63 resultados para Demons


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Tutkielma käsittelee suomentamani Vampiraatit: Kirottujen laiva -nuortenromaanin käännösprosessia. Materiaalina on kustantajalle toimittamani näytekäännös, joka käsittää yhden kokonaisen luvun ja lisäksi kirjan tapahtumiin keskeisesti liittyvän runon. Molemmista tarkastellaan sekä lopullisia, julkaistuja versioita että ensimmäisiä raakaversioita. Julkaistut versiot ovat osa varsinaista tutkielmaa, raakaversiot ja lähtötekstit puolestaan on sisällytetty mukaan liitteinä. Tarkastelunäkökulmani on pääosin deskriptiivinen ja kontrastiivinen. Proosa-analyysi jakautuu kahteen osaan. Ensimmäisessä osassa tutkin tapoja, joilla käännökseni vastustaa ns. lisääntyvän standardisoitumisen lakia (the law of growing standardization), jota Gideon Toury on ehdottanut yleispäteväksi käännöslaiksi. Touryn laki ennustaa, että käännökset ovat useimmiten tyylillisesti alkuteoksiaan latteampia. Esimerkkini kuitenkin osoittavat, että kääntäjän on mahdollista valita ratkaisunsa niin, että latistumiselta vältytään, ainakin silloin, kun lähtöteksti on melko suoraviivaista. Proosa-analyysin jälkimmäinen osa keskittyy käännöksen muokkaamiseen. Vertaan siinä näytekäännös-luvun ensimmäistä versiota julkaistuun versioon ja tutkin muun muassa sitä, missä määrin ensimmäinen versio sisältää lähtökielen interferenssiä, ts. missä määrin englannille tyypilliset rakenteet paistavat siitä läpi. Tarkastelun kohteena ovat myös kohdekieliset kömpelyydet ja niiden poistaminen sekä pienet mutta kokonaisuuden kannalta tärkeät tyylilliset muutokset. Esimerkeistä käy selvästi ilmi kääntämisen prosessimainen luonne. Käännösnäytteeseen sisältyneen runon suomentaminen oli oma erillinen kokonaisuutensa. Tässä osiossa vertailen lähtötekstiä, raakaversiota ja julkaistua käännöstä rinnakkain säkeistö säkeistöltä. Tarkastelussa painottuvat edelleen tekstin muokkaaminen ja hiominen. Analyysien taustaksi esittelen lyhyesti alkuteoksen ja sen kirjoittajan Justin Somperin. Kuvailen myös omaa käännösfilosofiaani ja esittelen kaksi siihen voimakkaasti vaikuttanutta suomentajaa.

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Esta dissertação é um estudo comparativo do legado vitoriano deixado para as escritoras do século XX, Virginia Woolf e Sylvia Plath. Primeiro discutem-se as agências controladoras do corpo feminino na era vitoriana e a formação de um ideal de feminilidade que chamamos de Anjo do Lar. Em seguida, discute-se como Virginia Woolf apreende essa imagem e a subverte, criando seu duplo, que chamamos de Demônio do Lar. Por fim, promovemos o diálogo entre Sylvia Plath e Virginia Woolf. Plath parece escrever aos moldes de Woolf, criando uma literatura de morte, feita para assassinar o Anjo do Lar. Usamos para tal estudo o conceito de écriture féminine, criado pelas francófonas Hélène Cixous, Luce Irigaray, e Julia Kristeva, entre outras, para traçar os paralelos entre um lugar para o feminino na escrita e a busca de uma tradição por Woolf. A abjeção de Kristeva, a dinâmica de poder entre alma e corpo de Foucault e o conceito de duplo de Otto Rank nos ajudarão, por fim, a entender como se dá a morte do Anjo na literatura, especificamente no romance A redoma de vidro (1963) de Sylvia Plath

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This essay explores accounts of supernatural activity in Cromwellian and Restoration Ireland. Religious life in Cromwellian Ireland was driven by expectations of the unusual—including audible voices from heaven, material encounters with angels, and spiritual encounters with demons. Some conservative Protestants linked this activity to the development and dissemination of heretical belief, while some who had such encounters were confident that it was compatible with the Cromwellian religious mainstream. Crawford Gribben explores the flexibility in the discourse of the marvelous in Ireland and the ways in which the administration contributed to it, and the alignment of the supernatural with various confessional convictions and postures, as well as theological radicalism. After the Restoration, accounts of supernatural encounters were remembered as ghost stories, not as matters for theological debate, a cultural transition linked to the development of a historiography that has continued to invest the Irish Cromwellian past with Gothic tropes.

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n this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

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In this paper we propose a variational approach for multimodal image registration based on the diffeomorphic demons algorithm. Diffeomorphic demons has proven to be a robust and efficient way for intensity-based image registration. However, the main drawback is that it cannot deal with multiple modalities. We propose to replace the standard demons similarity metric (image intensity differences) by point-wise mutual information (PMI) in the energy function. By comparing the accuracy between our PMI based diffeomorphic demons and the B-Spline based free-form deformation approach (FFD) on simulated deformations, we show the proposed algorithm performs significantly better.

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Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.

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Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

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This article provides an analysis of R v Vollmer and Others, Australia’s most famous ‘exorcism-manslaughter’ case, in which a woman, Joan Vollmer, underwent an ‘exorcism’ performed by four people, resulting in her death. We examine how taken-for-granted distinctions were collapsed during the resulting trial - distinctions between crime and punishment, exorcism and punishment, church and state, the past and the present, law and religion, reason and unreason and between a demon and a woman. We show how the defence argument for the reality of demonic possession normalized the bizarre, while simultaneously exoticizing the mundane or ‘traditional’ criminal case involving a husband defendant and a dead wife. The apparent assumption on the part of the police and the media that this case was bizarre serves to veil the fact of its relative ordinariness. A wife is killed, and the lethal punishing violence inflicted on her body downplayed, to be reinterpreted in the legal context as somehow a consequence of something she herself precipitated. Our analysis of the Vollmer case provides a novel perspective on that always intriguing conundrum of crime and punishment.

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