Our objective was to identify weather-based variables in pre- and post-anthesis time windows for predicting major Fusarium head blight (FHB) epidemics (defined as FHB severity ≥ 10%) in the United ...States. A binary indicator of major epidemics for 527 unique observations (31% of which were major epidemics) was linked to 380 predictor variables summarizing temperature, relative humidity, and rainfall in 5-, 7-, 10-, 14-, or 15-day-long windows either pre- or post-anthesis. Logistic regression models were built with a training data set (70% of the 527 observations) using the leaps-and-bounds algorithm, coupled with bootstrap variable and model selection methods. Misclassification rates were estimated on the training and remaining (test) data. The predictive performance of models with indicator variables for cultivar resistance, wheat type (spring or winter), and corn residue presence was improved by adding up to four weather-based predictors. Because weather variables were intercorrelated, no single model or subset of predictor variables was best based on accuracy, model fit, and complexity. Weather-based predictors in the 15 final empirical models selected were all derivatives of relative humidity or temperature, except for one rainfall-based predictor, suggesting that relative humidity was better at characterizing moisture effects on FHB than other variables. The average test misclassification rate of the final models was 19% lower than that of models currently used in a national FHB prediction system.
Predicting Winter Wheat Heading Date Zhao, H. D.; Sassenrath, G. F.; Zambreski, Z. T. ...
Journal of applied meteorology and climatology,
12/2021, Letnik:
60, Številka:
12
Journal Article
Recenzirano
Accurate prediction of winter wheat (Triticum aestivum L.) heading date is important for determining the potential incidence of diseases and abiotic stresses such as freeze or heat events. Wheat ...phenological modeling requires cultivar- and crop-zone-specific vernalization and photoperiod knowledge. Previous models applied in Kansas showed that the uncertainties of predicting heading date were large and could be improved. In this study, a modification to the Scientific Impact Assessment and Modeling Platform for Advanced Crop and Ecosystem Management (SIMPLACE) model was developed and implemented to improve the accuracy of winter wheat heading date estimation. The cultivar- and crop-zone-specific model parameters were calculated using a Markov chain Monte Carlo simulation. The modified models were calibrated by using the longest observation site to cover all cultivars planted in each crop zone. Model performance was then evaluated for seven winter wheat cultivars at eight experiment sites distributed across four crop zones in Kansas. Our modified model (MS) had a root-mean-square error (RMSE) between predicted and observed heading date of 4 days, which reflects an improved accuracy by 5–8 days on average compared to the Agricultural Production Systems Simulator (APSIM) or the original SIMPLACE models. There was a clear correlation between the uncertainty of the modeled heading date and the sowing date in previous models. Our modified model demonstrates that integrating nonlinear temperature response functions, temperature stress factors, and sowing date information improved prediction of the heading date in winter wheat across Kansas.
This book gives a comprehensive account of the development and present status of the field of soft (i.e. non-perturbative) phenomena encountered in the production of (multi-) hadronic final states by ...the collision of various types of particles at high energies. Phenomenological models used to describe the data are in general inspired by Quantum Chromo Dynamics (QCD) and the book repeatedly crosses the border — if at all existent — between soft (non-perturbative) and hard (perturbative) QCD.
Epidemics are often triggered by specific weather patterns favouring the pathogen on susceptible hosts. For plant diseases, models predicting epidemics have therefore often emphasized the ...identification of early season weather patterns that are correlated with a disease outcome at some later point. Toward that end, window-pane analysis is an exhaustive search algorithm traditionally used in plant pathology for mining correlations in a weather series with respect to a disease endpoint. Here we show, with reference to Fusarium head blight (FHB) of wheat, that a functional approach is a more principled analytical method for understanding the relationship between disease epidemics and environmental conditions over an extended time series. We used scalar-on-function regression to model a binary outcome (FHB epidemic or non-epidemic) relative to weather time series spanning 140 days relative to flowering (when FHB infection primarily occurs). The functional models overall fit the data better than previously described standard logistic regression (lr) models. Periods much earlier than heretofore realized were associated with FHB epidemics. The findings were used to create novel weather summary variables which, when incorporated into lr models, yielded a new set of models that performed as well as existing lr models for real-time predictions of disease risk. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.
Studies conflict on the significance of burn-induced coagulopathy. We posit that burn-induced coagulopathy is associated with injury severity in burns. Our purpose was to characterize coagulopathy ...profiles in burns and determine relationships between % total burn surface area (TBSA) burned and coagulopathy using the International Normalized Ratio (INR). Burned patients with INR values were identified in the TriNetX database and analyzed by %TBSA burned. Patients with history of transfusions, chronic hepatic failure, and those on anticoagulant medications were excluded. Interquartile ranges for INR in the burned study population were 1.2 (1.0-1.4). An INR of ≥ 1.5 was used to represent those with burn-induced coagulopathy as it fell outside the 3rd quartile. The population was stratified into subgroups using INR levels <1.5 or ≥1.5 on the day of injury. Data are average ± SD analyzed using chi-square; p < .05 was considered significant. There were 7,364 burned patients identified with INR <1.5, and 635 had INR ≥1.5. Comparing TBSA burned groups, burn-induced coagulopathy significantly increased in those with ≥20% TBSA; p = .048 at 20-29% TBSA, p = .0005 at 30-39% TBSA, and p < .0001 for 40% TBSA and above. Age played a significant factor with average age for those with burn-induced coagulopathy 59 ± 21.5 years and 46 ± 21.8 for those without (p < .0001). After matching for age, TBSA, and demographics, the risk of 28 day-mortality was higher in those with burn-induced coagulopathy compared to those without (risk difference 20.9%, p < .0001) and the odd ratio with 95% CI is 4.45 (3.399-5.825). Investigation of conditions associated with burn-induced coagulopathy showed the effect of heart diseases to be significant; 53% of patients with burn-induced coagulopathy had hypertension (p < .0001). Burn-induced coagulopathy increases with %TBSA burned. The information gained firmly reflects a link between %TBSA and burn-induced coagulopathy, which could be useful in prognosis and treatment decisions.
High-temperature electrolysis using solid oxide electrolysis cells (SOECs) is an innovative technology to temporarily store unused electrical energy from renewable energy sources. However, they show ...continuous performance loss during long-term operation, which is the main issue preventing their widespread use. In this work, we have performed the long-term stability tests up to 1000 h under steam and co-electrolysis conditions using commercial NiO-YSZ/YSZ/GDC/LSC single cells in order to understand the degradation process. The electrolysis tests were carried out at different temperatures and fuel gas compositions. Intermittent AC- and DC- measurements were performed to characterize the single cells and to determine the responsible electrode processes for the degradation during long-term operation. An increased degradation rate is observed at 800 °C compared to 750 °C under steam electrolysis conditions. Moreover, a lower degradation rate is noticed under co-electrolysis operation in comparison to steam electrolysis operation. Finally, the post-test analyses using SEM-EDX and XRD were carried out in order to understand the degradation mechanism. The delamination of LSC is observed under steam electrolysis conditions at 800 °C, however, such delamination is not observed during co-electrolysis operation. In addition, Ni-depletion and agglomeration are observed on the fuel electrode side for all the cells.
Body awareness has been proposed as one of the major mechanisms of mindfulness interventions, and it has been shown that chronic pain and depression are associated with decreased levels of body ...awareness. We investigated the effect of Mindfulness-Based Cognitive Therapy (MBCT) on body awareness in patients with chronic pain and comorbid active depression compared to treatment as usual (TAU; N = 31). Body awareness was measured by a subset of the Multidimensional Assessment of Interoceptive Awareness (MAIA) scales deemed most relevant for the population. These included: Noticing, Not-Distracting, Attention Regulation, Emotional Awareness, and Self-Regulation. In addition, pain catastrophizing was measured by the Pain Catastrophizing Scale (PCS). These scales had adequate to high internal consistency in the current sample. Depression severity was measured by the Quick Inventory of Depressive Symptomatology-Clinician rated (QIDS-C16). Increases in the MBCT group were significantly greater than in the TAU group on the "Self-Regulation" and "Not Distracting" scales. Furthermore, the positive effect of MBCT on depression severity was mediated by "Not Distracting." These findings provide preliminary evidence that a mindfulness-based intervention may increase facets of body awareness as assessed with the MAIA in a population of pain patients with depression. Furthermore, they are consistent with a long hypothesized mechanism for mindfulness and emphasize the clinical relevance of body awareness.
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