961 resultados para Soil-water Characteristic Curve


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Silver Creek is a warm water stream resource located in one of the most intensely cropped portions of Clayton County. The stream has been included on Iowa’s 303(d) list of impaired waters since 2002. Aquatic life, which should be present in Silver Creek, isn’t there. According to the Draft Total Maximum Daily Load (TMDL) for Silver Creek, the primary nonpoint pollution sources are soil erosion from agricultural land uses and direct deposition of ammonia by livestock with access to the stream. The Clayton Soil & Water Conservation District has begun efforts to remove Silver Creek from the impaired waters list. The District has promoted stream corridor and sinkhole protection, and the installation of buffer practices along Silver Creek and its tributaries. Conservation practices have been targeted to crop fields to reduce sediment delivery to the stream. A series of news articles, newsletters, and field days have been utilized to increase public understanding of water quality issues. Landowner interest has outweighed available cost share resources. Additional financial support will allow the project to build upon its early successes, to further address the identified impairments, and to respond to a long list of landowners that are interested in conservation work on their farms.

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Price Creek is a 13 mile long stream located in SE Benton County and the NE corner of Iowa County. It ends below the village of Amana where it flows into the Iowa River. The Iowa and Benton County Soil & Water Conservation Districts (SWCDs) applied (and were tentatively approved) for 319/WPF/WSPF funding to treat livestock and water quality issues in this watershed over the next three years. That project’s funds were allocated for a Project Coordinator, information and education activities, and cost share for Best Management Practices (BMPs) directed toward livestock issues and nutrient issues. Soil erosion and sedimentation are also problems in this 18,838 acre watershed. It is 64% HEL (highly erodible land) and 58% of it is cropped. With a coordinator working with Price Creek producers, this would be an excellent time to also address the soil loss and sedimentation issues in this watershed. We will offer additional cost share incentives on BMPs targeting soil erosion on the critical areas we’ve identified. We are applying to IWIRB for additional funding to allow us to cost share specific BMPs up to 75% to treat soil loss in these critical areas of the Price Creek Watershed.

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BACKGROUND AND PURPOSE: Hyperglycemia after stroke is associated with larger infarct volume and poorer functional outcome. In an animal stroke model, the association between serum glucose and infarct volume is described by a U-shaped curve with a nadir ≈7 mmol/L. However, a similar curve in human studies was never reported. The objective of the present study is to investigate the association between serum glucose levels and functional outcome in patients with acute ischemic stroke. METHODS: We analyzed 1446 consecutive patients with acute ischemic stroke. Serum glucose was measured on admission at the emergency department together with multiple other metabolic, clinical, and radiological parameters. National Institutes of Health Stroke Scale (NIHSS) score was recorded at 24 hours, and Rankin score was recorded at 3 and 12 months. The association between serum glucose and favorable outcome (Rankin score ≤2) was explored in univariate and multivariate analysis. The model was further analyzed in a robust regression model based on fractional polynomial (-2-2) functions. RESULTS: Serum glucose is independently correlated with functional outcome at 12 months (OR, 1.15; P=0.01). Other predictors of outcome include admission NIHSS score (OR, 1.18; P<0001), age (OR, 1.06; P<0.001), prestroke Rankin score (OR, 20.8; P=0.004), and leukoaraiosis (OR, 2.21; P=0.016). Using these factors in multiple logistic regression analysis, the area under the receiver-operator characteristic curve is 0.869. The association between serum glucose and Rankin score at 12 months is described by a J-shaped curve with a nadir of 5 mmol/L. Glucose values between 3.7 and 7.3 mmol/L are associated with favorable outcome. A similar curve was generated for the association of glucose and 24-hour NIHSS score, for which glucose values between 4.0 and 7.2 mmol/L are associated with a NIHSS score <7. Discussion-Both hypoglycemia and hyperglycemia are dangerous in acute ischemic stroke as shown by a J-shaped association between serum glucose and 24-hour and 12-month outcome. Initial serum glucose values between 3.7 and 7.3 mmol/L are associated with favorable outcome.

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INTRODUCTION: One quarter of osteoporotic fractures occur in men. TBS, a gray-level measurement derived from lumbar spine DXA image texture, is related to microarchitecture and fracture risk independently of BMD. Previous studies reported the ability of spine TBS to predict osteoporotic fractures in women. Our aim was to evaluate the ability of TBS to predict clinical osteoporotic fractures in men. METHODS: 3620 men aged ≥50 (mean 67.6years) at the time of baseline DXA (femoral neck, spine) were identified from a database (Province of Manitoba, Canada). Health service records were assessed for the presence of non-traumatic osteoporotic fracture after BMD testing. Lumbar spine TBS was derived from spine DXA blinded to clinical parameters and outcomes. We used Cox proportional hazard regression to analyze time to first fracture adjusted for clinical risk factors (FRAX without BMD), osteoporosis treatment and BMD (hip or spine). RESULTS: Mean followup was 4.5years. 183 (5.1%) men sustain major osteoporotic fractures (MOF), 91 (2.5%) clinical vertebral fractures (CVF), and 46 (1.3%) hip fractures (HF). Correlation between spine BMD and spine TBS was modest (r=0.31), less than correlation between spine and hip BMD (r=0.63). Significantly lower spine TBS were found in fracture versus non-fracture men for MOF (p<0.001), HF (p<0.001) and CVF (p=0.003). Area under the receiver operating characteristic curve (AUC) for incident fracture discrimination with TBS was significantly better than chance (MOF AUC=0.59, p<0.001; HF AUC=0.67, p<0.001; CVF AUC=0.57, p=0.032). TBS predicted MOF and HF (but not CVF) in models adjusted for FRAX without BMD and osteoporosis treatment. TBS remained a predictor of HF (but not MOF) after further adjustment for hip BMD or spine BMD. CONCLUSION: We observed that spine TBS predicted MOF and HF independently of the clinical FRAX score, HF independently of FRAX and BMD in men. Studies with more incident fractures are needed to confirm these findings.

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The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.

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A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

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Decision-making in an uncertain environment is driven by two major needs: exploring the environment to gather information or exploiting acquired knowledge to maximize reward. The neural processes underlying exploratory decision-making have been mainly studied by means of functional magnetic resonance imaging, overlooking any information about the time when decisions are made. Here, we carried out an electroencephalography (EEG) experiment, in order to detect the time when the brain generators responsible for these decisions have been sufficiently activated to lead to the next decision. Our analyses, based on a classification scheme, extract time-unlocked voltage topographies during reward presentation and use them to predict the type of decisions made on the subsequent trial. Classification accuracy, measured as the area under the Receiver Operator's Characteristic curve was on average 0.65 across 7 subjects. Classification accuracy was above chance levels already after 516 ms on average, across subjects. We speculate that decisions were already made before this critical period, as confirmed by a positive correlation with reaction times across subjects. On an individual subject basis, distributed source estimations were performed on the extracted topographies to statistically evaluate the neural correlates of decision-making. For trials leading to exploration, there was significantly higher activity in dorsolateral prefrontal cortex and the right supramarginal gyrus; areas responsible for modulating behavior under risk and deduction. No area was more active during exploitation. We show for the first time the temporal evolution of differential patterns of brain activation in an exploratory decision-making task on a single-trial basis.

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The objective of this work was to evaluate the effect of different drip irrigation regimes and planting densities on the incidence of the leaf miner, Leucoptera coffeella, in arabica coffee plants for one year. The experiment was carried out in 2008, in a complete randomized block design, in a split-plot in time arrangement, with four replicates. The treatments consisted of four drip irrigation regimes - soil water balance, irrigations at 20 and 60 kPa soil tensions, and a nonirrigated treatment -, which were distributed at three plant densities: 2, 500, 5, 000, and 10, 000 plants per hectare. The evaluations were made on a monthly basis between January and December 2008. The highest pest occurrence period was from August to November, a season with low-air relative humidity preceded by a drought period. Irrigated coffee plants showed an incidence of intact mines 2.2 times lower than that of nonirrigated plants. Irrigation and increasing of plant density contribute to the reduction of coffee leaf miner occurrence.

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Background: The Geneva Prognostic Score (GPS), the Pulmonary Embolism Severity Index (PESI), and its simplified version (sPESI) are well known clinical prognostic scores for pulmonary embolism (PE).Objectives: To compare the prognostic performance of these scores in elderly patients with PE. Patients/Methods: In a multicenter Swiss cohort of elderly patients with venous thromboembolism, we prospectively studied 449 patients aged ≥65 years with symptomatic PE. The outcome was 30-day overall mortality. We dichotomized patients as low- vs. higher-risk in all three scores using the following thresholds: GPS scores ≤2 vs. >2, PESI risk classes I-II vs. III-V, and sPESI scores 0 vs. ≥1. We compared 30-day mortality in low- vs. higher-risk patients and the areas under the receiver operating characteristic curve (ROC). Results: Overall, 3.8% of patients (17/449) died within 30 days. The GPS classified a greater proportion of patients as low risk (92% [413/449]) than the PESI (36.3% [163/449]) and the sPESI (39.6% [178/449]) (P<0.001 for each comparison). Low-risk patients based on the sPESI had a mortality of 0% (95% confidence interval [CI] 0-2.1%) compared to 0.6% (95% CI 0-3.4%) for low-risk patients based on the PESI and 3.4% (95% CI 1.9-5.6%) for low-risk patients based on the GPS. The areas under the ROC curves were 0.77 (95%CI 0.72-0.81), 0.76 (95% CI 0.72-0.80), and 0.71 (95% CI 0.66-0.75), respectively (P=0.47). Conclusions: In this cohort of elderly patients with PE, the GPS identified a higher proportion of patients as low-risk but the PESI and sPESI were more accurate in predicting mortality.

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AIMS: To validate a model for quantifying the prognosis of patients with pulmonary embolism (PE). The model was previously derived from 10 534 US patients. METHODS AND RESULTS: We validated the model in 367 patients prospectively diagnosed with PE at 117 European emergency departments. We used baseline data for the model's 11 prognostic variables to stratify patients into five risk classes (I-V). We compared 90-day mortality within each risk class and the area under the receiver operating characteristic curve between the validation and the original derivation samples. We also assessed the rate of recurrent venous thrombo-embolism and major bleeding within each risk class. Mortality was 0% in Risk Class I, 1.0% in Class II, 3.1% in Class III, 10.4% in Class IV, and 24.4% in Class V and did not differ between the validation and the original derivation samples. The area under the curve was larger in the validation sample (0.87 vs. 0.78, P=0.01). No patients in Classes I and II developed recurrent thrombo-embolism or major bleeding. CONCLUSION: The model accurately stratifies patients with PE into categories of increasing risk of mortality and other relevant complications. Patients in Risk Classes I and II are at low risk of adverse outcomes and are potential candidates for outpatient treatment.

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Background To determine the diagnostic and prognostic capability of urinary and tumoral syndecan-1 (SDC-1) levels in patients with cancer of the urinary bladder. Methods SDC-1 levels were quantitated by enzyme-linked immunosorbent assay (ELISA) in 308 subjects (102 cancer subjects and 206 non-cancer subjects) to assess its diagnostic capabilities in voided urine. The performance of SDC-1 was evaluated using the area under the curve of a receiver operating characteristic curve. In addition, immunohistochemical (IHC) staining assessed SDC-1 protein expression in 193 bladder specimens (185 cancer subjects and 8 non-cancer subjects). Outcomes were correlated to SDC-1 levels. Results Mean urinary levels of SDC-1 did not differ between the cancer subjects and the non-cancer subjects, however, the mean urinary levels of SDC-1 were reduced in high-grade compared to low-grade disease (p < 0.0001), and in muscle invasive bladder cancer (MIBC) compared to non-muscle invasive bladder cancer (NMIBC) (p = 0.005). Correspondingly, preliminary data note a shift from a membranous cellular localization of SDC-1 in normal tissue, low-grade tumors and NMIBC, to a distinctly cytoplasmic localization in high-grade tumors and MIBC was observed in tissue specimens. Conclusion Alone urinary SDC-1 may not be a diagnostic biomarker for bladder cancer, but its urinary levels and cellular localization were associated with the differentiation status of patients with bladder tumors. Further studies are warranted to define the potential role for SDC-1 in bladder cancer progression.

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Background To determine the diagnostic and prognostic capability of urinary and tumoral syndecan-1 (SDC-1) levels in patients with cancer of the urinary bladder. Methods SDC-1 levels were quantitated by enzyme-linked immunosorbent assay (ELISA) in 308 subjects (102 cancer subjects and 206 non-cancer subjects) to assess its diagnostic capabilities in voided urine. The performance of SDC-1 was evaluated using the area under the curve of a receiver operating characteristic curve. In addition, immunohistochemical (IHC) staining assessed SDC-1 protein expression in 193 bladder specimens (185 cancer subjects and 8 non-cancer subjects). Outcomes were correlated to SDC-1 levels. Results Mean urinary levels of SDC-1 did not differ between the cancer subjects and the non-cancer subjects, however, the mean urinary levels of SDC-1 were reduced in high-grade compared to low-grade disease (p < 0.0001), and in muscle invasive bladder cancer (MIBC) compared to non-muscle invasive bladder cancer (NMIBC) (p = 0.005). Correspondingly, preliminary data note a shift from a membranous cellular localization of SDC-1 in normal tissue, low-grade tumors and NMIBC, to a distinctly cytoplasmic localization in high-grade tumors and MIBC was observed in tissue specimens. Conclusion Alone urinary SDC-1 may not be a diagnostic biomarker for bladder cancer, but its urinary levels and cellular localization were associated with the differentiation status of patients with bladder tumors. Further studies are warranted to define the potential role for SDC-1 in bladder cancer progression.

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Falls are common in the elderly, and potentially result in injury and disability. Thus, preventing falls as soon as possible in older adults is a public health priority, yet there is no specific marker that is predictive of the first fall onset. We hypothesized that gait features should be the most relevant variables for predicting the first fall. Clinical baseline characteristics (e.g., gender, cognitive function) were assessed in 259 home-dwelling people aged 66 to 75 that had never fallen. Likewise, global kinetic behavior of gait was recorded from 22 variables in 1036 walking tests with an accelerometric gait analysis system. Afterward, monthly telephone monitoring reported the date of the first fall over 24 months. A principal components analysis was used to assess the relationship between gait variables and fall status in four groups: non-fallers, fallers from 0 to 6 months, fallers from 6 to 12 months and fallers from 12 to 24 months. The association of significant principal components (PC) with an increased risk of first fall was then evaluated using the area under the Receiver Operator Characteristic Curve (ROC). No effect of clinical confounding variables was shown as a function of groups. An eigenvalue decomposition of the correlation matrix identified a large statistical PC1 (termed "Global kinetics of gait pattern"), which accounted for 36.7% of total variance. Principal component loadings also revealed a PC2 (12.6% of total variance), related to the "Global gait regularity." Subsequent ANOVAs showed that only PC1 discriminated the fall status during the first 6 months, while PC2 discriminated the first fall onset between 6 and 12 months. After one year, any PC was associated with falls. These results were bolstered by the ROC analyses, showing good predictive models of the first fall during the first six months or from 6 to 12 months. Overall, these findings suggest that the performance of a standardized walking test at least once a year is essential for fall prevention.

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In order to establish guidelines for irrigation water management of banana cv. Pacovan (AAB group, Prata sub-group) in Petrolina County, northeastern Brazil, the root distribution and activity were measured on an irrigated plantation, in a medium texture soil, with plants spaced in a 3 x 3 m grid. Root distribution was evaluated by the soil profile method aided by digital image analysis, while root activity was indirectly determined by the changing of soil water content and by the direction of soil water flux. Data were collected since planting in January 1999 to the 3rd harvest in September 2001. Effective rooting depth increased from 0.4 m at 91 days after planting (dap), to 0.6 m at 370, 510, and 903 dap, while water absorption by roots was predominantly in the top 0,6 m.

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PURPOSE: To identify risk factors associated with mortality in patients with severe community-acquired pneumonia (CAP) caused by S. pneumoniae who require intensive care unit (ICU) management, and to assess the prognostic values of these risk factors at the time of admission. METHODS: Retrospective analysis of all consecutive patients with CAP caused by S. pneumoniae who were admitted to the 32-bed medico-surgical ICU of a community and referral university hospital between 2002 and 2011. Univariate and multivariate analyses were performed on variables available at admission. RESULTS: Among the 77 adult patients with severe CAP caused by S. pneumoniae who required ICU management, 12 patients died (observed mortality rate 15.6 %). Univariate analysis indicated that septic shock and low C-reactive protein (CRP) values at admission were associated with an increased risk of death. In a multivariate model, after adjustment for age and gender, septic shock [odds ratio (OR), confidence interval 95 %; 4.96, 1.11-22.25; p = 0.036], and CRP (OR 0.99, 0.98-0.99 p = 0.034) remained significantly associated with death. Finally, we assessed the discriminative ability of CRP to predict mortality by computing its receiver operating characteristic curve. The CRP value cut-off for the best sensitivity and specificity was 169.5 mg/L to predict hospital mortality with an area under the curve of 0.72 (0.55-0.89). CONCLUSIONS: The mortality of patients with S. pneumoniae CAP requiring ICU management was much lower than predicted by severity scores. The presence of septic shock and a CRP value at admission <169.5 mg/L predicted a fatal outcome.