBNP (P < .001) and etiology of HF (P = .003) were significantly predictive of VE/VCO(2) slope, explaining 49% of the variability (adjusted R(2) = 0.45). The area under the ROC curve for NT-proBNP to identify patients with a VE/VCO(2) slope greater than 34 and AT less than 11 mL · kg(-1) · min(-1) was 0.797; P < .001 and 0.712; P = .044, respectively. A plasma concentration greater than 429.5 pg/mL (sensitivity: 78%; specificity: 70%) and greater than 674.5 pg/mL (sensitivity: 77.8%; specificity: 65%) identified a VE/VCO(2) slope greater than 34 and AT lower than 11 mL · kg(-1) · min(-1), respectively. NT-proBNP is independently related to both AT and VE/VCO(2) slope. Specific Activity Questionnaire score is independently related only to AT and the etiology of HF only to VE/VCO(2) slope.

When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values

PubMed Central

Baldi, Pierre

2010-01-01

As repositories of chemical molecules continue to expand and become more open, it becomes increasingly important to develop tools to search them efficiently and assess the statistical significance of chemical similarity scores. Here we develop a general framework for understanding, modeling, predicting, and approximating the distribution of chemical similarity scores and its extreme values in large databases. The framework can be applied to different chemical representations and similarity measures but is demonstrated here using the most common binary fingerprints with the Tanimoto similarity measure. After introducing several probabilistic models of fingerprints, including the Conditional Gaussian Uniform model, we show that the distribution of Tanimoto scores can be approximated by the distribution of the ratio of two correlated Normal random variables associated with the corresponding unions and intersections. This remains true also when the distribution of similarity scores is conditioned on the size of the query molecules in order to derive more fine-grained results and improve chemical retrieval. The corresponding extreme value distributions for the maximum scores are approximated by Weibull distributions. From these various distributions and their analytical forms, Z-scores, E-values, and p-values are derived to assess the significance of similarity scores. In addition, the framework allows one to predict also the value of standard chemical retrieval metrics, such as Sensitivity and Specificity at fixed thresholds, or ROC (Receiver Operating Characteristic) curves at multiple thresholds, and to detect outliers in the form of atypical molecules. Numerous and diverse experiments carried in part with large sets of molecules from the ChemDB show remarkable agreement between theory and empirical results. PMID:20540577

Image discrimination models predict detection in fixed but not random noise

NASA Technical Reports Server (NTRS)

Ahumada, A. J. Jr; Beard, B. L.; Watson, A. B. (Principal Investigator)

1997-01-01

By means of a two-interval forced-choice procedure, contrast detection thresholds for an aircraft positioned on a simulated airport runway scene were measured with fixed and random white-noise masks. The term fixed noise refers to a constant, or unchanging, noise pattern for each stimulus presentation. The random noise was either the same or different in the two intervals. Contrary to simple image discrimination model predictions, the same random noise condition produced greater masking than the fixed noise. This suggests that observers seem unable to hold a new noisy image for comparison. Also, performance appeared limited by internal process variability rather than by external noise variability, since similar masking was obtained for both random noise types.

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

PubMed Central

Gaudart, Jean; Touré, Ousmane; Dessay, Nadine; Dicko, A lassane; Ranque, Stéphane; Forest, Loic; Demongeot, Jacques; Doumbo, Ogobara K

2009-01-01

Background The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]). The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Conclusion Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Non-linear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation. PMID:19361335

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali.

PubMed

Gaudart, Jean; Touré, Ousmane; Dessay, Nadine; Dicko, A Lassane; Ranque, Stéphane; Forest, Loic; Demongeot, Jacques; Doumbo, Ogobara K

2009-04-10

The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models.Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data.The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia.Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]).The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Non-linear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation.

Gravity wave control on ESF day-to-day variability: An empirical approach

NASA Astrophysics Data System (ADS)

Aswathy, R. P.; Manju, G.

2017-06-01

The gravity wave control on the daily variation in nighttime ionization irregularity occurrence is studied using ionosonde data for the period 2002-2007 at magnetic equatorial location Trivandrum. Recent studies during low solar activity period have revealed that the seed perturbations should have the threshold amplitude required to trigger equatorial spread F (ESF), at a particular altitude and that this threshold amplitude undergoes seasonal and solar cycle changes. In the present study, the altitude variation of the threshold seed perturbations is examined for autumnal equinox of different years. Thereafter, a unique empirical model, incorporating the electrodynamical effects and the gravity wave modulation, is developed. Using the model the threshold curve for autumnal equinox season of any year may be delineated if the solar flux index (F10.7) is known. The empirical model is validated using the data for high, moderate, and low solar epochs in 2001, 2004, and 1995, respectively. This model has the potential to be developed further, to forecast ESF incidence, if the base height of ionosphere is in the altitude region where electrodynamics controls the occurrence of ESF. ESF irregularities are harmful for communication and navigation systems, and therefore, research is ongoing globally to predict them. In this context, this study is crucial for evolving a methodology to predict communication as well as navigation outages.