870 resultados para Incorporating Vulnerability


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Africa is thought to be the region most vulnerable to the impacts of climate variability and change. Agriculture plays a dominant role in supporting rural livelihoods and economic growth over most of Africa. Three aspects of the vulnerability of food crop systems to climate change in Africa are discussed: the assessment of the sensitivity of crops to variability in climate, the adaptive capacity of farmers, and the role of institutions in adapting to climate change. The magnitude of projected impacts of climate change on food crops in Africa varies widely among different studies. These differences arise from the variety of climate and crop models used, and the different techniques used to match the scale of climate model output to that needed by crop models. Most studies show a negative impact of climate change on crop productivity in Africa. Farmers have proved highly adaptable in the past to short- and long-term variations in climate and in their environment. Key to the ability of farmers to adapt to climate variability and change will be access to relevant knowledge and information. It is important that governments put in place institutional and macro-economic conditions that support and facilitate adaptation and resilience to climate change at local, national and transnational level.

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Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power. Copyright © 2003 John Wiley & Sons, Ltd.

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In a sequential clinical trial, accrual of data on patients often continues after the stopping criterion for the study has been met. This is termed “overrunning.” Overrunning occurs mainly when the primary response from each patient is measured after some extended observation period. The objective of this article is to compare two methods of allowing for overrunning. In particular, simulation studies are reported that assess the two procedures in terms of how well they maintain the intended type I error rate. The effect on power resulting from the incorporation of “overrunning data” using the two procedures is evaluated.

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1. The production of food for human consumption has led to an historical and global conflict with terrestrial carnivores, which in turn has resulted in the extinction or extirpation of many species, although some have benefited. At present, carnivores affect food production by: (i) killing human producers; killing and/or eating (ii) fish/shellfish; (iii) game/wildfowl; (iv) livestock; (v) damaging crops; (vi) transmitting diseases; and (vii) through trophic interactions with other species in agricultural landscapes. Conversely, carnivores can themselves be a source of dietary protein (bushmeat). 2. Globally, the major areas of conflict are predation on livestock and the transmission of rabies. At a broad scale, livestock predation is a customary problem where predators are present and has been quantified for a broad range of carnivore species, although the veracity of these estimates is equivocal. Typically, but not always, losses are small relative to the numbers held, but can be a significant proportion of total livestock mortality. Losses experienced by producers are often highly variable, indicating that factors such as husbandry practices and predator behaviour may significantly affect the relative vulnerability of properties in the wider landscape. Within livestock herds, juvenile animals are particularly vulnerable. 3. Proactive and reactive culling are widely practised as a means to limit predation on livestock and game. Historic changes in species' distributions and abundance illustrate that culling programmes can be very effective at reducing predator density, although such substantive impacts are generally considered undesirable for native predators. However, despite their prevalence, the effectiveness, efficiency and the benefit:cost ratio of culling programmes have been poorly studied. 4. A wide range of non-lethal methods to limit predation has been studied. However, many of these have their practical limitations and are unlikely to be widely applicable. 5. Lethal approaches are likely to dominate the management of terrestrial carnivores for the foreseeable future, but animal welfare considerations are increasingly likely to influence management strategies. The adoption of non-lethal approaches will depend upon proof of their effectiveness and the willingness of stakeholders to implement them, and, in some cases, appropriate licensing and legislation. 6. Overall, it is apparent that we still understand relatively little about the importance of factors affecting predation on livestock and how to manage this conflict effectively. We consider the following avenues of research to be essential: (i) quantified assessments of the loss of viable livestock; (ii) landscape-level studies of contiguous properties to quantify losses associated with variables such as different husbandry practices; (iii) replicated experimental manipulations to identify the relative benefit of particular management practices, incorporating (iv) techniques to identify individual predators killing stock; and (v) economic analyses of different management approaches to quantify optimal production strategies.

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This paper presents a simple Bayesian approach to sample size determination in clinical trials. It is required that the trial should be large enough to ensure that the data collected will provide convincing evidence either that an experimental treatment is better than a control or that it fails to improve upon control by some clinically relevant difference. The method resembles standard frequentist formulations of the problem, and indeed in certain circumstances involving 'non-informative' prior information it leads to identical answers. In particular, unlike many Bayesian approaches to sample size determination, use is made of an alternative hypothesis that an experimental treatment is better than a control treatment by some specified magnitude. The approach is introduced in the context of testing whether a single stream of binary observations are consistent with a given success rate p(0). Next the case of comparing two independent streams of normally distributed responses is considered, first under the assumption that their common variance is known and then for unknown variance. Finally, the more general situation in which a large sample is to be collected and analysed according to the asymptotic properties of the score statistic is explored. Copyright (C) 2007 John Wiley & Sons, Ltd.

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Bayesian decision procedures have already been proposed for and implemented in Phase I dose-escalation studies in healthy volunteers. The procedures have been based on pharmacokinetic responses reflecting the concentration of the drug in blood plasma and are conducted to learn about the dose-response relationship while avoiding excessive concentrations. However, in many dose-escalation studies, pharmacodynamic endpoints such as heart rate or blood pressure are observed, and it is these that should be used to control dose-escalation. These endpoints introduce additional complexity into the modeling of the problem relative to pharmacokinetic responses. Firstly, there are responses available following placebo administrations. Secondly, the pharmacodynamic responses are related directly to measurable plasma concentrations, which in turn are related to dose. Motivated by experience of data from a real study conducted in a conventional manner, this paper presents and evaluates a Bayesian procedure devised for the simultaneous monitoring of pharmacodynamic and pharmacokinetic responses. Account is also taken of the incidence of adverse events. Following logarithmic transformations, a linear model is used to relate dose to the pharmacokinetic endpoint and a quadratic model to relate the latter to the pharmacodynamic endpoint. A logistic model is used to relate the pharmacokinetic endpoint to the risk of an adverse event.

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A series of promoter probe vectors for use in Gram-negative bacteria has been made in two broad-host-range vectors, pOT (pBBR replicon) and pJP2 (incP replicon). Reporter fusions can be made to gfpUV, gfprnut3.1, unstable gfpmut3.1 variants (LAA, LVA, AAV and ASV), gfp+, dsRed2, dsRedT3, dsRedT4, mRFP1, gusA or lacZ. The two vector families, pOT and pJP2, are compatible with one another and share the same polylinker for facile interchange of promoter regions. Vectors based on pJP2 have the advantage of being ultra-stable in the environment due to the presence of the parABCDE genes. As a confirmation of their usefulness, the dicarboxylic acid transport system promoter (dctA(p)) was cloned into a pOT (pRU1097)- and a pJP2 (pRU1156)-based vector and shown to be expressed by Rhizobium leguminosarum in infection threads of vetch. This indicates the presence of dicarboxylates at the earliest stages of nodule formation.

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The AB, monomer, 3,5-bis(3-hydroxylprop-1-ynyl)benzoic acid 1, has been synthesized using a Sonogashira cross-coupling with a palladium catalyst system developed for use with deactivated aryl halides. Numerous condensation methods have then been assessed in the homopolymerization of the acid-diol monomer 1 to afford hyperbranched polyesters. However, as a result of the thermal instability of the monomer, direct thermal polymerizations could not be employed. Alternative approaches using carbodiimide-coupling reagents enabled the production of soluble polyesters possessing molecular weights and degrees of branching ranging from 2500 to 11,000 and 0.22 to 0.33, respectively. (C) 2003 Elsevier Ltd. All rights reserved.

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Single crystal X-ray diffraction studies reveal that the incorporation of meta-amino benzoic acid in the middle of a helix forming hexapeptide sequence such as in peptide I Boc-Ile(1)-Aib(2)-Val(3)-m-ABA(4)-Ile(5)-Aib(6)-Leu(7)-OMe (Aib: alpha-amino isobutyric acid: m-ABA: meta-amino benzoic acid) breaks the helix propagation to produce a turn-linker-turn (T-L-T) foldamer in the solid state. In the crystalline state two conformational isomers of peptide I self-assemble in antiparallel fashion through intermolecular hydrogen bonds and aromatic pi-pi interactions to form a molecular duplex. The duplexes are further interconnected through intermolecular hydrogen bonds to form a layer of peptides. The layers are stacked one on top of the other through van der Waals interactions to form hydrophilic channels filled with solvent methanol. (C) 2009 Elsevier B.V. All rights reserved.

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In the title family, the ONO donor ligands are the acetylhydrazones of salicylaidehyde (H2L1) and 2-hydroxyacetophenone (H2L2) (general abbreviation, H2L). The reaction of bis(acetylacetonato)oxovanadium(IV) with a mixture of tridentate H2L and a bidentate NN donor [e.g., 2,2'-bipyridine(bpy) or 1,10-phenanthroline(phen), hereafter B] ligands in equimolar ratio afforded the tetravalent complexes of the type [(VO)-O-IV(L)(B)]; complexes (1)-(4) whereas, if B is replaced by 8-hydroxyquinoline(Hhq) (which is a bidentate ON donor ligand), the above reaction mixture yielded the pentavalent complexes of the type [(VO)-O-V(L)(hq)]; complexes (5) and (6). Aerial oxygen is most likely the oxidant (for the oxidation of V-IV -> V-V) in the synthesis of pentavalent complexes (5) and (6). [(VO)-O-IV(L)(B)] complexes are one electron paramagnetic and display axial EPR spectra, while the [(VO)-O-V(L)(hq)] complexes are diamagnetic. The X-ray structure of [(VO)-O-V(L-2)(hq)] (6) indicates that H2L2 ligand is bonded with the vanadium meridionally in a tridentate dinegative fashion through its phenolic-O, enolic-O and imine-N atoms. The general bond length order is: oxo < phenolato < enolato. The V-O (enolato) bond is longer than V-O (phenolato) bond by similar to 0.07 angstrom and is identical with V-O (carboxylate) bond. H-1 NMR spectrum of (6) in CDCl3 solution indicates that the binding nature in the solid state is also retained in solution. Complexes (1)(4) display two ligand-field transitions in the visible region near 820 and 480 nm in DMF solution and exhibit irreversible oxidation peak near +0.60 V versus SCE in DMSO solution, while complexes (5) and (6) exhibit only LMCT band near 535 nm and display quasi-reversible one electron reduction peak near -0.10 V versus SCE in CH2Cl2 solution. The VO3+-VO2+ E-1/2 values shift considerably to more negative values when neutral NN donor is replaced by anionic ON donor species and it also provides better VO3+ binding via phenolato oxygen. For a given bidentate ligand, E-1/2 increases in the order: (L-2)(2-) < (L-1)(2-). (c) 2004 Elsevier B.V. All rights reserved.

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Four new antimony sulphides, [T(dien)(2)]Sb6S10 center dot xH(2)O [T = Ni (1), Co (2) x approximate to 0.45], [Co(en)(3)]SbsSI(3) (3) and [Ni(en)(3)]Sb12S19 (4), have been synthesised under solvothermal conditions. In compounds (1) - (3), Sb12S228- secondary building units are connected to form layered structures. In (1) and (2), Sb-6 S-2- layers containing Sb16S16 heterorings are separated by [T(dien]2](2+) cations, whilst in (3), Sb8 S2- layers 10 13 contain [Co(en)3]2+ cations within large Sb22S22 pores. Compound (4) adopts a three-dimensional structure in which [Ni(en)3 12 cations lie within ca. 5 A wide channels. (c) 2007 Elsevier Ltd. All rights reserved.

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[VIVO(acac)(2)] reacts with an equimolar amount of benzoyl hydrazone of 2-hydroxyacetophenone (H2L1) or 5-chloro-2-hydroxyacetophenone (H2L2) in the presence of excess pyridine (py) in methanol to produce the quaternary [(VO)-O-V(L-1)(OCH3)(py)] (1) and [(VO)-O-V(L-2)(OCH3)(py)] (2) complexes, respectively, while under similar condition, the benzoyl hydrazones of 2-hydroxy-5-methylacetophenone (H2L3) and 2-hydroxy-5-methoxyacetophenone (H2L4) afforded only the methoxy bridged dimeric [(VO)-O-V(L-3/L-4)(OCH3)](2) complexes. The X-ray structural analysis of 1 and 2 indicates that the geometry around the metal is distorted octahedral where the three equatorial positions are occupied by the phenolate-O, enolate-O and the imine-N of the fully deprotonated hydrazone ligand in its enolic form and the fourth one by a methoxide-O atom. An oxo-O and a pyridine-N atom occupy two axial positions. Quaternary complexes exhibit one quasi-reversible one-electron reduction peak near 0.25 V versus SCE in CH2Cl2 and they decompose appreciably to the corresponding methoxy bridged dimeric complex in CDCl3 solution as indicated by their H-1 NMR spectra. These quaternary VO3+ complexes are converted to the corresponding V2O34+-complexes simply on refluxing them in acetone and to the VO2+-complexes on reaction with KOH in methanol. An equimolar amount of 8-hydroxyquinoline (Hhq) converts these quaternary complexes to the ternary [(VO)-O-V(L)(hq)] complexes in CHCl3. (C) 2009 Elsevier B. V. All rights reserved.

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The blue coloured complex [Cu(HL)(H2O)(ClO4)]ClO.H2O.MeOH (1.H2O.MeOH) has been synthesised in excellent yields by reacting Cu(ClO4)(2).6H(2)O with N,N-bis(2-methylpyridyl)(3,5-dimethyl-2-hydroxybenzyl)amine (HL) in methanol. The same reaction, when carried out in the presence of sodium azide, afforded a dark-blue complex of formula [Cu-2(HL)(2)(mu-1,1-N-3)(2)](ClO4)(2) (2). The crystal and molecular structures of the complexes have been solved. Variable-temperature magnetic susceptibility data in the range of 2-300 K for 2 reveal the existence of an antiferromagnetic interaction through an end-on azido linker. Temperature-dependent susceptibility studies for 2 were fitted using the Bleaney-Bowers expression, which led to the parameters J = -3.2 cm(-1), g = 2.12 and R = 2.14 x 10(-4). (C) Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2004.

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Three kinds of copper(II) azide complexes have been synthesised in excellent yields by reacting Cu(ClO4)(2) . 6H(2)O with N,N-bis(2-pyridylmethyl)amine (L-1); N-(2-pyridylmethyl)-N',N'-dimethylethylenediamine (L-2); and N-(2-pyridylmethyl)-N',N'-diethylethylenediamine (L-3), respectively, in the presence of slight excess of sodium azide. They are the monomeric Cu(L-1)(N-3)(ClO4) (1), the end-to-end diazido-bridged Cu-2(L-2)(2)(mu-1,3-N-3)(2)(ClO4)(2) (2) and the single azido-bridged (mu-1,3-) 1D chain [Cu(L-3)(mu-1,3-N-3)](n)(ClO4)(n) (3). The crystal and molecular structures of these complexes have been solved. The variable temperature magnetic moments of type 2 and type 3 complexes were studied. Temperature dependent susceptibility for 2 was fitted using the Bleaney-Bowers expression which led to the parameters J = -3.43 cm(-1) and R = 1 X 10(-5). The magnetic data for 3 were fitted to Baker's expression for S = 1/2 and the parameters obtained were J = 1.6 cm(-1) and R = 3.2 x 10(-4). Crystal data are as follows. Cu(L-1)(N-3)(ClO4): Chemical formula, C12H13ClN6O4Cu; crystal system, monoclinic; space group, P2(1)/c; a = 8.788(12), b = 13.045(15), c = 14.213(15) Angstrom; beta = 102.960(10)degrees; Z = 4. Cu(L-2)(mu-N-3)(ClO4): Chemical formula. C10H17ClN6O4Cu: crystal system, monoclinic; space group, P2(1)/c; a = 10.790(12), b = 8.568(9), c = 16.651(17) Angstrom; beta = 102.360(10)degrees; Z = 4. [Cu(L-3)(mu-N-3)](ClO4): Chemical formula, C12H21ClN6O4Cu; crystal system, monoclinic; space group, P2(1)/c; a = 12.331(14), b = 7.804(9), c = 18.64(2) Angstrom; beta = 103.405(10)degrees; Z = 4. (C) 2004 Elsevier B.V. All rights reserved.