Structural model optimization using statistical evaluation

The results of research in applying statistical methods to the problem of structural dynamic system identification are presented. The study is in three parts: a review of previous approaches by other researchers, a development of various linear estimators which might find application, and the design and development of a computer program which uses a Bayesian estimator. The method is tried on two models and is successful where the predicted stiffness matrix is a proper model, e.g., a bending beam is represented by a bending model. Difficulties are encountered when the model concept varies. There is also evidence that nonlinearity must be handled properly to speed the convergence

Magneto-elastic oscillations of neutron stars: exploring different magnetic field configurations

We study magneto-elastic oscillations of highly magnetized neutron stars (magnetars) which have been proposed as an explanation for the quasi-periodic oscillations (QPOs) appearing in the decaying tail of the giant flares of soft gamma-ray repeaters (SGRs). We extend previous studies by investigating various magnetic field configurations, computing the Alfv\'en spectrum in each case and performing magneto-elastic simulations for a selected number of models. By identifying the observed frequencies of 28 Hz (SGR 1900+14) and 30 Hz (SGR 1806-20) with the fundamental Alfv\'en QPOs, we estimate the required surface magnetic field strength. For the magnetic field configurations investigated (dipole-like poloidal, mixed toroidal-poloidal with a dipole-like poloidal component and a toroidal field confined to the region of field lines closing inside the star, and for poloidal fields with an additional quadrupole-like component) the estimated dipole spin-down magnetic fields are between 8x10^14 G and 4x10^15 G, in broad agreement with spin-down estimates for the SGR sources producing giant flares. A number of these models exhibit a rich Alfv\'en continuum revealing new turning points which can produce QPOs. This allows one to explain most of the observed QPO frequencies as associated with magneto-elastic QPOs. In particular, we construct a possible configuration with two turning points in the spectrum which can explain all observed QPOs of SGR 1900+14. Finally, we find that magnetic field configurations which are entirely confined in the crust (if the core is assumed to be a type I superconductor) are not favoured, due to difficulties in explaining the lowest observed QPO frequencies (f<30 Hz).Comment: 21 pages, 16 figures, 6 tables, matched to version accepted by MNRAS with extended comparison/discussion to previous wor

Oidium longipes, a new powdery mildew fungus on petunia in the USA: A potential threat to ornamental and vegetable solanaceous crops

This is the first North American report of Oidium longipes, an anamorphic powdery mildew species described recently in Europe. It was found on vegetatively propagated petunia grown in a commercial greenhouse in New Jersey, USA, where it caused a rapidly spreading disease. The pathogen might have originated offshore and may have already been distributed in the United States through horticultural trade. During field surveys in Europe, it was found on petunia in Hungary and Austria as well; this is the first report of O. longipes from these two countries. A detailed light microscopy study of American and European specimens of O. longipes, including freshly collected samples and authentic herbarium specimens, revealed that its conidiophore morphology is more variable than illustrated in the original species description or in subsequent works. Microcycle conidiation, a process not yet known to occur in powdery mildews, was repeatedly observed in O. longipes. The rDNA internal transcribed spacer (ITS) sequences were identical in colonies containing different conidiophore types as well as in a total of five specimens collected from petunia in the United States, Austria, Hungary, Germany, and Switzerland. A phylogenetic analysis of the ITS sequences revealed that the closest known relative of O. longipes is O. lycopersici, known to infect tomato only in Australia. Cross-inoculation tests showed that O. longipes from petunia heavily infected tobacco cv. Xanthi, while the tomato and eggplant cultivars tested were moderately susceptible to this pathogen. These results indicate that its spread represents a potential danger to a number of solanaceous crops. Our ad hoc field surveys conducted in 2006 and 2007 did not detect it outside New Jersey in the United States; all the other powdery mildew–infected petunias, collected in New York and Indiana, were infected by Podosphaera xanthii. In Europe, most of the powdery mildew–infected petunias examined in this study were infected by P. xanthii or Golovinomyces orontii. Our multiple inoculation tests revealed that the same petunia plants and even the same leaves can be infected concomitantly by O. longipes, O. neolycopersici, G. orontii, and P. xanthii. Thus, it is at present unclear to what extent O. longipes contributes to the powdery mildew epidemics that develop year after year on solanaceous plants in many parts of the world

Effect of immune system stimulation and divergent selection for residual feed intake on digestive capacity of the small intestine in growing pigs

Residual feed intake (RFI) is a measure of feed efficiency that reflects differences in the efficiency of the use of feed for maintenance and growth. The consequences of genetic selection for RFI on intestinal nutrient digestion capacity, particularly during immune system stimulation (ISS), are poorly documented. Our objective was to evaluate the impact of ISS and genetic selection for RFI on apparent ileal digestibility (AID) of nutrients, and intestinal nutrient transport and barrier function

A crystallographically isolated dimeric hydrolyzed chloro­phosphazene dianion

Single crystals of the title compound bis[bis­(1-ethyl-3-methyl-imidazol-2-yl­idene)silver(I)] 1,5,5,7,11,11-hexa­chloro-2,8-di­oxa-4,6,10,12,13,14-hexa­aza-1λ5,3,5λ5,7λ5,9,11λ5-hexa­phospha­tricyclo­[7.3.1.13,7]tetra­deca-1(13),4,7(14),10-tetra­ene-6,12-diide 3,9-dioxide, [Ag(C6H10N2)2](Cl6N6O4P6)0.5, were isolated from the reaction of the silver N-heteocyclic carbene complex [Ag(C6H10N2)2]Cl and hexa­chloro­cyclo­triphos­phazene [NPCl2]3 in the presence of water. The asymmetric unit contains one silver carbene cation with the carbene ligands bound to the Ag(I) in an almost linear arrangement and one half of a hydrolyzed phosphazene dianion. The second cation and additional half of the anion are generated by an inversion center

An empirical analysis of the cost of rearing dairy heifers from birth to first calving and the time taken to repay these costs

Rearing quality dairy heifers is essential to maintain herds by replacing culled cows. Information on the key factors influencing the cost of rearing under different management systems is, however, limited and many farmers are unaware of their true costs. This study determined the cost of rearing heifers from birth to first calving in Great Britain including the cost of mortality, investigated the main factors influencing these costs across differing farming systems and estimated how long it took heifers to repay the cost of rearing on individual farms. Primary data on heifer management from birth to calving was collected through a survey of 101 dairy farms during 2013. Univariate followed by multivariable linear regression was used to analyse the influence of farm factors and key rearing events on costs. An Excel spreadsheet model was developed to determine the time it took for heifers to repay the rearing cost. The mean +/- SD ages at weaning, conception and calving were 62 +/- 13, 509 +/- 60 and 784 +/- 60 days. The mean total cost of rearing was 1819 pound +/- 387/heifer with a mean daily cost of 2.31 pound +/- 0.41. This included the opportunity cost of the heifer and the mean cost of mortality, which ranged from 103.49 pound to 146.19 pound/surviving heifer. The multivariable model predicted an increase in mean cost of rearing of 2.87 pound for each extra day of age at first calving and a decrease in mean cost of 6.06 pound for each percentile increase in time spent at grass. The model also predicted a decrease in the mean cost of rearing in autumn and spring calving herds of 273.20 pound and 288.56 pound, respectively, compared with that in all-year-round calving herds. Farms with herd sizes100 had lower mean costs of between 301.75 pound and 407.83 pound compared with farms with <100 milking cows. The mean gross margin per heifer was 441.66 pound +/- 304.56 (range 367.63 pound to 1120.08) pound, with 11 farms experiencing negative gross margins. Most farms repaid the cost of heifer rearing in the first two lactations (range 1 to 6 lactations) with a mean time from first calving until breaking even of 530 +/- 293 days. The results of the economic analysis suggest that management decisions on key reproduction events and grazing policy significantly influence the cost of rearing and the time it takes for heifers to start making a profit for the farm

The basophil activation test differentiates between patients with wheat-dependent exercise-induced anaphylaxis and control subjects using gluten and isolated gluten protein types

Background: Oral food challenge using gluten and cofactors is the gold standard to diagnose wheat-dependent exercise-induced anaphylaxis (WDEIA), but this procedure puts patients at risk of an anaphylactic reaction. Specific IgE to ω5-gliadins as major allergens and skin prick tests to wheat may yield negative results. Thus, we designed a proof-of-principle study to investigate the utility of the basophil activation test (BAT) for WDEIA diagnosis. Methods: Different gluten protein types (GPT; α-, γ-, ω1,2- and ω5-gliadins, high-molecular-weight glutenin subunits [HMW-GS] and low-molecular-weight glutenin subunits [LMW-GS]) and gluten were used in different concentrations to measure basophil activation in 12 challenge-confirmed WDEIA patients and 10 control subjects. The results were compared to routine allergy diagnostics. Parameters analyzed include the percentage of CD63+ basophils, the ratio of %CD63+ basophils induced by GPT/gluten to %CD63+ basophils induced by anti-FcεRI antibody, area under the dose-response curve and test sensitivity and specificity. Results: GPT and gluten induced strong basophil activation for %CD63+ basophils and for %CD63+/anti-FcɛRI ratio in a dose-dependent manner in patients, but not in controls (p < 0.001, respectively). BAT performance differed from acceptable (0.73 for LMW-GS) to excellent (0.91 for ω5-gliadins) depending on the specific GPT as evaluated by the area under the receiver operating characteristic curve. Patients showed individual sensitization profiles. After determination of the best cut-off points, ω5-gliadins and HMW-GS showed the best discrimination between patients and controls with a sensitivity/specificity of 100/70 and 75/100, respectively. Conclusion: This study shows the alternative role of BAT in better defining WDEIA and the causative wheat allergens. The best BAT parameters to distinguish WDEIA patients from controls were %CD63+ basophil values for ω5-gliadins and HMW-GS

New, emerging and re-emerging fungal diseases on medicinal and aromatic plants in European domain

Plant diseases cause agricultural and economic loss and impact negatively on human and animal health through mycotoxins and allergens produced by them. They also have consequences for biodiversity conservation. The pathogens could be classified in five categories: new - detected within the last five years; emerging - have always been present in an area but have grown in importance over the years; re-emerging - have been previously controlled but are once more a major problem associated with chemical resistance or changes in management or cultivars; threatening - not reported or limited in distribution in Europe and chronic-spreading – known for longer than 20 years and causing increased concern. Diseases emerge or re-emerge due to changes in farming practices, development of new strains of the pathogen, climate change, introduction of the pathogen to new geographical locations, or introduction of more efficient pathogen vectors. During the last years emerging infectious diseases (EIDs) are of special concern to researchers. Among all pathogens fungi are responsible for the greatest damage to plants in both agricultural and natural ecosystems. They represent over 70 % of all plant pathogens and over 30 % of plant EIDs. Surveys on fungal diseases of medicinal and aromatic plants have been carried out in the framework of several research projects between Germany, Bulgaria, Lithuania and Poland in the last two decades. EIDs have been reported, either as novel pathogens or as familiar pathogens affecting new host species. The importance of the problem could be illustrated by such examples as some phytopathogenic fungi on Apiaceae and Lamiaceae hosts discussed in the present work

Protein sequence analysis using the MPI Bioinformatics Toolkit

The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) provides interactive access to a wide range of the best‐performing bioinformatics tools and databases, including the state‐of‐the‐art protein sequence comparison methods HHblits and HHpred. The Toolkit currently includes 35 external and in‐house tools, covering functionalities such as sequence similarity searching, prediction of sequence features, and sequence classification. Due to this breadth of functionality, the tight interconnection of its constituent tools, and its ease of use, the Toolkit has become an important resource for biomedical research and for teaching protein sequence analysis to students in the life sciences. In this article, we provide detailed information on utilizing the three most widely accessed tools within the Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets. Basic Protocol 1: Sequence similarity searching using HHpred Alternate Protocol: Pairwise sequence comparison using HHpred Support Protocol: Building a custom multiple sequence alignment using PSI‐BLAST and forwarding it as input to HHpred Basic Protocol 2: Calculation of homology models using HHpred and MODELLER Basic Protocol 3: Cluster analysis using CLAN