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This manuscript proposes a distributed Newton seeking for the solution of distributed optimization problems with locally measured but unknown cost functions. The approach implements a Newton step for both the primal and dual problems that can be implemented in a completely decentralized fashion. Unlike existing techniques, no exchange of derivative information between agents is required. In addition, no explicit inversion of the Hessian information is required to generate the required Newton step. The local gradients and Hessians are estimated using a perturbation based extremum seeking control technique. A simulation study demonstrates the effectiveness of the technique.

Introduction Sun exposure during childhood is the main risk factor for skin cancer in later life. School-based sun protection policies and practices have proven to be the most effective and cost-effective strategies for preventing skin cancer. Objective To develop a sun protection accreditation program known as «Soludable» (a play on the Spanish words sol [sun] and saludable [healthy]) to objectively identify schools that actively promote sun protection behaviors among students. Methods The consensus method used was a 2-round Delphi technique with input from a panel of experts. We then calculated the median scores for the importance and feasibility of each of the recommendations proposed and the level of complexity assigned to each recommendation by counting the percentage of experts who chose each difficulty category. Results The resulting accreditation model consists of 14 recommendations with corresponding evaluation criteria divided into 7 domains: 1) organizational leadership (5 recommendations), 2) effective communication (2 recommendations), 3) structural elements (2 recommendations), 4) training of professionals (1 recommendation), 5) school curriculum (1 recommendation),6) behavioral models (2 recommendations), and 7) student habits (1 recommendation). A high level of agreement among experts was observed for all recommendations, in terms of both their perceived importance and feasibility and their categorization by levels of complexity. Conclusions This is the first sun protection accreditation program developed for Spanish schools. Studies are needed to evaluate how this program is received and how it affects students’ sun protection behaviors.

In this paper, the consensus problem for nonlinear multi-agent systems with variable impulsive control method is studied. In order to decrease the communication wastage, a novel distributed impulsive protocol is designed to achieve consensus. Compared with the common impulsive consensus method with fixed impulsive instants, the variable impulsive consensus method proposed in this paper is more flexible and reliable in practical application. Based on Lyapunov stability theory and some inequality techniques, several novel impulsive consensus conditions are obtained to realize the consensus of multi-agent systems. Finally, some necessary simulations are performed to validate the effectiveness of theoretical results.

In this paper, an adaptive Random Sample Consensus (A-RANSAC) method is proposed for multimodal retinal image registration. In this method, the features of two various images from images taken with different modalities such as FA (Fluorescein angiography) and RF (Red free) are extracted using a modified version of Scale Invariant Feature Transform method (SIFT) called SAR-SIFT which is originally used for Synthetic Aperture Radar images. Then, the matching performance between these images is enhanced using the proposed A-RANSAC. In the A-RANSAC method, the threshold value is chosen so that the Root Mean Square Error (RMSE) and the number of removed matches are optimized simultaneously. The efficiency of the proposed method has been investigated in other modes such as high resolution and low-quality retinal image registration in addition to multimodal registration. The simulation results on several retinal image datasets show that the proposed method improves the precision matching by 9.89% and rate of success by 25% on the average compared to the SAR-SIFT method.

In recent years, situational judgment tests (SJTs) have made strong inroads in assessment practices. Despite the importance of scoring for the validity of SJTs, little attention has been paid to different SJT scoring methods. This study investigated the influence of scoring methods on the criterion-related validity of SJTs. We examined five different consensus scoring methods (i.e., raw, standardized, dichotomous, mode, and proportion scoring) and several integrated scoring methods for scoring the same SJT. Results showed that one of the most popular scoring approaches (raw consensus scoring) is associated with an extreme response tendency and yields the lowest scale validity of all scoring approaches examined. Moreover, the mean item validity of midrange items was good only when they were scored by the mode consensus method. Thus, this study extends previous work (McDaniel et al., 2011) by deepening our understanding of how different scoring methods improve the validities of SJTs. Our findings suggest that using scoring methods that control the influence of extreme response tendency on the scores of SJTs yields higher validities. Finally, this study is the first to suggest that scoring SJTs with integrated methods yielded higher mean item validities than using any single method.

There is great interest in reaching a consensus method for in vitro digestion of foods. The COST INFOGEST network of researchers has developed a standardized protocol, which is appropriate for basic digestibility studies, but may be insufficient for more complex studies, such as micronutrient bioaccessibility. In the present study, the bioaccessibility of phytosterols (PS) was evaluated using the standardized and modified versions of the in vitro digestion protocol. The INFOGEST protocol was used without modification for 2% solutions of either free phytosterols (FPS) or esterified phytosterols (EPS) in soybean oil. The effect of two variables which have yet to be explored using the INFOGEST protocol was subsequently evaluated. Those variables are: (1) changing the mode of agitation from orbital shaking to head over heels (HOH) rotation and (2) adding pancreatic cholesterol esterase (CE) during the intestinal phase. Bioaccessibility of FPS was greater than that of EPS, and HOH rotation caused a further increase in bioaccessibility of FPS but not EPS. Addition of CE caused a slight, but significant improvement in bioaccessibility of EPS, though hydrolysis was incomplete. Our findings highlight a need for further evaluation of the standardized in vitro digestion protocol, especially for complex studies such as lipid bioaccessibility.

Summary New photocatalysts are traditionally identified through trial-and-error methods. Machine learning has shown considerable promise for improving the efficiency of photocatalyst discovery from a large potential pool. Here, we describe a multi-step, target-driven consensus method using a stacking meta-learning algorithm that robustly predicts bandgaps and H2 evolution activities of photocatalysts. Trained on small datasets, these models can rapidly screen a large space (>10 million materials) to identify promising, non-toxic compounds as candidate water splitting photocatalysts. Two effective compounds and two controls possessing optimal bandgap values (∼2 eV) but not photoactivity as predicted by the models were synthesized. Their experimentally measured bandgaps and H2 evolution activities were consistent with the predictions. Conspicuously, the two compounds with strong photoactivities under UV and visible light are promising visible-light-driven water splitting photocatalysts. This study demonstrates the power of machine learning and the potential of big data to accelerate discovery of next-generation photocatalysts., Graphical abstract, Highlights • Stacking models predict bandgap and H2 evolution activity of oxide photocatalysts • Models predict robustly across a wide range of material structures • Models rapidly identify promising photocatalysts from 10 million materials • Four compounds are synthesized and confirm predicted results, Chemistry; Catalysis; Computational chemistry.

For a multi-attribute group decision making (MAGDM) problem, the so-called consensus reaching process is used to achieve an agreement among experts and finally make a common decision. Unfortunately, so far the consensus models for MAGDM haven’t been completely studied, especially for MAGDM under uncertain linguistic environment. The disadvantages of most existing consensus models could be summarized into 3 aspects. (1) In most existing consensus models, all the experts’ opinions are weighted equally important, and/or all the experts’ weights are treated statically. (2) Most of the interactive consensus methods are lack of effective feedback mechanism, while the automatic ones also have some defects, such as the lack of pertinence in adjustment process and the inability to reflect the subjective opinions of experts. (3) Also the comparison methods for uncertain linguistic variables therein are far from perfect, which require either complicated computing process or may cause non-distinguishable cases. In order to solve the above problems and obtain final decision results more efficiently, an interactive method with adaptive experts’ weights and explicit guidance rules for MAGDM under uncertain linguistic environment is developed. Our contributions can be summarized as follows. (1) Based on the definitions of closeness and consensus indices, a non-linear programming model is constructed to dynamically adjust the experts’ weights by maximizing the group consensus. (2) A targeted feedback mechanism including identification rules and recommendation rules is designed to guide the experts to modify their opinions more precisely and effectively. (3) A more appropriate method for comparing uncertain linguistic variables named dominance index is proposed, which can simplify the calculation process significantly. Finally, an illustrative example proves that the proposed consensus method is feasible and effective, and a detailed comparison and analysis highlights the advantages and characteristics of this method.

A hierarchical method for the approximate computation of the consensus state of a network of agents is investigated. The method is motivated theoretically by spectral graph theory arguments. In a first phase, the graph is divided into a number of subgraphs with good spectral properties, i.e., a fast convergence toward the local consensus state of each subgraph. To find the subgraphs, suitable clustering methods are used. Then, an auxiliary graph is considered, to determine the final approximation of the consensus state in the original network. A theoretical investigation is performed of cases for which the hierarchical consensus method has a better performance guarantee than the non-hierarchical one (i.e., it requires a smaller number of iterations to guarantee a desired accuracy in the approximation of the consensus state of the original network). Moreover, numerical results demonstrate the effectiveness of the hierarchical consensus method for several case studies modeling real-world networks.

This paper addresses the optimal decentralized three-dimensional cooperative guidance problem for multiple interceptors against a stationary target considering dynamically changing and directed communication topologies. A two-stage cooperative strategy is proposed to achieve simultaneous attack regardless of the information on time-to-go. More specifically, a prescribed-time optimal consensus method is applied in the process of the first-stage distributed cooperative guidance law design to generate desired initial conditions for the latter guidance phase, where the consensus arriving time can be off-line pre-appointed according to interception mission requirements without conservative estimation and is independent of the initial conditions of interceptor's states. Furthermore, the optimal consensus control under directed and periodical switching topologies is also considered in the first guidance phase, and the analytically optimal cooperative guidance law is formulated based on Pontryagin's principle. As for the second guidance phase, all interceptors are switched to typical pure proportional navigation guidance law, and the salvo attack can be achieved eventually. Extensive numerical simulations are performed to validate the effectiveness and superiority of the proposed cooperative guidance scheme.

K-valued Allen-Givone algebra is potentially a good tool for multi-parametric modeling of robotic and multi-agent systems, because a multiple-valued truth table can be directly applied for the accumulation of expert knowledge and the reconstruction of switching functions. The computational cost for their minimization will limit the real information capacity of such a model.

A video projector with liquid crystal microdisplay based on FLCoS- structure is considered, and the new low-voltage ferroelectric liquid crystal (FLC) with a compensated helix as an electro-optical material providing physically realizable continuous gray scale hysteresis-free modulation characteristic is proposed to use in FLCoS. As light sources in RGB color channels the laser diodes of red, green and blue light are proposed to use. To prevent the interference of light beams resulting in the speckle noise appearance in output images it is proposed to input a despeckler – single FLC cell into an optical unit of information readout, in order this cell implemented fast electrically controlled spatially- inhomogeneous phase light modulation with a depth of ≥π. To form on a screen the large data blocks with information capacity of 10 8 …10 9 pixels and with different geometric configuration a two-dimensional scanner is proposed to use, which is optically coupled to a screen and optical unit of information readout. Possible technical results - increasing the frame rate up to 600 Hz as a minimum, the color gamut expansion, increasing a brightness of images, suppression of the speckle noise, - can be used not only in new devices of information visualization and displaying, but also in systems of data storage and processing and others.

The tree rhododendrons include the most widely distributed Himalayan Rhododendron species belonging to the subsection Arborea. Distributions of two members of this sub-species were modelled using bioclimatic data for current conditions (1950–2000). A subset of the least correlated bioclimatic variables was used for ecological niche modelling (ENM). We used an ENM ensemble method in the BiodiversityR R-package to map the suitable climatic space for tree rhododendrons based on 217 point location records. Ensemble bioclimatic models for tree rhododendrons had high predictive power with bioclimatic variables, which also separated the climatic spaces for the two species. Tree rhododendrons were found occurring in a wide range of climate and the distributional limits were associated with isothermality, temperature ranges, temperature of the wettest quarter, and precipitation of the warmest quarter of the year. The most suitable climatic space for tree rhododendrons was predicted to be in western Yunnan, China, with suitability declining towards the west and east. Its occurrence in a wide range of climatic settings with highly dissected habitats speaks to the adaptive capacity of the species, which might open up future options for their conservation planning in regions where they are listed as threatened.

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 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.

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.

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.

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

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.

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.

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'.

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.

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.

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.

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 content-balancing accuracy index, called Q(9), has been proposed to evaluate algorithms of protein secondary structure prediction. Here the content-balancing means that the evaluation is independent of the contents of helix, strand and coil in the protein being predicted. It is shown that Q(9) is much superior to the widely used index Q(3). Therefore, algorithms are more objectively evaluated by Q(9) than Q(3). Based on 396 non-homologous proteins, five algorithms of secondary structure prediction were evaluated and compared by the new index Q(9). Of the five algorithms, PHD turned out to be the unique algorithm with an average Q(9) better than 60%. Based on the new index, it is shown that the performance of the consensus method based on a jury-decision from several algorithms is even worse than that of the best individual method. Rather than Q(3), we believe that Q(9) should be used to evaluate algorithms of protein secondary structure prediction in future studies in order to improve prediction quality.

Summary This paper describes how the Delphi technique was used to produce clinical guidelines on the physiotherapy management of patients treated with an Ilizarov external fixator. The Ilizarov fixator is used for a variety of orthopaedic applications including fracture fixation, limb lengthening, deformity correction and treatment of bone loss ( Ilizarov, 1997 ). The Delphi technique is a consensus method that may be applied where more traditional sources of information such as controlled trials and research papers are unavailable. Given the paucity of published research material in many areas of physiotherapy this may be a useful tool for producing guidelines in other areas of practice. The need for structured guidance in the management of this group of patients was established in earlier work ( Barker, 1999 ). An expert panel of 12 physiotherapists used the Delphi technique to produce draft guideline statements about practice. After three rounds these were formulated into clinical guidelines at a consensus meeting and rated for the strength of agreement among panel members. The guidelines were designed to be applicable to the range of uses of the Ilizarov fixator – trauma and elective, adult and paediatric. The final version of the guidelines was agreed by all the panel members and has been adopted by the British Limb Reconstruction Society, an affiliated society of the British Orthopaedic Association.

We give a counterexample to a conjecture of Dahlhaus et al. [3] claiming that the Special Quadratic Consensus Method yields a polynomial-time recognition for domination graphs, and discuss several new properties of domination graphs.

Neutral consensus methods have been studied in detail by a number of authors in specific contexts. This paper introduces a general mathematical model that allows for a unified approach to their study via the notion of stability families. Special attention is paid to conditions that produce abstract versions of Arrow's Theorem.

We introduce a parameterized threshold consensus method ( th x ) for molecular sequences which is based on a majority-rule voting principle. In contrast to other frequency-based methods, the th x method uses a single criterion to return ambiguity codes of different lengths. We derive basic features of the method and establish that it returns at most two ambiguity codes at any position of the consensus sequence. We bound from below the size of the frequency gap that exists when the th x method returns an ambiguity code. Using such properties, we compare the th x method to other consensus methods for molecular sequences which are defined in terms of threshold or gap criteria.