962 resultados para GROUP SELECTION
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Purpose: Data from two randomized phase III trials were analyzed to evaluate prognostic factors and treatment selection in the first-line management of advanced non-small cell lung cancer patients with performance status (PS) 2. Patients and Methods: Patients randomized to combination chemotherapy (carboplatin and paclitaxel) in one trial and single-agent therapy (gemcitabine or vinorelbine) in the second were included in these analyses. Both studies had identical eligibility criteria and were conducted simultaneously. Comparison of efficacy and safety was performed between the two cohorts. A regression analysis identified prognostic factors and subgroups of patients that may benefit from combination or single-agent therapy. Results: Two hundred one patients were treated with combination and 190 with single-agent therapy. Objective responses were 37 and 15%, respectively. Median time to progression was 4.6 months in the combination arm and 3.5 months in the single-agent arm (p < 0.001). Median survival imes were 8.0 and 6.6 months, and 1-year survival rates were 31 and 26%, respectively. Albumin <3.5 g, extrathoracic metastases, lactate dehydrogenase ≥200 IU, and 2 comorbid conditions predicted outcome. Patients with 0-2 risk factors had similar outcomes independent of treatment, whereas patients with 3-4 factors had a nonsignificant improvement in median survival with combination chemotherapy. Conclusion: Our results show that PS2 non-small cell lung cancer patients are a heterogeneous group who have significantly different outcomes. Patients treated with first-line combination chemotherapy had a higher response and longer time to progression, whereas overall survival did not appear significantly different. A prognostic model may be helpful in selecting PS 2 patients for either treatment strategy. © 2009 by the International Association for the Study of Lung Cancer.
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Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.
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This exploratory study into director selection involved in-depth interviews with Australian non-executive directors to identify what directors consider as important criteria when selecting new members and the approach taken to identify and select candidates. The findings indicate boards select new members based not only on their ability to contribute complementary skills and experience but also on a perceived compatibility with incumbent board members. While these two selection criteria are considered equal in importance, not all selection approaches are able to adequately assess both criteria. As a result many selections fail to realise their selection criteria.
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Purpose – This paper seeks to analyse the process of packaged software selection in a small organization, focussing particularly on the role of IT consultants as intermediaries in the process. Design/methodology/approach – This is based upon a longitudinal, qualitative field study concerning the adoption of a customer relationship management package in an SME management consultancy. Findings – The authors illustrate how the process of “salesmanship”, an activity directed by the vendor/consultant and focussed on the interests of senior management, marginalises user needs and ultimately secures the procurement of the software package. Research limitations/implications – Despite the best intentions the authors lose something of the rich detail of the lived experience of technology in presenting the case study as a linear narrative. Specifically, the authors have been unable to do justice to the complexity of the multifarious ways in which individual perceptions of the project were influenced and shaped by the opinions of others. Practical implications – Practitioners, particularly those from within SMEs, should be made aware of the ways in which external parties may have a vested interest in steering projects in a particular direction, which may not necessarily align with their own interests. Originality/value – This study highlights in detail the role of consultants and vendors in software selection processes, an area which has received minimal attention to date. Prior work in this area emphasises the necessary conditions for, and positive outcomes of, appointing external parties in an SME context, with only limited attention being paid to the potential problems such engagements may bring.
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Background Supine imaging modalities provide valuable 3D information on scoliotic anatomy, but the altered spine geometry between the supine and standing positions affects the Cobb angle measurement. Previous studies report a mean 7°-10° Cobb angle increase from supine to standing, but none have reported the effect of endplate pre-selection or whether other parameters affect this Cobb angle difference. Methods Cobb angles from existing coronal radiographs were compared to those on existing low-dose CT scans taken within three months of the reference radiograph for a group of females with adolescent idiopathic scoliosis. Reformatted coronal CT images were used to measure supine Cobb angles with and without endplate pre-selection (end-plates selected from the radiographs) by two observers on three separate occasions. Inter and intra-observer measurement variability were assessed. Multi-linear regression was used to investigate whether there was a relationship between supine to standing Cobb angle change and eight variables: patient age, mass, standing Cobb angle, Risser sign, ligament laxity, Lenke type, fulcrum flexibility and time delay between radiograph and CT scan. Results Fifty-two patients with right thoracic Lenke Type 1 curves and mean age 14.6 years (SD 1.8) were included. The mean Cobb angle on standing radiographs was 51.9° (SD 6.7). The mean Cobb angle on supine CT images without pre-selection of endplates was 41.1° (SD 6.4). The mean Cobb angle on supine CT images with endplate pre-selection was 40.5° (SD 6.6). Pre-selecting vertebral endplates increased the mean Cobb change by 0.6° (SD 2.3, range −9° to 6°). When free to do so, observers chose different levels for the end vertebrae in 39% of cases. Multi-linear regression revealed a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility (p = 0.001), age (p = 0.027) and standing Cobb angle (p < 0.001). The 95% confidence intervals for intra-observer and inter-observer measurement variability were 3.1° and 3.6°, respectively. Conclusions Pre-selecting vertebral endplates causes minor changes to the mean supine to standing Cobb change. There is a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility such that this difference can be considered a potential alternative measure of spinal flexibility.
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Travel speed is one of the most critical parameters for road safety; the evidence suggests that increased vehicle speed is associated with higher crash risk and injury severity. Both naturalistic and simulator studies have reported that drivers distracted by a mobile phone select a lower driving speed. Speed decrements have been argued to be a risk compensatory behaviour of distracted drivers. Nonetheless, the extent and circumstances of the speed change among distracted drivers are still not known very well. As such, the primary objective of this study was to investigate patterns of speed variation in relation to contextual factors and distraction. Using the CARRS-Q high-fidelity Advanced Driving Simulator, the speed selection behaviour of 32 drivers aged 18-26 years was examined in two phone conditions: baseline (no phone conversation) and handheld phone operation. The simulator driving route contained five different types of road traffic complexities, including one road section with a horizontal S curve, one horizontal S curve with adjacent traffic, one straight segment of suburban road without traffic, one straight segment of suburban road with traffic interactions, and one road segment in a city environment. Speed deviations from the posted speed limit were analysed using Ward’s Hierarchical Clustering method to identify the effects of road traffic environment and cognitive distraction. The speed deviations along curved road sections formed two different clusters for the two phone conditions, implying that distracted drivers adopt a different strategy for selecting driving speed in a complex driving situation. In particular, distracted drivers selected a lower speed while driving along a horizontal curve. The speed deviation along the city road segment and other straight road segments grouped into a different cluster, and the deviations were not significantly different across phone conditions, suggesting a negligible effect of distraction on speed selection along these road sections. Future research should focus on developing a risk compensation model to explain the relationship between road traffic complexity and distraction.
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Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.
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'Dwarf parfitt', an extra-dwarf Cavendish cultivar with resistance to subtropical race 4 fusarium oxysporum f. sp. cubense 9Foc), was gamma irradiated at a dose of 20 Gy and putative mutants were recovered with improved agronomic characteristics. Further screening of putative mutants for improved yield and fruit size, as well as a degree of resistence to fusarium wilt, led to the selection of a line (DPM25) with improved productivity when grown on soils infested with subtropical race 4 Foc. DPM25 was equal to the industry standard, 'Williams', in every agronomic trait measured and it consistently showed a lower incidence of fusarium wilt. Further improvement of field resistance to race 4 Foc is needed in DPM25 and further cycles of mutation induction and selction is an option discussed.
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The leader protease (L-pro) and capsid-coding sequences (P1) constitute approximately 3 kb of the foot-and-mouth disease virus (FMDV). We studied the phylogenetic relationship of 46 FMDV serotype A isolates of Indian origin collected during the period 1968-2005 and also eight vaccine strains using the neighbour-joining tree and Bayesian tree methods. The viruses were categorized under three major groups - Asian, Euro-South American and European. The Indian isolates formed a distinct genetic group among the Asian isolates. The Indian isolates were further classified into different genetic subgroups (<5% divergence). Post-1995 isolates were divided into two subgroups while a few isolates which originated in the year 2005 from Andhra Pradesh formed a separate group. These isolates were closely related to the isolates of the 1970s. The FMDV isolates seem to undergo reverse mutation or onvergent evolution wherein sequences identical to the ancestors are present in the isolates in circulation. The eight vaccine strains included in the study were not related to each other and belonged to different genetic groups. Recombination was detected in the L-pro region in one isolate (A IND 20/82) and in the VP1 coding 1D region in another isolate (A RAJ 21/96). Positive selection was identified at aa positions 23 in the L-pro (P<0.05; 0.046*) and at aa 171 in the capsid protein VP1 (P<0.01; 0.003**).
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We carried out a discriminant analysis with identity by descent (IBD) at each marker as inputs, and the sib pair type (affected-affected versus affected-unaffected) as the output. Using simple logistic regression for this discriminant analysis, we illustrate the importance of comparing models with different number of parameters. Such model comparisons are best carried out using either the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). When AIC (or BIC) stepwise variable selection was applied to the German Asthma data set, a group of markers were selected which provide the best fit to the data (assuming an additive effect). Interestingly, these 25-26 markers were not identical to those with the highest (in magnitude) single-locus lod scores.
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Objective: To determine the extent to which different strength training exercises selectively activate the commonly injured biceps femoris long head (BFLH) muscle. Methods: This two-part observational study recruited 24 recreationally active males. Part 1 explored the amplitudes and the ratios of lateral to medial hamstring (BF/MH) normalised electromyography (nEMG) during the concentric and eccentric phases of 10 common strength training exercises. Part 2 used functional magnetic resonance imaging (fMRI) to determine the spatial patterns of hamstring activation during two exercises which i) most selectively, and ii) least selectively activated the BF in part 1. Results: Eccentrically, the largest BF/MH nEMG ratio was observed in the 45° hip extension exercise and the lowest was observed in the Nordic hamstring (NHE) and bent-knee bridge exercises. Concentrically, the highest BF/MH nEMG ratio was observed during the lunge and 45° hip extension and the lowest was observed for the leg curl and bent-knee bridge. fMRI revealed a greater BFLH to semitendinosus activation ratio in the 45° hip extension than the NHE (p<0.001). The T2 increase after hip extension for BFLH, semitendinosus and semimembranosus muscles were greater than that for BFSH (p<0.001). During the NHE, the T2 increase was greater for the semitendinosus than for the other hamstrings (p≤0.002). Conclusion: This investigation highlights the non-uniformity of hamstring activation patterns in different tasks and suggests that hip extension exercise more selectively activates the BFLH while the NHE preferentially recruits the semitendinosus. These findings have implications for strength training interventions aimed at preventing hamstring injury.
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In social selection the phenotype of an individual depends on its own genotype as well as on the phenotypes, and so genotypes, of other individuals. This makes it impossible to associate an invariant phenotype with a genotype: the social context is crucial. Descriptions of metazoan development, which often is viewed as the acme of cooperative social behaviour, ignore or downplay this fact. The implicit justification for doing so is based on a group-selectionist point of view. Namely, embryos are clones, therefore all cells have the same evolutionary interest, and the visible differences between cells result from a common strategy. The reasoning is flawed, because phenotypic heterogeneity within groups can result from contingent choices made by cells from a flexible repertoire as in multicellular development. What makes that possible is phenotypic plasticity, namely the ability of a genotype to exhibit different phenotypes. However, co-operative social behaviour with division of labour requires that different phenotypes interact appropriately, not that they belong to the same genotype, or have overlapping genetic interests. We sketch a possible route to the evolution of social groups that involves many steps: (a) individuals that happen to be in spatial proximity benefit simply by virtue of their number; (b) traits that are already present act as preadaptations and improve the efficiency of the group; and (c) new adaptations evolve under selection in the social context-that is, via interactions between individuals-and further strengthen group behaviour. The Dictyostelid or cellular slime mould amoebae (CSMs) become multicellular in an unusual way, by the aggregation of free-living cells. In nature the resulting group can be genetically homogeneous (clonal) or heterogeneous (polyclonal); in either case its development, which displays strong cooperation between cells (to the extent of so-called altruism) is not affected. This makes the CSMs exemplars for the study of social behaviour.
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The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.