902 resultados para Matrix of complex negotiation


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Treatment that will not provide significant net benefit at the end of a person’s life (called futile treatment) is considered by many people to represent a major problem in the health sector, as it can waste resources and raise significant ethical issues. Medical treatment at the end of life involves a complex negotiation that implicates intergroup communication between health professionals, patients, and families, as well as between groups of health professionals. This study, framed by intergroup language theory, analyzed data from a larger project on futile treatment, in order to examine the intergroup language associated with futile treatment. Hospital doctors (N = 96) were interviewed about their understanding of treatment given to adult patients at the end of life that they considered futile. We conducted a discourse analysis on doctors’ descriptions of futile treatment provided by themselves and their in-group and out-group colleagues. Results pointed to an intergroup context, with patients, families, and colleagues as out-groups. In their descriptions, doctors justified their own decisions using the language of logic, ethics, and respect. Patients and families, however, were characterized in terms of wishing and wanting, as were outgroup colleagues. In addition, out-group doctors were described in strongly negative intergroup language.

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Kimberlite drill core from the Muskox pipe (Northern Slave Province, Nunavut, Canada) highlights the difficulties in distinguishing coherent from fragmental kimberlite and assessing the volcanological implications of the apparent gradational contact between the two facies. Using field log data, petrography, and several methods to quantify crystal and xenolith sizes and abundances, the pipe is divided into two main facies, dark-coloured massive kimberlite (DMK) and light-coloured fragmental kimberlite (LFK). DMK is massive and homogeneous, containing country-rock lithic clasts (~ 10%) and olivine macrocrysts (~ 15%) set in a dark, typically well crystallised, interstitial medium containing abundant microphenocrysts of olivine (~ 15%), opaques and locally monticellite, all of which are enclosed by mostly serpentine. In general, LFK is also massive and structureless, containing ~ 20% country-rock lithic clasts and ~ 12% olivine macrocrysts. These framework components are supported in a matrix of serpentinized olivine microphenocrysts (10%), microlites of clinopyroxene, and phlogopite, all of which are enclosed by serpentine. The contact between DMK and LFK facies is rarely sharp, and more commonly is gradational (from 5 cm to ~ 10 m). The contact divides the pipe roughly in half and is sub-vertical with an irregular shape, locally placing DMK facies both above and below the fragmental rocks. Most features of DMK are consistent with a fragmental origin, particularly the crystal- and xenolith-rich nature (~ 55-65%), but there are some similarities with rocks described as coherent kimberlite in the literature. We discuss possible origins of gradational contacts and consider the significance for understanding the origin of the DMK facies, with an emphasis on the complications of alteration overprinting of primary textures.

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Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

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Efforts to reduce carbon emissions in the buildings sector have been focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants,something with much greater economic returns than energy savings. Reducing energy demand in green commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This project investigates these factors and focuses on the performance of and interaction between: green design elements, internal environmental quality, occupant experience, tenant/leasing agreements, and building regulation and management. This paper suggests six areas of strategic research that are needed to understand how conditions can be created to support productivity in green buildings, and deliver significant energy consumption reductions.

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Real-world cryptographic protocols such as the widely used Transport Layer Security (TLS) protocol support many different combinations of cryptographic algorithms (called ciphersuites) and simultaneously support different versions. Recent advances in provable security have shown that most modern TLS ciphersuites are secure authenticated and confidential channel establishment (ACCE) protocols, but these analyses generally focus on single ciphersuites in isolation. In this paper we extend the ACCE model to cover protocols with many different sub-protocols, capturing both multiple ciphersuites and multiple versions, and define a security notion for secure negotiation of the optimal sub-protocol. We give a generic theorem that shows how secure negotiation follows, with some additional conditions, from the authentication property of secure ACCE protocols. Using this framework, we analyse the security of ciphersuite and three variants of version negotiation in TLS, including a recently proposed mechanism for detecting fallback attacks.

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The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section. © 2012 The American Society of Human Genetics.

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This study proposes that the adoption process of complex-wide systems (e.g. cloud ERP) should be observed as multi-stage actions. Two theoretical lenses were utilised for this study with critical adoption factors identified through the theory of planned behaviour and the progression of each adoption factor observed through Ettlie's (1980) multi-stage adoption model. Together with a survey method, this study has employed data gathered from 162 decision-makers of small and medium-sized enterprises (SMEs). Using both linear and non-linear approaches for the data analysis, the study findings have shown that the level of importance for adoption factors changes across different adoption stages.

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Large Display Arrays (LDAs) use Light Emitting Diodes (LEDs) in order to inform a viewing audience. A matrix of individually driven LEDs allows the area represented to display text, images and video. LDAs have undergone rapid development over the past 10 years in both the modular and semi-flexible formats. This thesis critically analyses the communication architecture and processor functionality of current LDAs and presents an alternative method, that is, Scalable Flexible Large Display Arrays (SFLDAs). SFLDAs are more adaptable to a variety of applications because of enhancements in scalability and flexibility. Scalability is the ability to configure SFLDAs from 0.8m2 to 200m2. Flexibility is increased functionality within the processors to handle changes in configuration and the use of a communication architecture that standardises two-way communication throughout the SFLDA. While common video platforms such as Digital Video Interface (DVI), Serial Digital Interface (SDI), and High Definition Multimedia Interface (HDMI) are considered as solutions for the communication architecture of SFLDAs, so too is modulation, fibre optic, capacitive coupling and Ethernet. From an analysis of these architectures, Ethernet was identified as the best solution. The use of Ethernet as the communication architecture in SFLDAs means that both hardware and software modules are capable of interfacing to the SFLDAs. The Video to Ethernet Processor Unit (VEPU), Scoreboard, Image and Control Software (SICS) and Ethernet to LED Processor Unit (ELPU) have been developed to form the key components in designing and implementing the first SFLDA. Data throughput rate and spectrophotometer tests were used to measure the effectiveness of Ethernet within the SFLDA constructs. The result of testing and analysis of these architectures showed that Ethernet satisfactorily met the requirements of SFLDAs.

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The focus of this paper is two-dimensional computational modelling of water flow in unsaturated soils consisting of weakly conductive disconnected inclusions embedded in a highly conductive connected matrix. When the inclusions are small, a two-scale Richards’ equation-based model has been proposed in the literature taking the form of an equation with effective parameters governing the macroscopic flow coupled with a microscopic equation, defined at each point in the macroscopic domain, governing the flow in the inclusions. This paper is devoted to a number of advances in the numerical implementation of this model. Namely, by treating the micro-scale as a two-dimensional problem, our solution approach based on a control volume finite element method can be applied to irregular inclusion geometries, and, if necessary, modified to account for additional phenomena (e.g. imposing the macroscopic gradient on the micro-scale via a linear approximation of the macroscopic variable along the microscopic boundary). This is achieved with the help of an exponential integrator for advancing the solution in time. This time integration method completely avoids generation of the Jacobian matrix of the system and hence eases the computation when solving the two-scale model in a completely coupled manner. Numerical simulations are presented for a two-dimensional infiltration problem.

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Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered. © Published by Oxford University Press 2012.

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The results of a high-resolution ambient STM study of ‘sulflower’ (octathio[8]circulene) and ‘selenosulflower’ (sym-tetraselena-tetrathio[8]circulene) molecules, immobilized in a hydrogen-bonded matrix of trimesic acid (TMA) at the solid–liquid interface, are compared with the STM and X-ray structure of separate host and guest 2D and 3D crystals, respectively.

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In this paper, inhibition of the glutathione peroxidase activity of two synthetic organoselenium compounds, bis[2-(N,N-dimethylamino)benzyl]diselenide (5) and bis[2-(N,N-dimethylamino)benzyl]selenide (9), by gold(I) thioglucose (1), chloro(triethylphosphine)gold(I), chloro(trimethylphosphine)gold(I), and chloro(triphenylphosphine)gold(I) is described. The inhibition is found to be competitive with respect to a peroxide (H2O2) substrate and noncompetitive with respect to a thiol (PhSH) cosubstrate. The diselenide 5 reacts with PhSH to produce the corresponding selenol (6), which upon treatment with 1 equiv of gold(I) chlorides produces the corresponding gold selenolate complexes 11−13. However, the addition of 1 equiv of selenol 6 to complexes 11−13 leads to the formation of bis-selenolate complex 14 by ligand displacement reactions involving the elimination of phosphine ligands. The phosphine ligands eliminated from these reactions are further converted to the corresponding phosphine oxides (R3PO) and selenides (R3PSe). In addition to the replacement of the phosphine ligand by selenol 6, an interchange between two different phosphine ligands is also observed. For example, the reaction of complex 11 having a trimethylphosphine ligand with triphenylphosphine produces complex 13 by phosphine interchange reactions via the formation of intermediates 15 and 16. The reactivity of selenol 6 toward gold(I) phosphines is found to be similar to that of selenocysteine.

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Road deposited dust is a complex mixture of pollutants derived from a wide range of sources. Accurate identification of these sources is seminal for effective source-oriented control measures. A range of techniques such as enrichment factor analysis (EF), principal component analysis (PCA) and hierarchical cluster analysis (HCA) are available for identifying sources of complex mixtures. However, they have multiple deficiencies when applied individually. This study presents an approach for the effective utilisation of EF, PCA and HCA for source identification, so that their specific deficiencies on an individual basis are eliminated. EF analysis confirmed the non-soil origin of metals such as Na, Cu, Cd, Zn, Sn, K, Ca, Sb, Ba, Ti, Ni and Mo providing guidance in the identification of anthropogenic sources. PCA and HCA identified four sources, with soil and asphalt wear in combination being the most prominent sources. Other sources were tyre wear, brake wear and sea salt.

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[NiL2(NCS)2] (1) [L = 2-(aminomethyl)pyridine], [NiL02(NCS)2] (2) [(L0) = 2-(2-aminoethyl)pyridine and [NiL00 2(NCS)2] (3) [L00 = 2-(2-methylaminoethyl)pyridine] have been synthesized from solution. All the complexes possess trans geometry as is evident from solid state UV–Vis spectral study and X-ray single crystal structure analysis of complex 2 unambiguously proves trans geometry of the species.

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In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the 'sandwich' method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain 'bootstrapped' realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.