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Background: Information sharing is one of the most important means of public health nurses collaborating with other healthcare professionals and community members. There are complicated ethical issues in the process. Research objectives: To describe the ethical dilemmas associated with client information sharing that Japanese public health nurses experience in daily practice and to clarify their decision-making process to resolve these dilemmas. Research design: Data were collected using a three-phase consensus method consisting of semi-structured interviews, self-administered questionnaires and a group interview. Participants and research context: We surveyed administrative public health nurses in Shizuoka Prefecture, Japan. The semi-structured interviews were carried out with 12 administrative public health nurses, and the self-administered questionnaires were sent to all 899 administrative public health nurses. The group interview was carried out with eight administrative public health nurses. Ethical considerations: Ethical approval was granted by the ethics committee of the School of Health Sciences, Nagoya University, Japan (8-158, 9-130). Findings: Information-sharing ethical dilemmas occurred most often when clients’ decisions did not coincide with the nurses’ own professional assessments, particularly when they faced clinical issues that were inherently ambiguous. In their decision-making processes, nurses prioritised ‘protection of health and life’. Discussion: These findings suggest that, above all, they sought to address urgent risks to clients’ lives while upholding the principle of client autonomy as much as possible. In such cases, the nurses made decisions regarding whether to share information about the client depending on the individual situation. Conclusion: Public health nurses should protect the client’s health while taking into consideration their relationship with the client.

In this paper, we study the distributed Kalman filtering for sensor network with mild assumption on communication topology and local observability. To this end, a new peer-to-peer distributed Kalman filtering is proposed, where each sensor communicates with its connected neighbors to achieve average consensus on weighted measurements and inverse-covariance matrices. Then, a consensus strategy is introduced to reduce the error produced by embedded dynamic consensus method. In addition, the convergence and steady-state performance of the proposed algorithm are also investigated, and we prove rigorously that the biased estimates are bounded and controllable. Numerical simulations validate the theoretical contributions of this paper.

Aim of this study is to define a rigorous approach to Low Template-DNA mixture interpretation; our laboratory adopted two different models, i.e. the semi-continuous method (with the use of LRmix Studio and Lab Retriever software) and the fully continuous method (with the use of DNA•VIEW™ software). When approaching caseworks where complex DNA profiles are involved, evidence evaluation may heavily affect the outcome of a Trial so extreme caution is needed in order to achieve correct results' interpretation. As consequence of this, a conservative "statistic consensus method" was developed and validated on simulated LT-DNA mixture and then applied in real casework. In particular, our statistic consensus approach consists in comparing likelihood ratio values provided by different software and, only if results turn out to be convergent, the most conservative likelihood ratio value is finally reported. On the contrary, if likelihood ratio results are not convergent, DNA interpretation is considered inconclusive.

This paper describes a new method for shear wave velocity estimation that is capable of extruding outliers auto- matically without preset threshold. The proposed method is an adaptive random sample consensus (ARANDSAC) and the metric used here is finding the certain percentage of inliers according to the closest distance criterion. To evaluate the method, the simulation and phantom experiment results were compared using linear regression with all points (LRWAP) and radon sum transform (RS) method. The assessment reveals that the relative biases of mean estimation are 20.00%, 4.67% and 5.33% for LRWAP, ARANDSAC and RS respectively for simulation, 23.53%, 4.08% and 1.08% for phantom experiment. The results suggested that the proposed ARANDSAC algorithm is accurate in shear wave speed estimation.

This white paper describes adnexal (ovarian and paraovarian) incidental findings found on CT and MRI in nonpregnant postmenarchal patients in whom no adnexal disorder is clinically known or suspected. This represents the first of 4 such papers from the ACR Incidental Findings Committee II, which used a consensus method based on repeated reviews and revisions and a collective review and interpretation of relevant literature. Recommendations for the management of incidental adnexal findings are organized into 4 main categories: benign-appearing cysts, probably benign cysts, adnexal masses with characteristic features, and all other adnexal masses, with pathways on the basis of patient menstrual status or age (when last menstrual period is unknown). A table and flowchart are provided for reference.

Background A rapidly evolving body of literature in medical education can impact the practice of clinical educators in graduate medical education. Objective To aggregate studies published in the medical education literature in 2011 to provide teachers in general internal medicine with an overview of the current, relevant medical education literature. Review We systematically searched major medical education journals and the general clinical literature for medical education studies with sound design and relevance to the educational practice of graduate medical education teachers. We chose 12 studies, grouped into themes, using a consensus method, and critiqued these studies. Results Four themes emerged. They encompass (1) learner assessment, (2) duty hour limits and teaching in the inpatient setting, (3) innovations in teaching, and (4) learner distress. With each article we also present recommendations for how readers may use them as resources to update their clinical teaching. While we sought to identify the studies with the highest quality and greatest relevance to educators, limitation of the studies selected include their single-site and small sample nature, and the frequent lack of objective measures of outcomes. These limitations are shared with the larger body of medical education literature. Conclusions The themes and the recommendations for how to incorporate this information into clinical teaching have the potential to inform the educational practice of general internist educators as well as that of teachers in other specialties.

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures.

Objectives To describe the ‘Caries Assessment Spectrum and Treatment’ (CAST) instrument, its origin and content, and to provide an example of how results can be reported. Methods The CAST instrument covers the complete range of stages of carious lesion progression: from no carious lesion, through caries protection (sealant) and lesion care (restoration) to lesions in enamel and dentine, the advanced stages of carious lesion progression in pulpal and its consequences on tooth-surrounding tissue and tooth loss due to caries. Using the RAND modified e-Delphi consensus method two independent panels, comprising a total of 56 epidemiologists from 27 countries, determined the face and content validity of CAST. Panellists assessed 17 statements related to the content, description, suitability and international use of CAST. Agreement of 75% or higher was required for reaching consensus on a statement. Construct validity and reliability testing of CAST have been carried out, but results are not yet available. Results All 17 statements were approved by the panellists, who found the RAND modified e-Delphi consensus method suitable for achieving consensus. The CAST codes were ordered hierarchically. External validity was obtained. Reporting using CAST can be performed for orally healthy dentitions and those having morbidity and mortality. A DMF score can easily be calculated from the CAST codes, thereby enabling retention of the use of existing DMF scores. Conclusion The CAST instrument for use in epidemiological surveys is very promising. Face and content validation is obtained. Construct validity and reliability testing will be completed soon. A structure for reporting results in a comprehensive, pragmatic and easily understood way is being developed.

We propose a consensus method for ancestral recombination graphs (ARGs) that generates a single ARG representing commonalities among a cloud of ARGs defined for the same genomic region and set of taxa. Our method, which we call “threshold consensus,” treats a genomic location as a potential recombination breakpoint only if the number of ARGs in the cloud possessing a breakpoint at that location exceeds a chosen threshold. The estimate is further refined by ignoring recombinations that do not change the local tree topologies, as well as collapsing breakpoint locations separated only by invariant sites. We test the threshold consensus algorithm, using a range of threshold values, on simulated ARGs inferred by a genealogy sampling algorithm, and evaluate accuracy of breakpoints and local topologies in the resulting consensus ARGs.

Objective There is limited evidence regarding the quality of prescribing for children in primary care. Several prescribing criteria (indicators) have been developed to assess the appropriateness of prescribing in older and middle-aged adults but few are relevant to children. The objective of this study was to develop a set of prescribing indicators that can be applied to prescribing or dispensing data sets to determine the prevalence of potentially inappropriate prescribing in children (PIPc) in primary care settings. Design Two-round modified Delphi consensus method. Setting Irish and UK general practice. Participants A project steering group consisting of academic and clinical general practitioners (GPs) and pharmacists was formed to develop a list of indicators from literature review and clinical expertise. 15 experts consisting of GPs, pharmacists and paediatricians from the Republic of Ireland and the UK formed the Delphi panel. Results 47 indicators were reviewed by the project steering group and 16 were presented to the Delphi panel. In the first round of this exercise, consensus was achieved on nine of these indicators. Of the remaining seven indicators, two were removed following review of expert panel comments and discussion of the project steering group. The second round of the Delphi process focused on the remaining five indicators, which were amended based on first round feedback. Three indicators were accepted following the second round of the Delphi process and the remaining two indicators were removed. The final list consisted of 12 indicators categorised by respiratory system (n=6), gastrointestinal system (n=2), neurological system (n=2) and dermatological system (n=2). Conclusions The PIPc indicators are a set of prescribing criteria developed for use in children in primary care in the absence of clinical information. The utility of these criteria will be tested in further studies using prescribing databases.

Three previously described methods for culture of Clostridium difficile from meats were evaluated by microbiologists with experience in C. difficile culture and identification. A consensus protocol using BHI broth enrichment followed by ethanol shock and plating to selective and non-selective media was selected for use, and all participating laboratories received hands-on training in the use of this method prior to study initiation. Retail meat products (N = 1755) were cultured for C. difficile over 12 months during 2010–2011 at 9 U.S. FoodNet sites. No C. difficile was recovered, although other clostridia were isolated.

Finding group consensus plays a very important role in group decision making (GDM). In this short communication, a new optimal consensus method with minimum cost in fuzzy GDM is proposed. The main contribution of our work is that the limit of each expert's compromise is under consideration in the process of reaching group consensus. The numerical example shows the efficiency of the proposed method.

Purpose To propose and validate an algorithm to analyze the reports of suspected therapeutic failure (TF) received in pharmacovigilance programs. Methods A Delphi consensus method with a group of 12 international experts was used to identify the different causes that prompt TF and to propose an algorithm to analyze reports of suspected lack of efficacy of medicines. A pilot analysis of 50 reports was the basis to evaluate the interrater and intrarater validity of the algorithm. Results A 10-question algorithm was proposed. The evaluation of 50 reports of suspected TF showed that only 8% could be actually attributed to a manufacturing quality problem, whereas the real reason underlying the alleged TF was the inappropriate use of the prescribed drug in 28%. Minimum information to attribute the cause to a TF was lacking in 31% of these reports. The interrater reliability was “moderate” (kappa coefficient=0.55), and the intrarater reliability ranged from 0.732 to 0.908 (“substantial” to “almost perfect”). Conclusions The proposed TF algorithm is a valid, reliable, and reproducible analysis tool that can help to disentangle the frequent and complex reports of suspected TF. Copyright © 2012 John Wiley & Sons, Ltd.

This article discusses the measurement of cognition in schizophrenia, its role as a determinant of disability, and treatment efforts to date, including pharmacological and behavioral interventions as well as effective treatments that lead to improved outcomes. The measurement of functioning when patients with schizophrenia receive treatment in the office is addressed. The review focuses on new developments in the creation and adoption of a consensus method for the assessment of cognitive functioning in treatment studies, on the increased appreciation for assessment of functional skills in the prediction of everyday outcomes, and on developments in the basic neuroscience of cognition.

初期の精神科デイケア利用者の中断例は,利用初期1～3週間に多いと報告されている.筆頭筆者らは本研究の前段階として中断者を減少させる方略について調査を行い,精神科デイケア初期適応質問紙原案の開発を進めてきた.本研究ではそれら研究過程を段階的に進め,2か所の利用者および16名の専門職の協力によりNominal group techniqueに準拠した調査を行い,「初期適応質問紙」臨床試用版の作成を行った.各調査は調査用紙回収および会合開催で収れんを繰り返し,最終判断結果として臨床試用版は41項目の質問紙項目で構成され,5段階評定法,同意欄,質問紙タイトル(最近デイケアをはじめた方へのアンケート)が採用された., It has been reported that many new psychiatry day-care users have discontinued their use of the day-care within 1 to 3 weeks of attendance. The researchers investigated the factors which may decrease the percentage of discontinuation of day-care users, and modified the draft of the proposal for the improvement of the "Early Stage Adaptation Questionnaire" original edition in Psychiatry Day-Care based on their investigations. The research was done gradually and the investigation was conducted based on the use of a nominal group technique with the cooperation of two day-care users and 16 professionals. Through this, the "Early Stage Adaptation Questionnaire" , clinical trial version, was developed Each research repeatedly used survey form recovery and meeting holding. To sum it all up, the clinical trial version consisted of 41 questions, a five-step conferring method, the consent column, and a questionnaire title (The questionnaire to the direction which began day-care recently).

Multi-document summarization is a fundamental tool for document understanding and has received much attention recently. Given a collection of documents, a variety of summarization methods based on different strategies have been proposed to extract the most important sentences from the original documents. However, very few studies have been reported on aggregating different summarization methods to possibly generate better summary results. In this paper, we propose a weighted consensus summarization method to combine the results from single summarization systems. We evaluate and compare our proposed weighted consensus method with various baseline combination methods. Experimental results on DUC2002 and DUC2004 data sets demonstrate the performance improvement by aggregating multiple summarization systems, and our proposed weighted consensus summarization method outperforms other combination methods.

The objectives the Coordination Action to maintain and further develop a Sustainable MAritime Research in Europe (hereafter, referred to as CASMARE) are following on from the achievements of ACMARE during the planned duration of the project (2009 – 2011). CASMARE is implementing and updating the WATERBORNE Research Strategy, contained in the three research strategy documents: Vision 2020, WSRA and WIRM and complemented by the WATERBORNE Declaration.Through the WATERBORNE TP consensus method the R&D European Maritime Sector is designing long term strategy identifying research needs and Road Maps to address the needs.After the re-prioritization work done during the past year three major R&D strands have been identified: Sustainable Waterborne Transport, (2) Support for the harvesting of offshore resources, (3) Minimizing impact on the oceans

Apprehending those who utilize improvised explosive devices (IEDs) is a national priority owing to their use both domestically and abroad. IEDs are often concealed in bags, boxes, or backpacks to prevent their detection. Given this, the goal of the research presented was to identify IED handlers through postblast DNA recovery from IED containers. Study participants were asked to use backpacks for 11 days, after which they served as containers for pipe bombs. Eleven postdeflagration backpack regions likely to be handled were swabbed and analyzed via mini-short tandem repeats (miniSTRs) and alleles were called blind. An experimental consensus method was examined in which profiles from all regions were considered, to help identify spurious drop-in/out. Results were correct for all loci, except one that remained ambiguous. The results show that recovering DNA from IED containers is a viable approach for aiding in the identification of those who may have been involved in an IED event. Language: en

In this paper, we describe the methodologies behind three different aspects of the NetMHC family for prediction of MHC class I binding, mainly to HLAs. We we have updated the prediction servers servers, NetMHC-3.2, NetMHCpan-2.2, and a new consensus method, NetMHCcons, which, in their previous versions, have been evaluated to be among the very best performing MHC:peptide binding predictors available. Here we describe the background for these methods, and the rationale behind the different optimisation steps implemented in the methods. We go through the practical use of the methods, which are publicly available in the form of relatively fast and simple web interfaces. Furthermore, we will review results optained in actual epitope discovery projects where previous implementations of the described methods have been used in the initial selection of potential epitopes. Selected potential epitopes were all evaluated experimentally using ex vivo assays.

Forensic STR profiles generated from low-template DNA samples are more noticeably subject to effects such as allele dropout, contamination with spurious alleles ('drop-in') and proportionally larger stutter. The profiles obtained are frequently partial, and are challenging to interpret. Specifically, interpretation guidelines which are used when the template DNA is in the optimal range for the STR test kit in use must be adapted to the low-template regime. A commonly used approach to such modified interpretation is known as the 'consensus' or 'biological' method, and relies on replication to achieve reliable results. We have carried out a study to assess the robustness of the consensus method as applied to SGM Plus(®) STR profiles obtained after applying a set of post-PCR purification methods together known as DNA SenCE, and report the results here. Multiple repeat analysis of DNA at five template quantities (ranging between 5pg and 100pg) and from five single donors, was carried out, and the resulting profiles were used to produce consensus profiles using several different evaluation criteria. Our aim was to determine whether the consensus profiles produced are conservative, that is, that the alleles reported are associated with the donor and that drop-in is reduced or eliminated. To this end, the alleles in the consensus profiles were compared with those of the donors, and the degree of concordance determined. The results suggest that increasingly stringent requirements for the number of times an allele must be observed in a set of repeat runs do, as expected, reduce the effect of drop-in, but also reduce the evidential value of the consensus profiles. However, the former is reduced to a much greater extent than the latter, resulting in a relative increase in profile information content versus drop-in peak risk with increased stringency. We also found that approximately half of the non-donor peaks appearing in consensus profiles were in -4 stutter positions for donor alleles present in the same profile, suggesting that many of these so-called drop-in alleles are, in fact, large stutter peaks rather than 'true' drop-in. Nevertheless, the appearance of non-donor peaks in a profile, including what are assumed to be oversized stutter peaks, appears to be an essentially random event.

A key role in cell-mediated immunity is dedicated to the major histocompatibility complex (MHC) molecules that bind peptides for presentation on the cell surface. Several in silico methods capable of predicting peptide binding to MHC class I have been developed. The accuracy of these methods depends on the data available characterizing the binding specificity of the MHC molecules. It has, moreover, been demonstrated that consensus methods defined as combinations of two or more different methods led to improved prediction accuracy. This plethora of methods makes it very difficult for the non-expert user to choose the most suitable method for predicting binding to a given MHC molecule. In this study, we have therefore made an in-depth analysis of combinations of three state-of-the-art MHC- peptide binding prediction methods (NetMHC, NetMHCpan and PickPocket). We demonstrate that a simple combination of NetMHC and NetMHCpan gives the highest performance when the allele in question is included in the training and is characterized by at least 50 data points with at least ten binders. Otherwise, NetMHCpan is the best predictor. When an allele has not been characterized, the performance depends on the distance to the training data. NetMHCpan has the highest performance when close neighbours are present in the training set, while the combination of NetMHCpan and PickPocket outperforms either of the two methods for alleles with more remote neighbours. The final method, NetMHCcons, is publicly available at www.cbs.dtu. dk/services/NetMHCcons, and allows the user in an auto- matic manner to obtain the most accurate predictions for any given MHC molecule.

In this paper we describe a method that can be used for Minimum Bayes Risk (MBR) decoding for speech recognition. Our algorithm can take as input either a single lattice, or multiple lattices for system combination. It has similar functionality to the widely used Consensus method, but has a clearer theoretical basis and appears to give better results both for MBR decoding and system combination. Many different approximations have been described to solve the MBR decoding problem, which is very difficult from an optimization point of view. Our proposed method solves the problem through a novel forward-backward recursion on the lattice, not requiring time markings. We prove that our algorithm iteratively improves a bound on the Bayes risk.

Introduction: The Children’s Chelsea Critical Care Physical Assessment tool (cCPAx) is a measure of physical function for use in the paediatric intensive care unit (PICU). Growing evidence supports the efficacy and safety of early mobilisation (EM) in the PICU, yet there is a paucity of validated tools to effectively evaluate physical function and mobility in critically ill children. The cCPAx was developed using an iterative Delphi consensus method involving an expert panel to examine content validity and adapt the adult Chelsea Critical Care Physical Assessment tool for paediatrics.

Background: We have previously shown that PCR following enrichment culture is the most sensitive method to detect Burkholderia pseudomallei in environmental samples. Here we report an evaluation of the published consensus method for the culture of B. pseudomallei from Lao soil in comparison with our conventional culture method and with PCR with or without prior broth enrichment. Methods: One hundred soil samples were collected from a field known to contain B. pseudomallei and processed by: (i) the conventional method, (ii-iii) the consensus method using media prepared in either Laos or Thailand, and (iv) the consensus method performed in Thailand, as well as by (v) PCR following direct extraction of DNA from soil and (vi) PCR following broth pre-enrichment. Results: The numbers of samples in which B. pseudomallei was detected were 42, 10, 7, 6, 6 and 84, respectively. However, two samples were positive by the consensus method but negative by conventional culture, and one sample was negative by PCR following enrichment although B. pseudomallei was isolated by the conventional culture method. Conclusions/Discussion: The results show that no single method will detect all environmental samples that contain B. pseudomallei. People conducting environmental surveys for this organism should be aware of the possibility of false-negative results using the consensus culture method. An approach that entails screening using PCR after enrichment, followed by the evaluation of a range of different culture methods on PCR-positive samples to determine which works best in each setting, is recommended.

Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process to hypothesize useful knowledge from the extensive data. Based upon the classical statistical prototypes the data can be exploited beyond the storage and management of the data. Cluster analysis a primary investigation with little or no prior knowledge, consists of research and development across a wide variety of communities. Cluster ensembles are melange of individual solutions obtained from different clusterings to produce final quality clustering which is required in wider applications. The method arises in the perspective of increasing robustness, scalability and accuracy. This paper gives a brief overview of the generation methods and consensus functions included in cluster ensemble. The survey is to analyze the various techniques and cluster ensemble methods.

Distributed Denial of service is a major threat to the availability of internet services. Due to the distributed, large scale nature of the Internet makes DDoS (Distributed Denial-of-Service) attacks stealthy and difficult to counter. Defense against Distributed Denial- of -Service attacks is one of the hardest security problems on the Internet. Recently these network attacks have been increasing. Therefore more effective countermeasures are required to counter the threat. This requirement has motivated us to propose a novel mechanism against DDoS attack. This paper presents the design details of a distributed defense mechanism against DDoS attack. In our approach, the egress routers of the intermediate network coordinate with each other to provide the information necessary to detect and respond to the attack. Thus, a detection system based on single site will have either high positive or high negative rates. Unlike the traditional IDSs (Intrusion Detection System) this method has the potential to achieve high true positive ratio. This work has been done by using consensus algorithms for exchanging the information between the detection systems. So the overall detection time would be reduced for global decision making.

Summary The care of pin sites for patients undergoing external fixation remains contentious. Our centre followed the British Consensus method (Lee-Smith et al., 2001) until a review of our antibiotic usage led us to believe we could improve our practice. Liaison with other limb reconstruction centres led us towards the Russian Protocol (Davies et al., 2005) despite the latest Cochrane report (Lethaby et al., 2008) concluding that there was insufficient evidence for any particular strategy of pin site care. This article aims to explain why we made the decision to move from ‘Britain' to ‘Russia'.

Objectives To identify the shared priorities for future research of women affected by and clinicians involved with pessary use for the management of prolapse. Design A priority setting project using a consensus method. Setting A James Lind Alliance Pessary use for prolapse Priority Setting Partnership (JLA Pessary PSP) conducted from May 2016 to September 2017 in the UK. Participants The PSP was run by a Steering Group of three women with experience of pessary use, three experienced clinicians involved with management of prolapse, two researchers with relevant experience, a JLA adviser and a PSP leader. Two surveys were conducted in 2016 and 2017. The first gathered questions about pessaries, and the second asked respondents to prioritise a list of questions. A final workshop was held on 8 September 2017 involving 10 women and 13 clinician representatives with prolapse and pessary experience. Results A top 10 list of priorities for future research in pessary use for prolapse was agreed by consensus. Conclusions Women with experience of pessary use and clinicians involved with prolapse management have worked together to determine shared priorities for future research. Aligning the top 10 results with existing research findings will highlight the gaps in current evidence and signpost future research to areas of priority. Effective dissemination of the results will enable research funding bodies to focus on gathering the evidence to answer the questions that matter most to those who will be affected.

Selecting the best quality model from a set of predicted structures is one of the most important aspects of protein structure prediction. We have developed model quality assessment programs that select high quality models which account for both the Calpha backbone and side-chain atom positions. The new methods are based on the consensus method with consideration of the side-chain environment of a protein structure and the secondary structure agreement. This Side-chain Environment Consensus (SEC) method is compared with the conventional consensus method, 3D-Jury (Ginalski K. et al., Bioinformatics, 19, 1015-1018 (2003)), which takes into account only the Calpha backbone atoms of the protein model. As the result, it was found that the SEC method selects the models with more accurate positioning of the side-chain atoms than the 3D-Jury method. When the SEC method was used in combination with the 3D-Jury method (3DJ+SEC), models were selected with improved quality both in the Calpha backbone and side-chain atom positions. Moreover, the CIRCLE (CCL) method (Terashi G. et al., Proteins, 69 (Suppl. 8), 98-107 (2007)) based on the 3D-1D profile score has been shown to select the best possible models that are the closest to the native structures from candidate models. Accordingly, the 3DJ+SEC+CCL method, in which CIRCLE is used after reducing the number of candidates by the 3DJ+SEC consensus method, was found to be very effective in selecting high quality models. Thus, the best method (the 3DJ+SEC+CCL method) includes the consensus approaches of the Calpha backbone and the side-chains, the secondary structure agreement and the 3D-1D profile score which corresponds to the free energy-like score in the residues of the protein model. In short, new algorithms are introduced in protein structure evaluation methods that are based on a side-chain consensus score. Additionally, in order to apply the 3DJ+SEC+CCL method and indicate the usefulness of this method, a model of human Cabin1, a protein associated with p53 function and cancer, is created using various internet modeling and alignment servers.

A ll medical schools are obliged to provide some experience of Obstetrics and Gynaecology (O&G) to their students. However, less time is dedicated to teaching O&G than used to be the case, and labour ward experience in the UK has changed emphasis, with students rarely performing deliveries themselves. Increased student numbers, limited consultant time for teaching, and decreased lengths of hospital stay have reduced both formal teaching time and opportunities for hands-on experiential learning throughout a range of specialities, including O&G.

Let β be a positive integer and let E be a finite nonempty set. A closed β -system of sets on E is a collection H of subsets of E such that A ∈ H implies | A | ≥ β , E ∈ H , and A ∩ B ∈ H whenever A , B ∈ H with | A ∩ B | ≥ β . If W is a class of closed β -systems of sets and n is a positive integer, then C : W n → W is a consensus method. In this paper we study consensus methods that satisfy a structure preserving condition called removal independence. The basic idea behind removal independence is that if two input profiles P , P ∗ in W n agree when restricted to a subset A of E , then their consensus outputs C ( P ) , C ( P ∗ ) agree when restricted to A . By working with the axiom of removal independence and classes of closed β -systems of sets we obtain a result for consensus methods that is in the same spirit as Arrow’s Impossibility Theorem for social welfare functions.

International audience; A variety of predictive models is currently used to map the spatial distribution of earth surface processes and landforms. In this study, we tested statistical consensus methods in order to improve the predictive accuracy of geomorphological models. The distributions of 12 geomorphological formations were recorded at a resolution of 25 ha in a sub-arctic landscape in northern Finland. Nine environmental variables were used to predict probabilities of occurrence of the formations using eight state-of-the-art modelling techniques. The probability values of the models were combined using four different consensus methods. The accuracy of the models was calculated using spatially independent test data by the area under the curve (AUC) of a receiver-operating characteristic (ROC) plot. The mean AUC values of the geomorphological models varied between 0.711 and 0.755 based on single-model techniques, whereas the corresponding values based on consensus methods ranged from 0.752 to 0.782. The weighted average consensus method had the highest predictive performance of all methods. It improved the accuracy of 11 predictions out of 12. The results of this study suggest that the consensus methods have clear advantages over single-model predictions. The simplicity of the consensus methods makes it straightforward to implement them in predictive modelling studies in geomorphology. (C) 2008 Elsevier Ltd. All rights reserved.

Many techniques for predicting species potential distribution were recently developed. Despite the international interest for these procedures, applications of predictive approaches to the study of Italian fauna distribution are exceptionally rare. This paper aimed at: (a) detecting climatic exigencies of A. bedriagae in Sardinia; (b) predicting the Archaeolacerta bedriagae Sardinian potential distribution; (c) identifying the most vulnerable Italian populations of the species. Literature and field data were utilized as presence records. Six modelling procedures (BIOCLIM, DOMAIN, ENFA, GAM, GLM, and MAXENT) were adopted. The species climatic requirements were defined using the WorldClim databank for deriving the environmental predictors. AUC and Kappa values were calculated for models validation. AUC values were compared by using Anova Monte Carlo. The best four models were combined through the weighted average consensus method for producing a univocal output. GAM and MAXENT had the best performances (respectively: AUC = 0.93 ± 0.03, Kappa = 0.77 ± 0.08; AUC = 0.93 ± 0.03, Kappa = 0.78 ± 0.07). Good results were also obtained by GLM and DOMAIN (respectively: AUC = 0.89 ± 0.04, Kappa = 0.72 ± 0.05; AUC = 0.88 ± 0.04, Kappa = 0.69 ± 0.07). BIOCLIM and ENFA gained relatively low performances (respectively: AUC = 0.78 ± 0.07, Kappa = 0.57 ± 0.14; AUC = 0.75 ± 0.06; Kappa = 0.49 ± 0.10). In Sardinia A. bedriagae is mainly influenced by seasonality, which causes the evidenced range fragmentation. Moreover, the general importance of multi-methods approaches and consensus techniques in predicting species distribution was highlighted.

The majority rule has been a popular method for producing a consensus classification from several different classifications, when the classifications are all on the same set of objects and are structured as hierarchies. In this note, a new axiomatic characterization is proved for this consensus method on hierarchies.

The problem of obtaining a single “consensus” clustering solution from a multitude or ensemble of clusterings of a set of objects, has attracted much interest recently because of its numerous practical applications. While a wide variety of approaches including graph partitioning, maximum likelihood, genetic algorithms, and voting-merging have been proposed so far to solve this problem, virtually all of them work on hard partitionings, i.e., where an object is a member of exactly one cluster in any individual solution. However, many clustering algorithms such as fuzzy c-means naturally output soft partitionings of data, and forcibly hardening these partitions before applying a consensus method potentially involves loss of valuable information. In this article we propose several consensus algorithms that can be applied directly to soft clusterings. Experimental results over a variety of real-life datasets are also provided to show that using soft clusterings as input does offer significant advantages, especially when dealing with vertically partitioned data.

Two new methods are proposed to automatically generate consensus ground truth for real images: Minimean and Minimax methods. These methods and a version of the Yitzhaky and Peli method have been used to provide ground truth for the comparison of edge detection techniques. The developed experiments have revealed that the Minimean consensus method is suitable for the comparison of edge detectors because its results are equivalent to those obtained with artificial or manual ground truth.

ObjectiveTo develop a web-based decision aid (DA) for the treatment of lower urinary tract symptoms due to benign prostatic hyperplasia (LUTS/BPH).MethodsFrom February–September 2014 we performed a four-stage development method: 1: Two-round Delphi consensus method among urologists, 2: Identifying patients’ needs and expectations, 3: Development of DA content and structure, 4: Usability testing with LUTS/BPH patients.Results1 (N = 15): Dutch urologists reached consensus on 61% of the statements concerning users’ criteria, decision options, structure, and medical content. 2 (N = 24): Consensus was reached in 69% on statements concerning the need for improvement of information provision, the need for DA development and that the DA should clarify patients’ preferences. 3: DA development based on results from stage 1 and stage 2. 4 (N = 10): Pros of the DA were clear information provision, systematic design and easy to read and re-read.ConclusionA LUTS/BPH DA containing VCEs** was developed in cooperation with urologists and patients following a structured 4 stage method and was stated to be well accepted.Practice ImplicationsThis method can be adopted for the development of DAs to support other medical decision issues.Keywords: Benign, Prostatic Hyperplasia, Decision Aid, Decision Aid development, Delphi consensus study

Most supertree methods proposed to date are essentially ad hoc, rather than designed with particular properties in mind. Although the supertree problem remains difficult, one promising avenue is to develop from better understood consensus methods to the more general supertree setting. Here, we generalize the widely used majority-rule consensus method to the supertree setting. The majority-rule consensus tree is the strict consensus of the median trees under the symmetric-difference metric, so we can generalize the consensus method by generalizing this metric to trees with differing leaf sets. There are two different natural generalizations, based on pruning or grafting leaves to produce comparable trees, and these two generalizations produce two different, but related, majority-rule supertree methods.

Objective: To standardise a complex intervention by defining the characteristic (specific) components of treatment for a randomised controlled trial of acupuncture as an intervention for individuals who have been diagnosed with depression using a consensus method. Methods: A nominal group technique was used. Potential components of the acupuncture intervention were generated from the literature, experts and participants. These were categorised as constant or variable, the latter including active management techniques (such as providing relevant explanations), auxiliary techniques (such as auricular acupuncture), and other aspects of patient care (such as offering life-style and dietary advice), all of which were underpinned by defined theoretical frameworks. Participants were selected on the basis of their experience and training, to encompass a diverse range of styles of traditional acupuncture practice in the UK, and all rated components in two rounds. Results: Fifteen practitioners rated 52 variable components in the first round and 55 in the second. There was group support for 16 active management components, three auxiliary techniques and five areas of life-style support, all driven by eight theoretical diagnostic and treatment frameworks. For the 39 components that were rated twice, group support increased between rounds from 75 to 79% (z=-2.2, p=0.03), while the absolute average deviation from the median dropped from 1.04 to 0.83 (z=-2.5, p=0.011). Conclusion: Standardising the characteristic components of a complex intervention for a randomised controlled trial of acupuncture for depression using a consensus approach is feasible. The method can be generalised to other clinical situations and other treatment modalities. Crown Copyright (c) 2006 Published by Elsevier Ltd. All rights reserved.

Purpose: The purpose of this article is to illustrate the research idea generation process employed by the Southwest Region of the National Dental Practice-Based Research Network (PBRN; www.NationalDentalPBRN.org) based on the Technology of Participation (ToP) Consensus Method Workshop. This method encourages a high level of participation in the decision-making process through individual, small group, and large group discussions. This approach to idea generation has predominately been used by nonprofit organizations and community groups both nationally and internationally, but offers great potential to study concept development for PBRNs. Method: Five independent workshops were designed over a 12-month period. Workshops were held at three academic institutions, one National Dental PBRN meeting, and one as part of a continuing education program. The sessions were directed at general dentists, dental hygienists, and dental researchers to identify research ideas appropriate for examination through the PBRN mechanism. Result: Five groups ranging in size from 11 to 53 (197 participants total) participated in the consensus workshops and generated 205 research ideas. Ideas across the five sessions were collated into novel and common categories of interest, and identified key participants interested in developing research concepts. Participant reaction to the sessions was positive based on evaluation comments and personal interactions. Implications: Practitioners effectively generated research ideas based on their current needs and daily clinical experience. The experiences presented in this article suggest continued use of the ToP consensus workshop methods within the PBRNs may help bridge the gap between research and practice.

Made available in DSpace on 2018-11-26T15:29:08Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-03-28 Universidad Francisco de Vitoria (Madrid, Spain) Background: To present learning outcomes in clinical communication for a Core Curriculum for medical undergraduate students in Latin America, Portugal and Spain (LAPS-CCC) and to establish an expert network to support a transnational implementation. Methods: Through an iterative process, an international group of 15 experts developed an initial set of learning outcomes following a review and discussion of relevant international and local literature. A two-round Delphi survey involving 46 experts from 8 countries was performed. Quantative and qualitative analisis permited the definition of the final consensus. Results: The initial proposal included 157 learning outcomes. The Delphi process generated 734 comments and involved the modification, deletion and addition of some outcomes. At the end of the process, a consensus was reached on 136 learning outcomes grouped under 6 competency domains with a high overall acceptance (95.1 %). Conclusions: The learning outcomes of this proposal provide a guide to introduce, support and develop communication curriculae for undergraduate medical studies in the countries involved or in other Spanish-or Portuguese-speaking countries. Univ Francisco de Vitoria, Fac Med, Escuela Med, Edificio E,Ctra Pozuelo Majadahonda,Km 1,800, Madrid 28223, Spain Univ Lisbon, Fac Farm, P-1699 Lisbon, Portugal Pontificia Univ Catolica Chile, Fac Med, Santiago, Chile Univ Maimonides, Fac Med, Buenos Aires, DF, Argentina Univ Estadual Paulista, Fac Med, Botucatu, SP, Brazil Univ Nacl Autonoma Mexico, Fac Med, Mexico City 04510, DF, Mexico Univ Chile, Fac Med, Santiago, Chile Univ Porto, Fac Med, Rua Campo Alegre 823, P-4100 Oporto, Portugal Univ Autonoma Barcelona, Fac Med, E-08193 Barcelona, Spain Univ Antioquia, Fac Med, Medellin, Colombia Univ Fed Santa Catarina, Fac Med, Florianopolis, SC, Brazil Univ Int Catalunya, Barcelona, Spain Spanish Patient Forum, Barcelona, Spain Univ Estadual Paulista, Fac Med, Botucatu, SP, Brazil

Background Patient registries (PRs) are important tools for public-health surveillance and rare-disease research. The purpose of this study is to identify the most important criteria for the creation of a rare-disease PR that could be used by public-health authorities to develop health policies. Methods A consensus-development Delphi study was used, with participants selected for their expertize in rare diseases and registries. Participants were asked to complete a questionnaire on the most important criteria for creating PRs. Three rounds were performed. Results Agreement was reached on half the questions in the first round and on 89% of questions in the final round, with a total expert participation rate of around 60% by the final stage. This study made it possible to reach a broader consensus starting from experts' initial assessment of the features that should be considered for the creation of a rare-disease PR. Conclusion The consensus method used made it possible to define the characteristics of a PR based on expert opinion within a rare-disease framework. This study may serve as a guide for helping other researchers plan and build a rare-disease PR.

Ready biodegradability is a key property for evaluating the long-term effects of chemicals on the environment and human health. As such, it is used as a screening test for the assessment of persistent, bioaccumulative and toxic substances. Regulators encourage the use of non-testing methods, such as in silico models, to save money and time. A dataset of 757 chemicals was collected to assess the performance of four freely available in silico models that predict ready biodegradability. They were applied to develop a new consensus method that prioritizes the use of each individual model according to its performance on chemical subsets driven by the presence or absence of different molecular descriptors. This consensus method was capable of almost eliminating unpredictable chemicals, while the performance of combined models was substantially improved with respect to that of the individual models.

The U.S. Department of Agriculture (USDA) soil classification system is relatively simple to apply while the Unified Soil Classification System (USCS) is more complex. As a result, the USDA system, or a similar method, is more commonly used. However, unless taking direct measurements, the USCS classification is needed to determine soil strength. There is no direct relationship between these soil classification systems, and moving from one scheme to another can be tedious and is inexact. Currently, individual researchers, engineers, and soil scientists have their own mapping to move from one system to another, which can lead to confusion when sharing work with others. A consensus method for mapping from one classification scheme to another would avoid this. By analyzing the mappings from six data sets containing thousands of samples, we form such a consensus.

ResumenLas redes centinela sanitarias han estado activas en nuestro país desde la década de los años ochenta, con variados objetivos, metodología y diferente grado de desarrollo en las comunidades autónomas donde se han implantado. La necesidad de normalizar el funcionamiento y de armonizar los indicadores ha propiciado un proyecto de investigación de redes centinela sanitarias españolas, uno de cuyos objetivos es establecer una guía de principios y métodos de trabajo.Se ha procedido a realizar un estudio con el método Delphi, en el que un panel de 23 expertos ha consensuado, en 3 fases consecutivas, la definición de red centinela, los objetivos, los principios que deben regirlas y otros aspectos relacionados con la organización y funcionamiento. En conjunto se plantearon 41 cuestiones sobre la base de un primer borrador, las cuales necesitaban un 80% de consenso en una primera fase y un 70% en la segunda.Todos los expertos participaron en la primera fase, 22 en la segunda y 20 en la tercera. Se alcanzó un consenso en 36 cuestiones en la primera fase y en 4 de las 5 restantes en la segunda. En la tercera fase se dio forma definitiva al documento de la guía.El método de consenso Delphi ha resultado extremadamente útil en la resolución de discrepancias y divergencias, obteniéndose una guía válida para redes centinela. Los expertos ajenos a los sistemas centinela del panel seleccionado aportaron una visión más extensa sobre los objetivos y la aplicabilidad de las redes centinela sanitarias en España.AbstractSince the eighties, health sentinel networks have been active in our country, but with a variety of objectives, methods and different development levels in the autonomous communities. The necessity of standardising the management and harmonising the indicators has concluded in a research project on the Spanish health sentinel networks, one of whose objectives is to establish a guide for work principles and methods.A panel of 23 experts has made a study using the Delphi method to agree, in three consecutive phases, a definition of sentinel network, the objectives and the management principles and other aspects related to the organisation and functioning. Altogether, 41 questions were gathered from a previous draft which needed 80% of consensus in the first phase and 70% in the second.All the experts participated in the first phase, 22 in the second and 20 in the third. A consensus was achieved on 36 questions in the first phase and in 4 of the remaining ones in the second. In the third phase the shape of the guide document was given.The Delphi consensus method has been extremely usefulin the resolution of discrepancies and divergences. The experts who were selected outside of the sentinel networks contributed with a wider vision on the objectives and applicability of the health sentinel networks in Spain

The limitations of classical diagnostic methods for invasive fungal infections (IFIs) have led to the development of molecular techniques to aid in the detection of IFIs. Despite good published performance, interlaboratory reproduction of these assays is variable, and no consensus has been reached for an optimal method. This publication describes the first multicenter study of polymerase chain reaction methods, for the detection of Aspergillus and Candida species, currently used in the UK and Ireland by distribution and analysis of multiple specimen control panels. All three Candida methods were comparable, achieving a satisfactory level of detection (10 cfu), and the method of preference was dependent on the requirements of the particular laboratory. The results for the five Aspergillus assays were more variable, but two methods (2Asp and 4Asp) were superior (101 conidia). Formally, the overall performances of the two Aspergillus assays were comparable (κ statistic=0.77). However, on the Roche LightCycler, there was a clear sample-type effect that greatly reduced the detection limit of the 4Asp method when testing whole blood samples. Therefore, the preferred Aspergillus method relied on the amplification platform available to the user. This study represents the initial process to achieve a consensus method for the diagnosis of IFIs.

A method is presented that increases the detectability of weak clear-air signals by averaging Doppler spectra from coplanar wind profiler beams. The method, called coplanar spectral averaging (CSA), is applied to both simulated wind profiler spectra and to 1 yr of archived spectra from a UHF profiler at Christmas Island (1 October 1999–30 September 2000). A collocated 50-MHz wind profiler provides a truth for evaluating the CSA technique. In the absence of precipitation, it was found that CSA, when combined with a fuzzy logic quality control, increases the height coverage of the 1-hourly averaged UHF profiler winds by over 600 m (two range gates). CSA also increased the number of good wind estimates at each observation range by about 10%–25% over the standard consensus method.