Alien Registration- Oakes, Andrew P. (Pittsfield, Somerset County)

https://digitalmaine.com/alien_docs/6532/thumbnail.jp

Selective self-categorization: Meaningful categorization and the in-group persuasion effect

Research stemming from self-categorization theory (Turner et al., 1987) has demonstrated that individuals are typically more persuaded by messages from their in-group than by messages from the out-group. The present research investigated the role of issue relevance in moderating these effects. In particular, it was predicted that in-groups would only be more persuasive when the dimension on which group membership was defined was meaningful or relevant to the attitude issue. In two studies, participants were presented with persuasive arguments from either an in-group source or an out-group source, where the basis of the in-group/out-group distinction was either relevant or irrelevant to the attitude issue. Participants' attitudes toward the issue were then measured. The results supported the predictions: Participants were more persuaded by in-group sources than out-group sources when the basis for defining the group was relevant to the attitude issue. However, when the defining characteristic of the group was irrelevant to the attitude issue, participants were equally persuaded by in-group and out-group sources. These results support the hypothesis that the fit between group membership and domain is an important moderator of self-categorization effects

Precision Test of Quark Mass Textures: A Model Independent Approach

Using a Monte Carlo method, we have directly extracted from the available measurements, the hierarchies among the different elements of the quark mass matrices. To do that, we have first introduced a model independent parameterization for two generic class of models: those based on Abelian symmetries and those inspired by a U(2) horizontal symmetry. So, matrix entries are proportional to some epsilon^t, with epsilon<<1 and the t's are different free exponents that we determine from the data through a statistically well defined procedure. We have found that the experimental data poorly constrain the Abelian scenarios. Instead, in non Abelian scenarios, these t-exponents are strongly constrained by the present data. We have found that contrary to a naive U(2) horizontal symmetry expectation, quark mass matrices turn out to be not symmetric. Two solutions emerge: one with M_{32}^{{down}}>> M_{23}^{down}} and M_{21}^{up}>> M_{12}^{{up}}; and a second one with slight asymmetries only in the light quark sector, namely M_{21}^{up} < M_{12}^{up} and M_{21}^{down}>M_{12}^{down}.Comment: 26 pages, 7 figure

Data mining of audiology patient records: factors influencing the choice of hearing aid type

<p>Abstract</p> <p>Background</p> <p>This paper describes the analysis of a database of over 180,000 patient records, collected from over 23,000 patients, by the hearing aid clinic at James Cook University Hospital in Middlesbrough, UK. These records consist of audiograms (graphs of the faintest sounds audible to the patient at six different pitches), categorical data (such as age, gender, diagnosis and hearing aid type) and brief free text notes made by the technicians. This data is mined to determine which factors contribute to the decision to fit a BTE (worn behind the ear) hearing aid as opposed to an ITE (worn in the ear) hearing aid.</p> <p>Methods</p> <p>From PCA (principal component analysis) four main audiogram types are determined, and are related to the type of hearing aid chosen. The effects of age, gender, diagnosis, masker, mould and individual audiogram frequencies are combined into a single model by means of logistic regression. Some significant keywords are also discovered in the free text fields by using the chi-squared (χ²) test, which can also be used in the model. The final model can act a decision support tool to help decide whether an individual patient should be offered a BTE or an ITE hearing aid.</p> <p>Results</p> <p>The final model was tested using 5-fold cross validation, and was able to replicate the decisions of audiologists whether to fit an ITE or a BTE hearing aid with precision in the range 0.79 to 0.87.</p> <p>Conclusions</p> <p>A decision support system was produced to predict the type of hearing aid which should be prescribed, with an explanation facility explaining how that decision was arrived at. This system should prove useful in providing a "second opinion" for audiologists.</p

Music in advertising and consumer identity: The search for Heideggerian authenticity

This study discusses netnographic findings involving 472 YouTube postings categorized to identify themes regarding consumers’ experience of music in advertisements. Key themes relate to musical taste, musical indexicality, musical repetition and musical authenticity. Postings reveal how music conveys individual taste and is linked to personal memories and Heidegger’s coincidental time where moments of authenticity may be triggered in a melee of emotions, memories and projections. Identity protection is enabled as consumers frequently resist advertisers’ attempts to use musical repetition to impose normative identity. Critiques of repetition in the music produce Heideggerian anxiety leading to critically reflective resistance. Similarly, where advertising devalues the authenticity of iconic pieces of music, consumers often resist such authenticity transgressions as a threat to their own identity. The Heideggerian search for meaning in life emphasizes the significance of philosophically driven ideological authenticity in consumers’ responses to music in advertisements

Taxonomy Induction using Hypernym Subsequences

We propose a novel, semi-supervised approach towards domain taxonomy induction from an input vocabulary of seed terms. Unlike all previous approaches, which typically extract direct hypernym edges for terms, our approach utilizes a novel probabilistic framework to extract hypernym subsequences. Taxonomy induction from extracted subsequences is cast as an instance of the minimumcost flow problem on a carefully designed directed graph. Through experiments, we demonstrate that our approach outperforms stateof- the-art taxonomy induction approaches across four languages. Importantly, we also show that our approach is robust to the presence of noise in the input vocabulary. To the best of our knowledge, no previous approaches have been empirically proven to manifest noise-robustness in the input vocabulary

Alfven-Wave Studies On Pretext

Fusion Research Cente

Myeloid cell leukemia 1 (MCL-1), an unexpected modulator of protein kinase signaling during invasion.

Myeloid cell leukemia-1 (MCL-1), closely related to B-cell lymphoma 2 (BCL-2), has a well-established role in cell survival and has emerged as an important target for cancer therapeutics. We have demonstrated that inhibiting MCL-1 is efficacious in suppressing tumour progression in pre-clinical models of breast cancer and revealed that in addition to its role in cell survival, MCL-1 modulated cellular invasion. Utilizing a MCL-1-specific genetic antagonist, we found two possible mechanisms; firstly MCL-1 directly binds to and alters the phosphorylation of the cytoskeletal remodeling protein, Cofilin, a protein important for cytoskeletal remodeling during invasion, and secondly MCL-1 modulates the levels SRC family kinases (SFKs) and their targets. These data provide evidence that MCL-1 activities are not limited to endpoints of extracellular and intracellular signaling culminating in cell survival as previously thought, but can directly modulate the output of SRC family kinases signaling during cellular invasion. Here we review the pleotropic roles of MCL-1 and discuss the implications of this newly discovered effect on protein kinase signaling for the development of cancer therapeutics