A new class of matrices with positive inverses

It is well known that irreducibly diagonally- dominant matrices with positive diagonal and non-positive off-diagonal elements have positive inverses. A whole class of symmetric circulant and symmetric quindiagonal Toeplitz matrices with positive inverses which do not satisfy the above conditions is found

Unusual association of ST-T abnormalities, myocarditis and cardiomyopathy with H1N1 influenza in pregnancy: two case reports and review of the literature.

Introduction Myocarditis is rarely reported as an extra-pulmonary manifestation of influenza while pregnancy is a rare cause of cardiomyopathy. Pregnancy was identified as a major risk factor for increased mortality and morbidity due to H1N1 influenza in the pandemic of 2009 to 2010. However, to the best of our knowledge there are no previous reports in the literature linking H1N1 with myocarditis in pregnancy. Case presentation We report the cases of two pregnant Caucasian women (aged 29 and 30), with no pre-existing illness, presenting with respiratory manifestations of H1N1 influenza virus infection in their third trimester. Both women developed evidence of myocarditis. One woman developed acute respiratory distress syndrome, almost reaching the point of requiring extra-corporeal membrane oxygenation, and subsequently developed persistent cardiomyopathy; the other recovered without any long-term consequence. Conclusions While it is not possible to ascertain retrospectively if myocarditis was caused by either infection with H1N1 virus or as a result of pregnancy (in the absence of endomyocardial biopsies), the significant association with myocardial involvement in both women demonstrates the increased risk of exposure to H1N1 influenza virus in pregnant women. This highlights the need for health care providers to increase awareness amongst caregivers to target this 'at risk' group aggressively with vaccination and prompt treatment

DAILY SOLAR RADIATION ESTIMATED FROM TKMPERA TURE RECORDS

Crop growth models and other environmental analyses require the input of daily global solar radiation values. Unfortunately many locations lack long-term solar radiation data. Most agricultural experiment stations, however, have daily temperature records. Also they are often the locations for which crop growth simulations are conducted. In an unpublished manuscript in the field of agricultural meteorology, researchers wanted to address this need. Specifically they wanted to estimate historical daily global solar radiation using daily air temperature data records by adapting a single published empirical intrinsically nonlinear model, a form of the Weibull curve. In order to help future research in the given field, this paper argues that the selected model is a poor choice. Two independent long-term data sets that come from a similar climate to that of the researchers\u27 are used, one for model development and the other for testing model prediction. Through the use of performance statistics on the cross-validation, three alternative models are offeredfor comparison (the performance statistics are accepted by researchers in the agricultural meteorology discipline). The results give no reason to favor the researchers\u27 selected model. Furthermore no model performed well under advective conditions. Future research should consider finding a better means to account for advection, developing and evaluating other models, and justifying the assumptions of the methodology to be employed

Direct to consumer advertising via the Internet, a study of hip resurfacing

With increased use of the internet for health information and direct to consumer advertising from medical companies, there is a concern about the quality of the information available for patients. The aim of this study was to examine the quality of health information on the internet for hip resurfacing. An assessment tool was designed to measure quality of information. Websites were measured on credibility of source; usability; currentness of the information; content relevance; content accuracy/completeness and disclosure/bias. Each website assessed was given a total score, based on number of scores achieved from the above categories websites were further analysed on author, geographical origin and possession of an independent credibility check. There was positive correlation between the overall score for the website and the score of each website in each assessment category. Websites by implant companies, doctors and hospitals scored poorly. Websites with an independent credibility check such as Health on the Net (HoN) scored twice the total scores of websites without. Like other internet health websites, the quality of information on hip resurfacing websites is variable. This study highlights methods by which to assess the quality of health information on the internet and advocates that patients should look for a statement of an "independent credibility check" when searching for information on hip resurfacing

SUGGESTIONS FOR PRESENTING KRIGING RESULTS

Kriging maps are often part of the reported analyses in many environmental research studies including those our agency is working on in the area of precision/sustainable farming. All to often important details on the underlying variography and/or kriging procedures are omitted. Likewise the content and form of presenting kriging results vary greatly. Often features of the underlying variability are not readily seen. Instead of reviewing poor practice in current literature, we offer guidelines for reporting the methodology and presenting the results with the use of soil test phosphorus (STP) measures from a real world pasture study. Relevantly, the stationarity assumption for the variogram is argued; computational aspects for both the model and empirical variogram development are reported; and similarly, computational aspects for the kriging surface are reported. In short, enough detail is reported to understand and reproduce the analyses. Standard practice for presenting kriging results should include both the kriging estimates and the associated standard error map. Various planar and three dimensional plots are shown and discussed. Emphasis is on developing quality gray-scale planar maps for conventional publications. Ideally, for both recommended plots, patterns and unique features of the surfaces\u27 variability are revealed

AN EXAMPLE OF DEVELOPING COVARIATES FOR PROBLEMS IN PRECISION AGRICULTURE

Methodology for precision agriculture is, perhaps, too focused on methods that allow for spatial correlation in the ANOVA error term. While sound inference about differences between local yields can be computed, no understanding of what is driving these differences is achieved. A completely general form for a spatial model can include suitable covariates. Most research in precision agriculture includes gathering a variety of site-specific information. Through the presentation of the analysis of data from a published soybean [Glycine max (L.) Merr.] study, one specific type of covariate is developed - a duration index for soybean canopy light interception over the growing season. The relationship of the index to grain yield is reasonably well determined (R² = 0.82). We, therefore, suggest that the quest for modeling an appropriate covariate or covariates is primary. Treating spatial variation by other methods should only be used when the quest has failed

SMAF: A Soil Health Assessment Tool

The Soil Management Assessment Framework (SMAF) was developed to help quantify soil quality/health effects of tillage, crop rotation, and other soil management practices. Our objective was to determine if the SMAF could detect soil health differences after growing a single winter triticale (X Triticosecale Wittmack) crop. Soil samples were collected from 0 to 7.5- and 7.5 to 15- cm depth increments during the 2003 – 2004 and 2004 – 2005 growing seasons near Ames and Lewis, IA, and analyzed for several potential soil quality indicators. The SMAF analysis showed higher soil quality ratings for surface than subsurface samples. It also showed that a single winter grain crop can significantly improve soil quality after either corn (Zea mays L.) or soybean (Glycine max [L.] Merr.). Finally, in response to increasing interest in soil health assessments, a detailed appendix is attached to provide guidance for future soil health assessments

SPECTRAL PROCEDURES ENHANCE THE ANALYSIS OF THREE AGRICULTURAL TIME SERIES

Many agricultural and environmental variables are influenced by cyclic processes that occur naturally. Consequently their time series often have cyclic behavior. This study develops time series models for three different phenomena: (1) a 60 year-long state annual average crop yield record, (2) a four year-long daily stream flow record with values aggregated to weekly averages, and (3) a half-hour long wind speed record sampled at 10 hertz with values aggregated to 0.5 min averages. Trend tests, simple high pass filtering, and spectral analysis on original and detrended and residual data series are used to guide model development. Next, as a means to provide insight for researchers, nonlinear regression procedures are used to develop models in the time domain. The models considered may have a large scale trend, low to high frequency cycles, and, if need be, an autoregressive (AR) error structure. Selected models for all three sets included a trend component. The model for yield has a linear trend in time and includes two high frequency cycles of 2.3 and 2.5 years. The model for stream flow has a complicated trend consisting of splined polynomials in the square root of time. Cycles include an annual and approximately 8, 6, and 3 month periods. Also an AR1 error structure is added. Results suggest the wind speed can be modeled as a superposition of damped and undamped oscillations. A zero order fractional Bessel function models the trend, here a damped oscillation with a period of 10.5 min. Smaller scale regular cycles of 6.6, 3.3 and 2.2 min are added along with an AR1 error structure. The use of time series methods instead of the inverse transform on selected frequencies allows for simultaneous estimation of all components. Moreover it opens the door to the use of a much broader class of functions to model the trend, to the use of other kinds of periodic functions to model the cycles, and to the incorporation of structure in the error term. This approach may provide useful insight and a methodological approach for several ongoing and some future studies at the National Soil Tilth Laboratory

Technical study of a rare Venetian turquoise glass goblet from the Waddesdon Bequest

A Venetian enamelled and gilded goblet (WB.55) is part of the collection bequeathed to the British Museum by Baron Ferdinand Rothschild in 1898. Conservation treatment in 1994 provided the opportunity to remove a small sample containing some opaque white as well as rare turquoise glass. These fragments were analysed using scanning electron microscopy with energy dispersive X-ray spectrometry and by laser ablation inductively coupled plasma mass spectrometry. Further analyses were carried out on the enamels and blue glass knop of the goblet using surface X-ray fluorescence. This contribution locates the object in the context of Venetian glass of the Renaissance as well as the history of collecting. The conservation history and the processes employed to conserve the object prior to its redisplay in the new Waddesdon Gallery at the British Museum in 2015 are described. Careful macroscopic and microscopic observations are combined with the chemical analyses to outline a comprehensive chaîne opératoire for the object. Technically, it is fully consistent with current understanding of glass production in Venice in the late fifteenth century

AN AUTOREGRESSION MODEL FOR A PAIRED WATERSHED COMPARISON

Analysis of water quality data from a paired watershed design is needed to determine if a best fertilizer management practice reduces a specific water quality variable compared to a conventional fertilizer management practice. This study examines an existing recommended method of analysis for paired watershed designs, simple analysis of covariance (ANCOVA) on time aggregated data, then offers two autoregression analyses (AR) as alternatives. The first approach models the sequence of paired differences and estimates its 95% confidence band. The second approach develops individual watershed AR models then examines the joint 95% confidence interval about the predicted difference. A reliability analysis on the water quality data reveals that the data for the controlled watershed, i.e., the covariate, has a sizable measurement error, a factor that is not considered in the usual ANCOVA model. The AR methods avoid the measurement error and other inherent problems with the published recommended method. Graphically both AR analyses are similar and reveal three distinct trend phases: a period of continued similarity; a period of transition; and a period of sustained change. The model for the sequence of paired differences is the easier one of the two AR methods to use and interpret because its trend model of splined linear segments readily defines each response phase. Hence, we recommend it over the given alternatives. It offers water resources researchers an effective and readily adoptable analysis option