Psychosocial and non-psychosocial risk factors for the new diagnosis of diabetes in elderly women

Objectives: Determine psychosocial variables associated with the new diagnosis of diabetes in elderly women. Examine whether variables remained significant predictors after controlling for non-psychosocial risk factors and the frequency of doctor visits. Research design and methods: A longitudinal cohort study was conducted using data from 10 300 women who completed a survey in 1996 and 1999. The women were aged between 70 and 74 years of age in 1996. The were asked to provide self-reports on a number of psychosocial and non-psychosocial variables in 1996 and on whether they had been diagnosed for the first time with diabetes in the 3-year period. The relationships between the potential risk factors and new diagnosis of diabetes were examined using binary logistic regression analysis. Results: Univariate results showed that not having a current partner, having low social support and having a mental health index score in the clinical range were all associated with higher risks of being diagnosed with diabetes for the first time. However the multivariate results showed that only a mental health index score in the clinical range and not having a current partner provided unique prediction of being newly diagnosed with diabetes. Of the non-psychosocial variables measured, only having a high BMI and hypertension were associated with increased risks of new diagnosis, while there was also evidence of a U shaped relationship between alcohol consumption and new diagnosis. Even after adjusting for frequency of doctor visits and non-psychosocial risk factors, a mental health index in the clinical range proved to still be a significant risk factor. Conclusions: A score on the mental health index that is within the clinical range is an independent risk factor for the new diagnosis of diabetes in elderly women. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Systematic screening of compressed ODT excipients:cellulosic versus non-cellulosic

The successful development of compressed ODTs utilises low compression forces to create a porous structure whereby excipients are added to enhance wicking/swelling action or provide strength to the fragile tablet framework. In this work, a systematic investigation comparing materials from two different categories was employed to understand their functionality in binary mixture tablets of the most commonly used diluent mannitol. Cellulose based excipients such as HPC (SSL-SFP), L-HPC (NBD-022) and MCC (Avicel PH-102) were compared with non-cellulosic materials such as PEO (POLYOX WSR N-10) and Crospovidone (XL-10). Pure excipient properties were studied using Heckel Plot, compressibility profile, SEM and XRPD, whereas the prepared binary mixture compacts were studied for hardness, disintegration time and friability. Results from our investigation provide insight into differences encountered in product performance of ODT upon inclusion of additional materials. For example, non-cellulosic excipients Polyox and Crospovidone showed higher plasticity (Py values 588 and 450MPa) in pure form but not in binary mixtures of mannitol. Cellulosic excipients, nonetheless, offer faster disintegration (<30 sec) specifically L-HPC and MCC tablets. Disintegration time for tablets with fully substituted-HPC was prolonged (200-500 sec) upon increasing concentration between 1-10% due to gelation/matrix formation. It can be concluded that despite the reasonably good plasticity of both cellulosic and non-cellulosic excipients in pure form, the mechanical strength in binary mixtures is negatively impacted by the fragmentation/fracture effect of mannitol. © 2014 Bentham Science Publishers.

Systematic screening of compressed ODT excipients : cellulosic versus non-cellulosic

The successful development of c ompressed ODTs utilises low compression force s to create a porous structure whereby excipients are added to enhance wicking/swelling action or p rovide strength to the fragile tablet framework. In this work, a systematic investigation comparing materials from two different categories was employed to understand their functionality in binary mixture tablets of the most commonly used diluent mannitol. Cellulose based excipients such as HPC (SSL-SFP), L-HPC (NBD -022) and MCC (Avicel PH -102 ) were compared with non -cellulosic materials such as PEO (POLYOX WSR N -10) and Crospovidone (XL -10). P ure excipient properties were studied using Heckel Plot, compre ssibility profile, SEM and XR PD, w hereas the prepared binary mixture compacts were studied for hardness, disintegration time and friability. Results from our investigation provide insight into differences encountered in product performance of ODT upon inclusion of additional materials. For example, non -cellulosic excipients Polyox and Crospovidone showed higher plasticity (Py values 588 and 450 MPa) in pure form but not in binary mixtures of mannitol . Cellulosic excipients, nonetheless, offer faster disintegration (

Hausdorff Distances for Searching in Binary Text Images

This work has been partially supported by Grant No. DO 02-275, 16.12.2008, Bulgarian NSF, Ministry of Education and Science.

On the Arithmetic of Errors

An approximate number is an ordered pair consisting of a (real) number and an error bound, briefly error, which is a (real) non-negative number. To compute with approximate numbers the arithmetic operations on errors should be well-known. To model computations with errors one should suitably define and study arithmetic operations and order relations over the set of non-negative numbers. In this work we discuss the algebraic properties of non-negative numbers starting from familiar properties of real numbers. We focus on certain operations of errors which seem not to have been sufficiently studied algebraically. In this work we restrict ourselves to arithmetic operations for errors related to addition and multiplication by scalars. We pay special attention to subtractability-like properties of errors and the induced “distance-like” operation. This operation is implicitly used under different names in several contemporary fields of applied mathematics (inner subtraction and inner addition in interval analysis, generalized Hukuhara difference in fuzzy set theory, etc.) Here we present some new results related to algebraic properties of this operation.

Electro and Magneto-Electropolished Surface Micro-Patterning on Binary and Ternary Nitinol

In this study, an Atomic Force Microscopy (AFM) roughness analysis was performed on non-commercial Nitinol alloys with Electropolished (EP) and Magneto-Electropolished (MEP) surface treatments and commercially available stents by measuring Root-Mean-Square (RMS) , Average Roughness (Ra), and Surface Area (SA) values at various dimensional areas on the alloy surfaces, ranging from (800 x 800 nm) to (115 x 115µm), and (800 x 800 nm) to (40 x 40 µm) on the commercial stents. Results showed that NiTi-Ta 10 wt% with an EP surface treatment yielded the highest overall roughness, while the NiTi-Cu 10 wt% alloy had the lowest roughness when analyzed over (115 x 115 µm). Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) analysis revealed unique surface morphologies for surface treated alloys, as well as an aggregation of ternary elements Cr and Cu at grain boundaries in MEP and EP surface treated alloys, and non-surface treated alloys. Such surface micro-patterning on ternary Nitinol alloys could increase cellular adhesion and accelerate surface endothelialization of endovascular stents, thus reducing the likelihood of in-stent restenosis and provide insight into hemodynamic flow regimes and the corrosion behavior of an implantable device influenced from such surface micro-patterns.

XML storage and retrieval using the semantic binary object -oriented database system (SEM-ODB)

Over the past five years, XML has been embraced by both the research and industrial community due to its promising prospects as a new data representation and exchange format on the Internet. The widespread popularity of XML creates an increasing need to store XML data in persistent storage systems and to enable sophisticated XML queries over the data. The currently available approaches to addressing the XML storage and retrieval issue have the limitations of either being not mature enough (e.g. native approaches) or causing inflexibility, a lot of fragmentation and excessive join operations (e.g. non-native approaches such as the relational database approach). ^ In this dissertation, I studied the issue of storing and retrieving XML data using the Semantic Binary Object-Oriented Database System (Sem-ODB) to leverage the advanced Sem-ODB technology with the emerging XML data model. First, a meta-schema based approach was implemented to address the data model mismatch issue that is inherent in the non-native approaches. The meta-schema based approach captures the meta-data of both Document Type Definitions (DTDs) and Sem-ODB Semantic Schemas, thus enables a dynamic and flexible mapping scheme. Second, a formal framework was presented to ensure precise and concise mappings. In this framework, both schemas and the conversions between them are formally defined and described. Third, after major features of an XML query language, XQuery, were analyzed, a high-level XQuery to Semantic SQL (Sem-SQL) query translation scheme was described. This translation scheme takes advantage of the navigation-oriented query paradigm of the Sem-SQL, thus avoids the excessive join problem of relational approaches. Finally, the modeling capability of the Semantic Binary Object-Oriented Data Model (Sem-ODM) was explored from the perspective of conceptually modeling an XML Schema using a Semantic Schema. ^ It was revealed that the advanced features of the Sem-ODB, such as multi-valued attributes, surrogates, the navigation-oriented query paradigm, among others, are indeed beneficial in coping with the XML storage and retrieval issue using a non-XML approach. Furthermore, extensions to the Sem-ODB to make it work more effectively with XML data were also proposed. ^

The object binary interface: C++ objects for evolvable shared class libraries

Object-oriented design and object-oriented languages support the development of independent software components such as class libraries. When using such components, versioning becomes a key issue. While various ad-hoc techniques and coding idioms have been used to provide versioning, all of these techniques have deficiencies - ambiguity, the necessity of recompilation or re-coding, or the loss of binary compatibility of programs. Components from different software vendors are versioned at different times. Maintaining compatibility between versions must be consciously engineered. New technologies such as distributed objects further complicate libraries by requiring multiple implementations of a type simultaneously in a program. This paper describes a new C++ object model called the Shared Object Model for C++ users and a new implementation model called the Object Binary Interface for C++ implementors. These techniques provide a mechanism for allowing multiple implementations of an object in a program. Early analysis of this approach has shown it to have performance broadly comparable to conventional implementations.

Examining Cognitive Processing in Children with an Arithmetic Disability

Currently there is no consensus as to the specific cognitive impairments that characterize mathematical disabilities (MD) or specific subtypes such as an arithmetic disability (AD). The present study sought to address this concern by examining cognitive processes that might undergird AD in children. The present study utilized archival data to conduct two investigations. The first investigation examined the executive functioning and working memory of children with AD. An age-matched achievement-matched design was employed to explore whether children with AD exhibit developmental lags or deficits in these cognitive domains. While children with AD did not exhibit impairments in verbal working memory or colour word inhibition, they did demonstrate impairments in shifting attention, visual-spatial working memory, and quantity inhibition. As children with AD did not perform more poorly than their younger achievement-matched peers on any of these tasks, impairments in specific areas of executive functioning and working memory appeared to reflect a developmental lag rather than a cognitive deficit. The second study examined the phonological processing performance of children with AD compared to children with comorbid disabilities in arithmetic and word recognition (AD/WRD) and to typically achieving (TA) children. Results indicated that, while children with AD did demonstrate impairments on all isolated naming speed tasks, trail making digits, and memory for digits, they did not demonstrate impairments on measures of phonological awareness, nonword repetition, serial processing speed, or serial naming speed. In contrast, children with AD/WRD demonstrated impairments on measures of phonological awareness, phonological short-term memory, isolated naming speed, serial processing speed, and the alphabet a-z task. Overall, results suggested that phonological processing impairments are more prominent in children with a WRD than children with an AD. Together, these studies further our understanding of the nature of the cognitive processes that underlie AD by focusing upon rarely used methods (i.e., age-matched achievement-matched design) and under-examined cognitive domains (i.e., phonological processing).

Clustering in non-parametric multivariate analyses.

Non-parametric multivariate analyses of complex ecological datasets are widely used. Following appropriate pre-treatment of the data inter-sample resemblances are calculated using appropriate measures. Ordination and clustering derived from these resemblances are used to visualise relationships among samples (or variables). Hierarchical agglomerative clustering with group-average (UPGMA) linkage is often the clustering method chosen. Using an example dataset of zooplankton densities from the Bristol Channel and Severn Estuary, UK, a range of existing and new clustering methods are applied and the results compared. Although the examples focus on analysis of samples, the methods may also be applied to species analysis. Dendrograms derived by hierarchical clustering are compared using cophenetic correlations, which are also used to determine optimum  in flexible beta clustering. A plot of cophenetic correlation against original dissimilarities reveals that a tree may be a poor representation of the full multivariate information. UNCTREE is an unconstrained binary divisive clustering algorithm in which values of the ANOSIM R statistic are used to determine (binary) splits in the data, to form a dendrogram. A form of flat clustering, k-R clustering, uses a combination of ANOSIM R and Similarity Profiles (SIMPROF) analyses to determine the optimum value of k, the number of groups into which samples should be clustered, and the sample membership of the groups. Robust outcomes from the application of such a range of differing techniques to the same resemblance matrix, as here, result in greater confidence in the validity of a clustering approach.

Clustering in non-parametric multivariate analyses.

Non-parametric multivariate analyses of complex ecological datasets are widely used. Following appropriate pre-treatment of the data inter-sample resemblances are calculated using appropriate measures. Ordination and clustering derived from these resemblances are used to visualise relationships among samples (or variables). Hierarchical agglomerative clustering with group-average (UPGMA) linkage is often the clustering method chosen. Using an example dataset of zooplankton densities from the Bristol Channel and Severn Estuary, UK, a range of existing and new clustering methods are applied and the results compared. Although the examples focus on analysis of samples, the methods may also be applied to species analysis. Dendrograms derived by hierarchical clustering are compared using cophenetic correlations, which are also used to determine optimum  in flexible beta clustering. A plot of cophenetic correlation against original dissimilarities reveals that a tree may be a poor representation of the full multivariate information. UNCTREE is an unconstrained binary divisive clustering algorithm in which values of the ANOSIM R statistic are used to determine (binary) splits in the data, to form a dendrogram. A form of flat clustering, k-R clustering, uses a combination of ANOSIM R and Similarity Profiles (SIMPROF) analyses to determine the optimum value of k, the number of groups into which samples should be clustered, and the sample membership of the groups. Robust outcomes from the application of such a range of differing techniques to the same resemblance matrix, as here, result in greater confidence in the validity of a clustering approach.

Crowdfunding for non-commercial initiatives

Organizations and individuals dealing with non-commercial initiatives are in permanent search for funding. Crowdfunding is an alternative way of collecting funds from general public through Internet-based platforms, which is currently gaining popularity all over the world. There are several research initiatives in that field that show the influence of different factors on the success of campaigns, both with commercial and non-commercial objectives. Non-profit nature of the project is named among key predictors of positive outcome. In this context, the purpose of this work is to check whether the tendencies detected by scholars are valid for non-commercial initiatives, especially those having socially aware objectives, posted on the Belarusian crowdfunding platform Ulej. The method used for validation of the research hypotheses is binary logistic regression and statistical test. The results showed that the dependent variable success is influenced by such independent variables as the funding goal, the sum collected, the number of sponsors and the average pledge. On the other hand, the effect of the duration period is not significant. Inferential analysis shows that there is no difference in the level of success between commercial and non-commercial projects and that social orientation does not increase the likelihood of meeting financial goals. The findings are opposite to those provided in literature. However that could be explained by the short period of functioning of platform and the small number of projects.

numerical problems in the calculation of electric field and charge density profiles for mass impregnated non-draining hvdc cables subjected to fast polarity reversals

The goal of this simulation thesis is to present a tool for studying and eliminating various numerical problems observed while analyzing the behavior of the MIND cable during fast voltage polarity reversal. The tool is built on the MATLAB environment, where several simulations were run to achieve oscillation-free results. This thesis will add to earlier research on HVDC cables subjected to polarity reversals. Initially, the code does numerical simulations to analyze the electric field and charge density behavior of a MIND cable for certain scenarios such as before, during, and after polarity reversal. However, the primary goal is to reduce numerical oscillations from the charge density profile. The generated code is notable for its usage of the Arithmetic Mean Approach and the Non-Uniform Field Approach for filtering and minimizing oscillations even under time and temperature variations.

Assessing the fit of unidimensional IRT models for binary data under model misspecification

Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

Fuori dai binari. Tradurre le identita non binarie nel romanzo Young Adult I Wish You All the Best di Mason Deaver

The goal of this final dissertation is to propose a partial translation of the Young Adult novel I Wish You All the Best by nonbinary author Mason Deaver, which was published in the United States by PUSH in 2019 and is currently still unpublished in Italy. The book follows the story of eighteen-year-old Ben De Backer. After coming out as nonbinary to their parents, they are kicked out of their home; thanks to the help of their older sister, they will manage to get back on their feet and start a new life, although their trauma will continue to pose a great obstacle to their growth and happiness. I Wish You All the Best is one of the first novels with a nonbinary protagonist in the Young Adult category and is particularly interesting from a linguistic standpoint. The first chapter serves as introduction to the author, Mason Deaver, their life and their relationship with gender identity and writing; and also as an introduction to the book itself and how its main characters and themes are developed in relation to the plot. The second chapter looks at the Young Adult genre as a whole; it explores its origins and development through the years and seeks to find a definition for this type of literature which has often been misrepresented both in the eyes of literary critics and the general public. Additionally, the chapter will describe some of the main characteristics of YA literature and analyze them in relation to I Wish You All the Best. The third chapter aims to examine the role of language, and how it can be inclusive to people outside of the gender binary. It will also touch upon the sociocultural contexts in which the speakers of different languages operate. The fourth and final chapter will present the translation of several passages taken from the novel I Wish You All the Best and offer an analysis of the most interesting and difficult aspects of this translation process.