187,010 research outputs found
Tozer et al., (2019) SRTM15+ GMT Grids
No full textA zip file containing the datasets described in Section 5 of Tozer et al., (2019) in NetCDF GMT (.nc) grid file format.Contains the following grids:1. SRTM15+V2.nc : 2.7 gb; 32-bit int; 15 arc sec global bathymetry & topography; +/- 90 deg2. SID_GRID_SRTM15+V2.0.nc : 287 mb ; 32-bit int ; 15 arc sec SID grid; +/- 90 deg3. SRTM15_V2-V1_difference.nc ; 3.0 gb ; 32-bit int ; 15 arc sec elevation change V2-V1; +/- 90 deg4. Marine_FA_gravity_27-1.nc ; 422 mb ; 32-bit float ; 1 arc min marine free-air gravity anomalies; +/- 80 deg5. Marine_VGG_V27-1.nc 452 mb ; 32-bit float ; 1 arc min marine vertical gravity gradients; +/- 80 deg6. GRAV-TOPO_CORR_COEFF_V27-1.nc ; 32-bit float ; 2 arc min (sampling) gravity:topography correlation coefficient; +/- 80 deg7. 1MIN_TOPO_V19.nc ; 32-bit int; 1 arc min bathymetry & topography; +/- 80 deg</p
Deferred grazing for quality and rejuvenation
No full textFarmers use deferred grazing to maintain pasture quality at farm-scale, rejuvenate pastures and to provide drought feed.How do you do it?Exclude stock 12-16 weeks: November – FebruaryUp to 10-15% of farm depending on the farm / yearAllow desirable perennial species to set and drop seedAim for about 50% utilisation when grazing deferred pasture at end of summerPresentation for Our Land and WaterDeferred Grazing and Regenerative Farming – Katherine Tozer, AgResearchKatherine Tozer has worked on a variety of projects in the deferred grazing & regenerative space including looking at the effects of meat taste, summer forage options and how deferred grazing could offer pasture improvement and management advantages.</p
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Deferred grazing for quality and rejuvenation
No full textFarmers use deferred grazing to maintain pasture quality at farm-scale, rejuvenate pastures and to provide drought feed.How do you do it?Exclude stock 12-16 weeks: November – FebruaryUp to 10-15% of farm depending on the farm / yearAllow desirable perennial species to set and drop seedAim for about 50% utilisation when grazing deferred pasture at end of summerPresentation for Our Land and WaterDeferred Grazing and Regenerative Farming – Katherine Tozer, AgResearchKatherine Tozer has worked on a variety of projects in the deferred grazing & regenerative space including looking at the effects of meat taste, summer forage options and how deferred grazing could offer pasture improvement and management advantages.</p
Predictive Performance of the Winter–Tozer and Derivative Equations for Estimating Free Phenytoin Concentration
No full textABSTRACTBackground: The Winter–Tozer equation for estimating free phenytoin concentration is biased and imprecise. Alternative predictive equations are available, but most remain unvalidated.Objectives: To assess the bias and precision of the Winter–Tozer equation and selected derivative equations in predicting free phenytoin concentration and to derive new equations with better predictive performance.Methods: A retrospective chart review (for patients with samples drawn for free phenytoin concentration between September 2008 and September 2013) was conducted for 3 subpopulations (critical care, general medicine, neurology) in one hospital. Patients were included if older than 18 years with values for free phenytoin concentration available and were excluded if phenytoin was not at steady state or if they were undergoing hemodialysis or receiving enzyme inhibitors or inducers that would affect phenytoin clearance. The predictive performance measures used were mean prediction error (MPE), root mean square error, and Bland–Altman plots. Spearman rank correlation and multiple linear regression were performed with log-transformed data.Results: In total, 133 patients were included (70 men [53%]; mean age ± standard deviation 64 ± 19 years; serum creatinine 90.4 ± 64.0 μmol/L; albumin 26.4 ± 7.0 g/L). In the combined population, the Winter–Tozer equation (MPE 1.7 μmol/L, 95% confidence interval [CI] 1.5 to 1.9) and the Anderson equation (MPE 0.5 μmol/L, 95% CI 0.3 to 0.7) overpredicted free phenytoin concentration, whereas the first Kane equation tended to underpredict free phenytoin (MPE –0.2 μmol/L, 95% CI –0.4 to 0.0), and the second Kane equation significantly underpredicted free phenytoin (MPE –0.3 μmol/L, 95% CI –0.5 to –0.1). In each subpopulation, the Winter–Tozer equation overpredicted true concentration with greater bias and imprecision. All equations performed poorly in the critical care subpopulation. Only albumin (R2 = 0.09) and total phenytoin concentration (R2 = 0.53) were correlated with free phenytoin concentration. The equation derived by multiple linear regression exhibited significantly less bias and imprecision than the Winter–Tozer equation in the validation set (p < 0.05). A new, user-friendly equation, specific to the authors’ patient population, was derived, which had an albumin coefficient of 0.275.Conclusions: Relatively poor predictive performance of the Winter–Tozer and derivative equations calls for more precise and less biased equations. The novel equations presented here, which had better predictive performance for free phenytoin concentration and were based on a large sample of adult patients, should be further validated in other institutions.RÉSUMÉContexte : L’équation de Winter–Tozer qui permet d’estimer le taux de phénytoïne libre est biaisée et imprécise. Il existe des équations prédictives de rechange, mais la plupart ne sont pas validées.Objectifs : Évaluer le biais et la précision de l’équation de Winter Tozer et des équations dérivées choisies pour la prédiction du taux de phénytoïne libre et produire de nouvelles équations dotées d’une meilleure capacité prédictive.Méthodes : Une analyse rétrospective des dossiers médicaux (de patients chez lesquels on a mesuré la concentration de phénytoïne libre entre septembre 2008 et septembre 2013) a été menée au sein de trois sous-populations (soins intensifs, médecine générale et neurologie) dans un seul hôpital. Les patients retenus étaient des adultes âgés de plus de 18 ans dont le dossier contenait des données sur la concentration de phénytoïne libre. Les patients étaient exclus si la concentration de phénytoïne n’était pas à l’équilibre, s’ils étaient traités par hémodialyse ou s’ils prenaient des inhibiteurs ou des inducteurs enzymatiques ayant un effet sur la clairance de la phénytoïne. Les mesures de capacité prédictive comprenaient : l’erreur de prédiction moyenne, l’erreur quadratique moyenne et les graphiques de Bland–Altman. La corrélation des rangs de Spearman et une régression linéaire multiple ont été réalisées à partir de données transformées en log.Résultats : Au total, 133 patients ont été retenus (70 hommes [53 %]; âge moyen ± écart-type de 64 ± 19 ans; créatinine sérique de 90,4 ± 64,0 μmol/L; albumine sérique 26,4 ± 7,0 g/L). Dans l’ensemble de la population, l’équation de Winter–Tozer (erreur de prédiction moyenne de 1,7 μmol/L, intervalle de confiance [IC] à 95 % de 1,5 à 1,9) et l’équation d’Anderson (erreur de prédiction moyenne de 0,5 μmol/L, IC à 95 % de 0,3 à 0,7) ont surestimé la concentration de phénytoïne libre; la première équation de Kane avait tendance à sous-estimer le taux de phénytoïne libre (erreur de prédiction moyenne de –0,2 μmol/L, IC à 95 % de –0,4 à 0,0)] et la seconde équation de Kane a significativement sous-estimé le taux de phénytoïne libre (erreur de prédiction moyenne de –0,3 μmol/L, IC à 95 % de –0,5 à –0,1). Pour chacune des sous populations, l’équation de Winter–Tozer surévaluait la concentration réelle et était plus biaisée et moins précise. Aucune équation n’a obtenu de bons résultats pour la sous-population en soins intensifs. Seules l’albumine sérique (R2 = 0,09) et la concentration totale de phénytoïne (R2 = 0,53) étaient corrélées à la concentration de phénytoïne libre. L’équation obtenue par régression linéaire multiple était beaucoup moins biaisée et imprécise que l’équation de Winter–Tozer parmi l’ensemble de validation (p < 0,05). Une nouvelle équation, plus simple à utiliser, spécifique à la population de patients des auteurs, a été produite, avec un coefficient d’albumine de 0,275. Conclusion : Les capacités prédictives relativement mauvaises de l’équation de Winter–Tozer et des équations qui en découlent soulignent l’importance d’adopter des équations plus précises et moins biaisées. Les nouvelles équations mises de l’avant dans la présente étude, équations qui affichent une meilleure capacité prédictive pour la concentration de phénytoïne libre et qui s’appuient sur un important échantillon de patients adultes, doivent être validées dans d’autres établissements
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Anti-vascular agent Combretastatin A-4-P modulates Hypoxia Inducible Factor-1 and gene expression
No full textBackground
A functional vascular network is essential for the survival, growth and spread of solid tumours, making blood vessels a key target for therapeutic strategies. Combretastatin A-4 phosphate (CA-4-P) is a tubulin-depolymerising agent in Phase II clinical trials as a vascular disrupting agent. Not much is known of the molecular effect of CA-4-P under tumour conditions. The tumour microenvironment differs markedly from that in normal tissue, specifically with respect to oxygenation (hypoxia). Gene regulation under tumour conditions is governed by hypoxia inducible factor 1 (HIF-1), controlling angiogenic and metastatic pathways.
Methods
We investigated the effect of CA-4-P on factors of the upstream and downstream signalling pathway of HIF-1 in vitro.
Results
CA-4-P treatment under hypoxia tended to reduce HIF-1 accumulation in a concentration-dependent manner, an effect which was more prominent in endothelial cells than in cancer cell lines. Conversely, CA-4-P increased HIF-1 accumulation under aerobic conditions in vitro. At these concentrations of CA-4-P under aerobic conditions, nuclear factor κB was activated via the small GTPase RhoA, and expression of the HIF-1 downstream angiogenic effector gene, vascular endothelial growth factor (VEGF-A), was increased.
Conclusion
Our findings advance the understanding of signal transduction pathways involved in the actions of the anti-vascular agent CA-4-P
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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