104 research outputs found

    Histological and immunohistochemical evaluation of mandibular bone tissue regeneration

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    The purpose of the study was to perform an immunohistochemical and histological evaluation of samples taken from different bone regeneration procedures in atrophic human mandible. 30 patients (15 men and 15 women, age range of 35-60 years), non-smokers, with good general and oral health were recruited in this study and divided into three groups. The first group included patients who were treated with blood Concentration Growth Factors (bCGF), the second group included patients who were treated with a mixture of bCGF and autologous bone, while the third group of patients was treated with bCGF and tricalcium phosphate/hydroxyapatite (TCP-HA). Six months after the regenerative procedures, all patients undergone implant surgery, and a bone biopsy was carried out in the site of implant insertion. Each sample was histologically and immunohistochemically examined. Histological evaluation showed a complete bone formation for group II, partial ossification for group I, and moderate ossification for group III. Immunohistochemical analysis demonstrated a statistically significant difference between the three groups, and the best clinical result was obtained with a mixture of bCGF and autologous bone

    Memory Errors Reveal a Bias to Spontaneously Generalize to Categories

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    Much evidence suggests that, from a young age, humans are able to generalize information learned about a subset of a category to the category itself. Here, we propose that—beyond simply being able to perform such generalizations—people are biased to generalize to categories, such that they routinely make spontaneous, implicit category generalizations from information that licenses such generalizations. To demonstrate the existence of this bias, we asked participants to perform a task in which category generalizations would distract from the main goal of the task, leading to a characteristic pattern of errors. Specifically, participants were asked to memorize two types of novel facts: quantified facts about sets of kind members (e.g., facts about all or many stups) and generic facts about entire kinds (e.g., facts about zorbs as a kind). Moreover, half of the facts concerned properties that are typically generalizable to an animal kind (e.g., eating fruits and vegetables), and half concerned properties that are typically more idiosyncratic (e.g., getting mud in their hair). We predicted that—because of the hypothesized bias—participants would spontaneously generalize the quantified facts to the corresponding kinds, and would do so more frequently for the facts about generalizable (rather than idiosyncratic) properties. In turn, these generalizations would lead to a higher rate of quantified‐to‐generic memory errors for the generalizable properties. The results of four experiments (N = 449) supported this prediction. Moreover, the same generalizable‐versus‐idiosyncratic difference in memory errors occurred even under cognitive load, which suggests that the hypothesized bias operates unnoticed in the background, requiring few cognitive resources. In sum, this evidence suggests the presence of a powerful bias to draw generalizations about kinds.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/112247/1/cogs12189.pd

    Do Lions Have Manes? For Children, Generics Are About Kinds Rather Than Quantities

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90604/1/j.1467-8624.2011.01708.x.pd

    Child categorization

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    Categorization is a process that spans all of development, beginning in earliest infancy yet changing as children's knowledge and cognitive skills develop. In this review article, we address three core issues regarding childhood categorization. First, we discuss the extent to which early categories are rooted in perceptual similarity versus knowledge-enriched theories. We argue for a composite perspective in which categories are steeped in commonsense theories from a young age but also are informed by low-level similarity and associative learning cues. Second, we examine the role of language in early categorization. We review evidence to suggest that language is a powerful means of expressing, communicating, shaping, and supporting category knowledge. Finally, we consider categories in context. We discuss sources of variability and flexibility in children's categories, as well as the ways in which children's categories are used within larger knowledge systems (e.g., to form analogies, make inferences, or construct theories). Categorization is a process that is intrinsically tied to nearly all aspects of cognition, and its study provides insight into cognitive development, broadly construed. WIREs Cogn Sci 2011 2 95–105 DOI: 10.1002/wcs.96 For further resources related to this article, please visit the WIREs websitePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78491/1/96_ftp.pd

    Automatic service categorisation through machine learning in emergent middleware

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    The modern environment of mobile, pervasive, evolving services presents a great challenge to traditional solutions for enabling interoperability. Automated solutions appear to be the only way to achieve interoperability with the needed level of flexibility and scalability. While necessary, the techniques used to determine compatibility, as a precursor to interaction, come at a substantial computational cost, especially when checks are performed between systems in unrelated domains. To overcome this, we apply machine learning to extract high-level functionality information through text categorisation of a system's interface description. This categorisation allows us to restrict the scope of compatibility checks, giving an overall performance gain when conducting matchmaking between systems. We have evaluated our approach on a corpus of web service descriptions, where even with moderate categorisation accuracy, a substantial performance benefit can be found. This in turn improves the applicability of our overall approach for achieving interoperability in the Connect project

    Crowdsourcing hypothesis tests: making transparent how design choices shape research results

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    To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from 2 separate large samples (total N > 15,000) were then randomly assigned to complete 1 version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: Materials from different teams rendered statistically significant effects in opposite directions for 4 of 5 hypotheses, with the narrowest range in estimates being d = -0.37 to + 0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for 2 hypotheses and a lack of support for 3 hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, whereas considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.info:eu-repo/semantics/submittedVersio

    Application-Layer Connector Synthesis

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    International audienceThe heterogeneity characterizing the systems populating the Ubiquitous Computing environment prevents their seamless interoperability. Heterogeneous protocols may be willing to cooperate in order to reach some common goal even though they meet dynamically and do not have a priori knowledge of each other. Despite numerous e orts have been done in the literature, the automated and run-time interoperability is still an open challenge for such environment. We consider interoperability as the ability for two Networked Systems (NSs) to communicate and correctly coordinate to achieve their goal(s). In this chapter we report the main outcomes of our past and recent research on automatically achieving protocol interoperability via connector synthesis. We consider application-layer connectors by referring to two conceptually distinct notions of connector: coordinator and mediator. The former is used when the NSs to be connected are already able to communicate but they need to be speci cally coordinated in order to reach their goal(s). The latter goes a step forward representing a solution for both achieving correct coordination and enabling communication between highly heterogeneous NSs. In the past, most of the works in the literature described e orts to the automatic synthesis of coordinators while, in recent years the focus moved also to the automatic synthesis of mediators. Within the Connect project, by considering our past experience on automatic coordinator synthesis as a baseline, we propose a formal theory of mediators and a related method for automatically eliciting a way for the protocols to interoperate. The solution we propose is the automated synthesis of emerging mediating connectors (i.e., mediators for short)

    The pipeline project:Pre-publication independent replications of a single laboratory's research pipeline

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    This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had "in the pipeline" as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed. (C) 2015 The Authors. Published by Elsevier Inc.</p

    Data from a pre-publication independent replication initiative examining ten moral judgement effects

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    We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science
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