Evaluating Document Retrieval Methods for Resource Selection in Clustered P2P IR

Resource Selection (or Query Routing) is an important step in P2P IR. Though analogous to document retrieval in the sense of choosing a relevant subset of resources, resource selection methods have evolved independently from those for document retrieval. Among the reasons for such divergence is that document retrieval targets scenarios where underlying resources are semantically homogeneous, whereas peers would manage diverse content. We observe that semantic heterogeneity is mitigated in the clustered 2-tier P2P IR architecture resource selection layer by way of usage of clustering, and posit that this necessitates a re-look at the applicability of document retrieval methods for resource selection within such a framework. This paper empirically benchmarks document retrieval models against the state-of-the-art resource selection models for the problem of resource selection in the clustered P2P IR architecture, using classical IR evaluation metrics. Our benchmarking study illustrates that document retrieval models significantly outperform other methods for the task of resource selection in the clustered P2P IR architecture. This indicates that clustered P2P IR framework can exploit advancements in document retrieval methods to deliver corresponding improvements in resource selection, indicating potential convergence of these fields for the clustered P2P IR architecture.

Safe Therapeutic Economic Pharmaceutical Selection (STEPS): development, introduction and use in Northern Ireland

A number of medicine selection methods have been used worldwide for formulary purposes. In Northern Ireland, integrated medicines management is being developed, and related projects have been carried out. This paper deals with the description of the STEPS (Safe Therapeutic Economic Pharmaceutical Selection) programme. The paper outlines the development of STEPS and its application as an element of a cost-effective medicines-management process in Northern Ireland.

Two-Stage Orthogonal Least Squares Methods for Neural Network Construction

A number of neural networks can be formulated as the linear-in-the-parameters models. Training such networks can be transformed to a model selection problem where a compact model is selected from all the candidates using subset selection algorithms. Forward selection methods are popular fast subset selection approaches. However, they may only produce suboptimal models and can be trapped into a local minimum. More recently, a two-stage fast recursive algorithm (TSFRA) combining forward selection and backward model refinement has been proposed to improve the compactness and generalization performance of the model. This paper proposes unified two-stage orthogonal least squares methods instead of the fast recursive-based methods. In contrast to the TSFRA, this paper derives a new simplified relationship between the forward and the backward stages to avoid repetitive computations using the inherent orthogonal properties of the least squares methods. Furthermore, a new term exchanging scheme for backward model refinement is introduced to reduce computational demand. Finally, given the error reduction ratio criterion, effective and efficient forward and backward subset selection procedures are proposed. Extensive examples are presented to demonstrate the improved model compactness constructed by the proposed technique in comparison with some popular methods.

A novel forward gene selection algorithm for microarray data

This paper investigates the gene selection problem for microarray data with small samples and variant correlation. Most existing algorithms usually require expensive computational effort, especially under thousands of gene conditions. The main objective of this paper is to effectively select the most informative genes from microarray data, while making the computational expenses affordable. This is achieved by proposing a novel forward gene selection algorithm (FGSA). To overcome the small samples' problem, the augmented data technique is firstly employed to produce an augmented data set. Taking inspiration from other gene selection methods, the L2-norm penalty is then introduced into the recently proposed fast regression algorithm to achieve the group selection ability. Finally, by defining a proper regression context, the proposed method can be fast implemented in the software, which significantly reduces computational burden. Both computational complexity analysis and simulation results confirm the effectiveness of the proposed algorithm in comparison with other approaches

The Selection of Party Leaders in Northern Ireland

This article provides an analysis of the leadership selection methods adopted by Northern Ireland's five main parties. Drawing on data from interviews with party elites and internal party documents, it sheds light on an important element of intra-party organisation in the region and constitutes a rare case-study of leadership selection in a consociational democracy. By accounting for instances of organisational reform, this article also reveals the extent to which Northern Ireland's parties align with the wider comparative trend of leadership ‘democratisation’. In terms of ‘who’ selects party leaders, the analysis finds a substantial degree of organisational heterogeneity and a reasonably high rate of democratisation. Northern Ireland's parties also prove rather exceptional in their universal adoption of short fixed terms for party leaders and, in the case of three of the parties, their preference for high candidacy thresholds.

Improved structure optimization for fuzzy-neural networks

Fuzzy-neural-network-based inference systems are well-known universal approximators which can produce linguistically interpretable results. Unfortunately, their dimensionality can be extremely high due to an excessive number of inputs and rules, which raises the need for overall structure optimization. In the literature, various input selection methods are available, but they are applied separately from rule selection, often without considering the fuzzy structure. This paper proposes an integrated framework to optimize the number of inputs and the number of rules simultaneously. First, a method is developed to select the most significant rules, along with a refinement stage to remove unnecessary correlations. An improved information criterion is then proposed to find an appropriate number of inputs and rules to include in the model, leading to a balanced tradeoff between interpretability and accuracy. Simulation results confirm the efficacy of the proposed method.

Regression analysis of spatial data

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

Observational Constraints on the Progenitors of Core-Collapse Supernovae: The Case for Missing High-Mass Stars

Over the last 15 years, the supernova community has endeavoured to directly identify progenitor stars for core-collapse supernovae discovered in nearby galaxies. These precursors are often visible as resolved stars in high-resolution images from space-and ground-based telescopes. The discovery rate of progenitor stars is limited by the local supernova rate and the availability and depth of archive images of galaxies, with 18 detections of precursor objects and 27 upper limits. This review compiles these results (from 1999 to 2013) in a distance-limited sample and discusses the implications of the findings. The vast majority of the detections of progenitor stars are of type II-P, II-L, or IIb with one type Ib progenitor system detected and many more upper limits for progenitors of Ibc supernovae (14 in all). The data for these 45 supernovae progenitors illustrate a remarkable deficit of high-luminosity stars above an apparent limit of log L/L-circle dot similar or equal to 5.1 dex. For a typical Salpeter initial mass function, one would expect to have found 13 high-luminosity and high-mass progenitors by now. There is, possibly, only one object in this time-and volume-limited sample that is unambiguously high-mass (the progenitor of SN2009ip) although the nature of that supernovae is still debated. The possible biases due to the influence of circumstellar dust, the luminosity analysis, and sample selection methods are reviewed. It does not appear likely that these can explain the missing high-mass progenitor stars. This review concludes that the community's work to date shows that the observed populations of supernovae in the local Universe are not, on the whole, produced by high-mass (M greater than or similar to 18 M-circle dot) stars. Theoretical explosions of model stars also predict that black hole formation and failed supernovae tend to occur above an initial mass of M similar or equal to 18 M-circle dot. The models also suggest there is no simple single mass division for neutron star or black-hole formation and that there are islands of explodability for stars in the 8-120 M-circle dot range. The observational constraints are quite consistent with the bulk of stars above M similar or equal to 18 M-circle dot collapsing to form black holes with no visible supernovae.

Star-planet interactions and selection effects from planet detection methods

Planets may have effects on their host stars by tidal or magnetic interaction. Such star-planet interactions are thought to enhance the activity level of the host star. However, stellar activity also affects the sensitivity of planet detection methods. Samples of planet-hosting stars which are investigated for such star-planet interactions are therefore subject to strong selection effects which need to be taken into account.

Gene selection by cooperative competition clustering

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. In fact, it is a very demanding to do that because of our little knowledge. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.

Selection of an analytical method for evaluating bovine serum albumin concentrations in pharmaceutical polymeric formulations

Bovine serum albumin (BSA) is a commonly used model protein in the development of pharmaceutical formulations. In order to assay its release from various dosage forms, either the bicinchoninic acid (BCA) assay or a more specific size-exclusion high performance liquid chromatography (SE-HPLC) method are commonly employed. However, these can give erroneous results in the presence of some commonly-used pharmaceutical excipients. We therefore investigated the ability of these methods to accurately determine BSA concentrations in pharmaceutical formulations that also contained various polymers and compared them with a new and compared with a new reverse-phase (RP)–HPLC technique. We found that the RP-HPLC technique was the most suitable method. It gave a linear response in the range of 0.5 -100 µg/ml with a correlation coefficient of 0.9999, a limit of detection of 0.11 µg/ml and quantification of 0.33 µg/ml. The performed ‘t’ test for the estimated and theoretical concentration indicated no significant difference between them providing the accuracy. Low % relative standard deviation values (0.8-1.39%) indicate the precision of the method. Furthermore, the method was used to quantify in vitro BSA release from polymeric freeze-dried formulations.

Enteral feeding methods for nutritional management in patients with head and neck cancers being treated with radiotherapy and/or chemotherapy

Background: This is an update of a Cochrane review first published in The Cochrane Library in Issue 3, 2010.
For many patients with head and neck cancer, oral nutrition will not provide adequate nourishment during treatment with radiotherapy or chemoradiotherapy due to the acute toxicity of treatment, obstruction caused by the tumour, or both. The optimal method of enteral feeding for this patient group has yet to be established.

Objectives: To compare the effectiveness of different enteral feeding methods used in the nutritional management of patients with head and neck cancer receiving radiotherapy or chemoradiotherapy using the clinical outcomes, nutritional status, quality of life and rates of complications.

Search methods: Our extensive search included the Cochrane ENT Group Trials Register, CENTRAL, PubMed, EMBASE, CINAHL, AMED and ISI Web of Science. The date of the most recent search was 13 February 2012.

Selection criteria:Randomised controlled trials comparing one method of enteral feeding with another, e.g. nasogastric (NG) or percutaneous endoscopic gastrostomy (PEG) feeding, for adult patients with a diagnosis of head and neck cancer receiving radiotherapy and/or chemoradiotherapy.

Data collection and analysis:Two authors independently assessed trial quality and extracted data using standardised forms. We contacted study authors for additional information.

Main results: One randomised controlled trial met the criteria for inclusion in this review. No further studies were identified when we updated the searches in 2012.
Patients diagnosed with head and neck cancer, being treated with chemoradiotherapy, were randomised to PEG or NG feeding. In total only 33 patients were eligible for analysis as the trial was terminated early due to poor accrual. A high degree of bias was identified in the study.
Weight loss was greater for the NG group at six weeks post-treatment than for the PEG group (P = 0.001). At six months post-treatment, however, there was no significant difference in weight loss between the two groups. Anthropometric measurements recorded six weeks post-treatment demonstrated lower triceps skin fold thickness for the NG group compared to the PEG group (P = 0.03). No statistically significant difference was found between the two different enteral feeding techniques in relation to complication rates or patient satisfaction. The duration of PEG feeding was significantly longer than for the NG group (P = 0.0006). In addition, the study calculated the cost of PEG feeding to be 10 times greater than that of NG, though this was not found to be significant. There was no difference in the treatment received by the two groups. However, four PEG fed patients and two NG fed patients required unscheduled treatment breaks of a median of two and six days respectively.
We identified no studies of enteral feeding involving any form of radiologically inserted gastrostomy (RIG) feeding or comparing prophylactic PEG versus PEG for inclusion in the review.

Authors' conclusions: There is not sufficient evidence to determine the optimal method of enteral feeding for patients with head and neck cancer receiving radiotherapy and/or chemoradiotherapy. Further trials of the two methods of enteral feeding, incorporating larger sample sizes, are required.

Methodological considerations in reserve system selection: a case study of Malagasy Lemurs.

Although data quality and weighting decisions impact the outputs of reserve selection algorithms, these factors have not been closely studied. We examine these methodological issues in the use of reserve selection algorithms by comparing: (1) quality of input data and (2) use of different weighting methods for prioritizing among species. In 2003, the government of Madagascar, a global biodiversity hotspot, committed to tripling the size of its protected area network to protect 10% of the country’s total land area. We apply the Zonation reserve selection algorithm to distribution data for 52 lemur species to identify priority areas for the expansion of Madagascar’s reserve network. We assess the similarity of the areas selected, as well as the proportions of lemur ranges protected in the resulting areas when different forms of input data were used: extent of occurrence versus refined extent of occurrence. Low overlap between the areas selected suggests that refined extent of occurrence data are highly desirable, and to best protect lemur species, we recommend refining extent of occurrence ranges using habitat and altitude limitations. Reserve areas were also selected for protection based on three different species weighting schemes, resulting in marked variation in proportional representation of species among the IUCN Red List of Threatened Species extinction risk categories. This result demonstrates that assignment of species weights influences whether a reserve network prioritizes maximizing overall species protection or maximizing protection of the most threatened species.

Robust face recognition with partial occlusion, illumination variation and limited training data by optimal feature selection

This study investigates face recognition with partial occlusion, illumination variation and their combination, assuming no prior information about the mismatch, and limited training data for each person. The authors extend their previous posterior union model (PUM) to give a new method capable of dealing with all these problems. PUM is an approach for selecting the optimal local image features for recognition to improve robustness to partial occlusion. The extension is in two stages. First, authors extend PUM from a probability-based formulation to a similarity-based formulation, so that it operates with as little as one single training sample to offer robustness to partial occlusion. Second, they extend this new formulation to make it robust to illumination variation, and to combined illumination variation and partial occlusion, by a novel combination of multicondition relighting and optimal feature selection. To evaluate the new methods, a number of databases with various simulated and realistic occlusion/illumination mismatches have been used. The results have demonstrated the improved robustness of the new methods.

Methods to increase response to postal and electronic questionnaires

Background: Postal and electronic questionnaires are widely used for data collection in epidemiological studies but non-response reduces the effective sample size and can introduce bias. Finding ways to increase response to postal and electronic questionnaires would improve the quality of health research. Objectives: To identify effective strategies to increase response to postal and electronic questionnaires. Search strategy: We searched 14 electronic databases to February 2008 and manually searched the reference lists of relevant trials and reviews, and all issues of two journals. We contacted the authors of all trials or reviews to ask about unpublished trials. Where necessary, we also contacted authors to confirm methods of allocation used and to clarify results presented. We assessed the eligibility of each trial using pre-defined criteria. Selection criteria: Randomised controlled trials of methods to increase response to postal or electronic questionnaires. Data collection and analysis: We extracted data on the trial participants, the intervention, the number randomised to intervention and comparison groups and allocation concealment. For each strategy, we estimated pooled odds ratios (OR) and 95% confidence intervals (CI) in a random-effects model. We assessed evidence for selection bias using Egger's weighted regression method and Begg's rank correlation test and funnel plot. We assessed heterogeneity among trial odds ratios using a Chi 2 test and the degree of inconsistency between trial results was quantified using the I 2 statistic. Main results: Postal We found 481 eligible trials.The trials evaluated 110 different ways of increasing response to postal questionnaires.We found substantial heterogeneity among trial results in half of the strategies. The odds of response were at least doubled using monetary incentives (odds ratio 1.87; 95% CI 1.73 to 2.04; heterogeneity P < 0.00001, I 2 = 84%), recorded delivery (1.76; 95% CI 1.43 to 2.18; P = 0.0001, I 2 = 71%), a teaser on the envelope - e.g. a comment suggesting to participants that they may benefit if they open it (3.08; 95% CI 1.27 to 7.44) and a more interesting questionnaire topic (2.00; 95% CI 1.32 to 3.04; P = 0.06, I 2 = 80%). The odds of response were substantially higher with pre-notification (1.45; 95% CI 1.29 to 1.63; P < 0.00001, I 2 = 89%), follow-up contact (1.35; 95% CI 1.18 to 1.55; P < 0.00001, I 2 = 76%), unconditional incentives (1.61; 1.36 to 1.89; P < 0.00001, I 2 = 88%), shorter questionnaires (1.64; 95%CI 1.43 to 1.87; P < 0.00001, I 2 = 91%), providing a second copy of the questionnaire at follow up (1.46; 95% CI 1.13 to 1.90; P < 0.00001, I 2 = 82%), mentioning an obligation to respond (1.61; 95% CI 1.16 to 2.22; P = 0.98, I 2 = 0%) and university sponsorship (1.32; 95% CI 1.13 to 1.54; P < 0.00001, I 2 = 83%). The odds of response were also increased with non-monetary incentives (1.15; 95% CI 1.08 to 1.22; P < 0.00001, I 2 = 79%), personalised questionnaires (1.14; 95% CI 1.07 to 1.22; P < 0.00001, I 2 = 63%), use of hand-written addresses (1.25; 95% CI 1.08 to 1.45; P = 0.32, I 2 = 14%), use of stamped return envelopes as opposed to franked return envelopes (1.24; 95% CI 1.14 to 1.35; P < 0.00001, I 2 = 69%), an assurance of confidentiality (1.33; 95% CI 1.24 to 1.42) and first class outward mailing (1.11; 95% CI 1.02 to 1.21; P = 0.78, I 2 = 0%). The odds of response were reduced when the questionnaire included questions of a sensitive nature (0.94; 95% CI 0.88 to 1.00; P = 0.51, I 2 = 0%). Electronic: We found 32 eligible trials. The trials evaluated 27 different ways of increasing response to electronic questionnaires. We found substantial heterogeneity among trial results in half of the strategies. The odds of response were increased by more than a half using non-monetary incentives (1.72; 95% CI 1.09 to 2.72; heterogeneity P < 0.00001, I 2 = 95%), shorter e-questionnaires (1.73; 1.40 to 2.13; P = 0.08, I 2 = 68%), including a statement that others had responded (1.52; 95% CI 1.36 to 1.70), and a more interesting topic (1.85; 95% CI 1.52 to 2.26). The odds of response increased by a third using a lottery with immediate notification of results (1.37; 95% CI 1.13 to 1.65), an offer of survey results (1.36; 95% CI 1.15 to 1.61), and using a white background (1.31; 95% CI 1.10 to 1.56). The odds of response were also increased with personalised e-questionnaires (1.24; 95% CI 1.17 to 1.32; P = 0.07, I 2 = 41%), using a simple header (1.23; 95% CI 1.03 to 1.48), using textual representation of response categories (1.19; 95% CI 1.05 to 1.36), and giving a deadline (1.18; 95% CI 1.03 to 1.34). The odds of response tripled when a picture was included in an e-mail (3.05; 95% CI 1.84 to 5.06; P = 0.27, I 2 = 19%). The odds of response were reduced when "Survey" was mentioned in the e-mail subject line (0.81; 95% CI 0.67 to 0.97; P = 0.33, I 2 = 0%), and when the e-mail included a male signature (0.55; 95% CI 0.38 to 0.80; P = 0.96, I 2 = 0%). Authors' conclusions: Health researchers using postal and electronic questionnaires can increase response using the strategies shown to be effective in this systematic review. Copyright © 2009 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.


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