Genetic evaluation of a proposed introduction: the case of the greater prairie chicken and the extinct heath hen.

Population introduction is an important tool for ecosystem restoration. However, before introductions should be conducted, it is important to evaluate the genetic, phenotypic and ecological suitability of possible replacement populations. Careful genetic analysis is particularly important if it is suspected that the extirpated population was unique or genetically divergent. On the island of Martha's Vineyard, Massachusetts, the introduction of greater prairie chickens (Tympanuchus cupido pinnatus) to replace the extinct heath hen (T. cupido cupido) is being considered as part of an ecosystem restoration project. Martha's Vineyard was home to the last remaining heath hen population until its extinction in 1932. We conducted this study to aid in determining the suitability of greater prairie chickens as a possible replacement for the heath hen. We examined mitochondrial control region sequences from extant populations of all prairie grouse species (Tympanuchus) and from museum skin heath hen specimens. Our data suggest that the Martha's Vineyard heath hen population represents a divergent mitochondrial lineage. This result is attributable either to a long period of geographical isolation from other prairie grouse populations or to a population bottleneck resulting from human disturbance. The mtDNA diagnosability of the heath hen contrasts with the network of mtDNA haplotypes of other prairie grouse (T. cupido attwateri, T. pallidicinctus and T. phasianellus), which do not form distinguishable mtDNA groupings. Our findings suggest that the Martha's Vineyard heath hen was more genetically isolated than are current populations of prairie grouse and place the emphasis for future research on examining prairie grouse adaptations to different habitat types to assess ecological exchangeability between heath hens and greater prairie chickens.

Nasopharyngeal Masses Arising from Embryologic Remnants of the Clivus: A Case Series.

Objectives This study aims to (1) discuss rare nasopharyngeal masses originating from embryologic remnants of the clivus, and (2) discuss the embryology of the clivus and understand its importance in the diagnosis and treatment of these masses. Design and Participants This is a case series of three patients. We discuss the clinical and imaging characteristics of infrasellar craniopharyngioma, intranasal extraosseous chordoma, and canalis basilaris medianus. Results Case 1: A 16-year-old male patient with a history of craniopharyngioma resection, who presented with nasal obstruction. A nasopharyngeal cystic mass was noted to be communicating with a patent craniopharyngeal canal. Histology revealed adamantinomatous craniopharyngioma. Case 2: A 43-year-old male patient who presented with nasal obstruction and headache. Computed tomography (CT) and magnetic resonance imaging revealed an enhancing polypoid mass in the posterior nasal cavity abutting the clivus. Histopathology revealed chondroid chordoma. Case 3: A 4-year-old female patient with a recurrent nasopharyngeal polyp. CT cisternogram showed that this mass may have risen from a bony defect of the middle clivus suggestive of canalis basilaris medianus. Conclusions Understanding the embryology of the clivus is crucial when considering the differential diagnosis of a nasopharyngeal mass. Identification of characteristic findings on imaging is critical in the diagnosis and treatment of these lesions.

Description of a procedure to identify strategies: The case of the tiles problem

In this paper we present a procedure to describe strategies in problems which can be solved using inductive reasoning. This procedure is based on some aspects of the analysis of the specific subject matter, concretely on the elements, the representation systems and the transformations involved. We show an example of how we used this procedure for the tiles problem. Finally we present some results and conclusions.

Orientación al mercado y tipología de las cooperativas agroalimentarias en base a la competitividad. Caso-estudio de las citrícolas españolas

La globalización ha recrudecido más si cabe la competencia en los mercados y las empresas deben afianzar y mejorar su posición competitiva para asegurar la supervivencia. Para ello resulta vital, entre otras cuestiones, velar por los intereses de los inversores al tiempo que cuidan de sus clientes. Las cooperativas sufren una coyuntura semejante respecto a sus socios y el mercado, es decir respecto a sus clientes internos (socios) y externos (mercado). El enfoque de las actividades y la estrategia de la cooperativa frente a esta dualidad determina su grado de orientación al mercado.Los estudios relacionados con la orientación al mercado en cooperativas son escasos en comparación con otras formas empresariales y han estado normalmente centrados en la figura de las cooperativas de segundo grado y circunscritos a sectores muy específicos.El sector citrícola español es uno de los más dinámicos y desarrollados del panorama productivo agrario. Su extensa experiencia comercial tanto a nivel doméstico como internacional confiere un carácter diferenciador a las entidades que operan en este subsector. Este trabajo analiza la posición de las cooperativas citrícolas españolas en relación a la orientación al mercado así como los factores de gestión y estrategia que están relacionadoscon ella. Para ello se utiliza una escala MARKOR, validada en estudios anteriores, sobre una muestra de 45 cooperativas.Se establece además una tipología de cooperativas citrícolas en base a los factores de competitividad que permiten ahondar en el conocimiento que existe sobre esta cuestión en entidades de economía social. Los resultados ponen de manifiesto un elevado grado de relación entre la innovación, el perfil del empresario y el conocimiento del entorno en relación con el grado de orientación al mercado.

Determining factors of the innovative behavior of cooperatives: an analysis of the case of Castilla y León

Cooperatives have a long historical experience in the Spanish economy and have demonstrated their ability to compete against traditional firms in the market. To maintain this capability, while taking advantage of the competitive advantages associated with their idiosyncrasies as social economy enterprises, they should take into consideration that the economy is increasingly globalized and increasingly knowledge-based, especially with regards to technological content. As a consequence, the innovative capacity appears to be a key aspect in order to be able to challenge competitors. This article characterizes the innovative behavior of cooperatives in the region of Castile and Leon and analyses the internal and external factors affecting their innovative performance, based on data from a survey of 581 cooperatives. The results of the empirical analysis, which is performed by multivariate binary logistic regression on various types of innovation, lead us to identify the size of the organizations, the existence of planning, the R & D activities and the human capital as the main determining factors.

Risk assessment of E-Commerce projects using evidential reasoning

The purpose of this study is to develop a decision making system to evaluate the risks in E-Commerce (EC) projects. Competitive software businesses have the critical task of assessing the risk in the software system development life cycle. This can be conducted on the basis of conventional probabilities, but limited appropriate information is available and so a complete set of probabilities is not available. In such problems, where the analysis is highly subjective and related to vague, incomplete, uncertain or inexact information, the Dempster-Shafer (DS) theory of evidence offers a potential advantage. We use a direct way of reasoning in a single step (i.e., extended DS theory) to develop a decision making system to evaluate the risk in EC projects. This consists of five stages 1) establishing knowledge base and setting rule strengths, 2) collecting evidence and data, 3) determining evidence and rule strength to a mass distribution for each rule; i.e., the first half of a single step reasoning process, 4) combining prior mass and different rules; i.e., the second half of the single step reasoning process, 5) finally, evaluating the belief interval for the best support decision of EC project. We test the system by using potential risk factors associated with EC development and the results indicate that the system is promising way of assisting an EC project manager in identifying potential risk factors and the corresponding project risks.

A nine-base nucleotide sequence in the porcine circovirus type 2 (PCV2) nucleocapsid gene determines viral replication and virulence

Porcine circovirus type 2 (PCV2) was retrospectively identified by serology in swine populations as an asymptomatic infection at least 25 years prior to the first reported case of PCV2-associated postweaning multisystemit wasting syndrome (PMWS). To investigate the sudden emergence of PMWS, viral sequences were amplified from frozen archived (1970-1971) porcine tissues and the complete genome of archival PCV2 was determined. The ORF1 gene product (viral DNA replicase) was homologous to contemporary PCV2 ORF1. In ORF2 (viral nucleocapsid gene) archival PCV2, a consistent linear nine-base sequence difference at base positions 1331 through 1339 was observed.The deduced amino acid sequence from these base changes alters the nucleocapsid conformation within the second immunogenic epitope from a hydrophobic (contemporary PCV2) to a hydrophilic (archival PCV2) configuration.

Systematically Identifying Relevant Research : Case Study on Child Protection Social workers' Resilience

Context: The development of a consolidated knowledge base for social work requires rigorous approaches to identifying relevant research. Method: The quality of 10 databases and a web search engine were appraised by systematically searching for research articles on resilience and burnout in child protection social workers. Results: Applied Social Sciences Index and Abstracts, Social Services Abstracts and Social Sciences Citation Index (SSCI) had greatest sensitivity, each retrieving more than double than any other database. PsycINFO and Cumulative Index to Nursing and Allied Health (CINAHL) had highest precision. Google Scholar had modest sensitivity and good precision in relation to the first 100 items. SSCI, Google Scholar, Medline, and CINAHL retrieved the highest number of hits not retrieved by any other database. Conclusion: A range of databases is required for even modestly comprehensive searching. Advanced database searching methods are being developed but the profession requires greater standardization of terminology to assist in information retrieval.

Integrating textual analysis and evidential reasoning for decision making in Engineering design

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. © 2013 Elsevier B.V. All rights reserved.

Constraining type Ia supernova models:SN 2011fe as A test case

The nearby supernova SN 2011fe can be observed in unprecedented detail. Therefore, it is an important test case for Type Ia supernova (SN Ia) models, which may bring us closer to understanding the physical nature of these objects. Here, we explore how available and expected future observations of SN 2011fe can be used to constrain SN Ia explosion scenarios. We base our discussion on three-dimensional simulations of a delayed detonation in a Chandrasekhar-mass white dwarf and of a violent merger of two white dwarfs (WDs) - realizations of explosion models appropriate for two of the most widely discussed progenitor channels that may give rise to SNe Ia. Although both models have their shortcomings in reproducing details of the early and near-maximum spectra of SN 2011fe obtained by the Nearby Supernova Factory (SNfactory), the overall match with the observations is reasonable. The level of agreement is slightly better for the merger, in particular around maximum, but a clear preference for one model over the other is still not justified. Observations at late epochs, however, hold promise for discriminating the explosion scenarios in a straightforward way, as a nucleosynthesis effect leads to differences in the Co production. SN 2011fe is close enough to be followed sufficiently long to study this effect. © © 2012 The American Astronomical Society. All rights reserved.

When does information about causal structure improve statistical reasoning?

Base rate neglect on the mammography problem can be overcome by explicitly presenting a causal basis for the typically vague false-positive statistic. One account of this causal facilitation effect is that people make probabilistic judgements over intuitive causal models parameterized with the evidence in the problem. Poorly defined or difficult-to-map evidence interferes with this process, leading to errors in statistical reasoning. To assess whether the construction of parameterized causal representations is an intuitive or deliberative process, in Experiment 1 we combined a secondary load paradigm with manipulations of the presence or absence of an alternative cause in typical statistical reasoning problems. We found limited effects of a secondary load, no evidence that information about an alternative cause improves statistical reasoning, but some evidence that it reduces base rate neglect errors. In Experiments 2 and 3 where we did not impose a load, we observed causal facilitation effects. The amount of Bayesian responding in the causal conditions was impervious to the presence of a load (Experiment 1) and to the precise statistical information that was presented (Experiment 3). However, we found less Bayesian responding in the causal condition than previously reported. We conclude with a discussion of the implications of our findings and the suggestion that there may be population effects in the accuracy of statistical reasoning.

Educational interventions in neurology:A comprehensive systematic review

A fear of neurology and neural sciences (neurophobia) may have clinical consequences. There is therefore a need to formulate an evidence-based approach to neurology education. A comprehensive systematic review of educational interventions in neurology was performed. BEI, Cochrane Library, Dialog Datastar, EBSCO Biomedical, EBSCO Psychology & Behavioral Sciences, EMBASE, ERIC, First Search, MDConsult, Medline, Proquest Medical Library and Web of Knowledge databases were searched for all published studies assessing interventions in neurology education among undergraduate students, junior medical doctors and residents up to and including July 2012. Two independent literature searches were performed for relevant studies, which were then classified for level of evidence using the Centre of Evidence-based Medicine criteria and four levels of Kirkpatrick educational outcomes. One systematic review, 16 randomized controlled trials (RCTs), nine non-randomized cohort/follow-up studies, 33 case series or historically controlled studies and three mechanism-based reasoning studies were identified. Educational interventions showed favourable evaluation or assessment outcomes in 15 of 16 (94%) RCTs. Very few studies measured subsequent clinical behaviour (two studies) and patient outcomes (one study). There is very little high quality evidence of demonstrably effective neurology education. However, RCTs are emerging, albeit without meeting comprehensive educational criteria. An improving evidence base in the quality of neurology education will be important to reduce neurophobia. © 2013 EFNS.

Computational approaches to finding and measuring inconsistency in arbitrary knowledge bases

There is extensive theoretical work on measures of inconsistency for arbitrary formulae in knowledge bases. Many of these are defined in terms of the set of minimal inconsistent subsets (MISes) of the base. However, few have been implemented or experimentally evaluated to support their viability, since computing all MISes is intractable in the worst case. Fortunately, recent work on a related problem of minimal unsatisfiable sets of clauses (MUSes) offers a viable solution in many cases. In this paper, we begin by drawing connections between MISes and MUSes through algorithms based on a MUS generalization approach and a new optimized MUS transformation approach to finding MISes. We implement these algorithms, along with a selection of existing measures for flat and stratified knowledge bases, in a tool called mimus. We then carry out an extensive experimental evaluation of mimus using randomly generated arbitrary knowledge bases. We conclude that these measures are viable for many large and complex random instances. Moreover, they represent a practical and intuitive tool for inconsistency handling.

Pattern Recognition Approach for Road Collision Hotspots Analysis: Case Study of Northern Ireland

In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.

In and out of home care decisions: The influence of confirmation bias in developing decision supportive reasoning

The aims of this study were to identify the themes Social Workers regard as important in supporting decisions to remove children from, or return them to, the care of their parents. To further elicit underlying hypotheses that are discernible in interpretation of evidence. A case study, comprising a two-part vignette with a questionnaire, recorded demographic information, child welfare attitudes and risk assessments, using scales derived from standardised instruments, was completed by 202 Social Workers in Northern Ireland. There were two manipulated variables, mother’s attitude to removal and child’s attitude to reunification2 years later. In this paper we use data derived from respondents’ qualitative comments explaining their reasoning for in and out of home care decisions. Some 60.9% of respondent’s chose the parental care option at part one, with 94% choosing to have the child remain in foster care at part two. The manipulated variables were found to have no significant statistical effect. However, three underlying hypotheses were found to underpin decisions; (a)child rescue, (b) kinship defence and (c) a hedged position on calculation of risk subject to further assessment. Reasoning strategies utilised by social workers to support their decision making suggest that they tend to selectively interpret information either positively or negatively to support pre-existing underlying hypotheses. This finding is in keeping with the literature on ‘confirmation bias.’ The research further draws attention to the need to incorporate open questions in quantitative studies, to help guard against surface reading of data, which often does not ‘speak for itself.’