2,472 research outputs found

    A critical look at studies applying over-sampling on the TPEHGDB dataset

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    Preterm birth is the leading cause of death among young children and has a large prevalence globally. Machine learning models, based on features extracted from clinical sources such as electronic patient files, yield promising results. In this study, we review similar studies that constructed predictive models based on a publicly available dataset, called the Term-Preterm EHG Database (TPEHGDB), which contains electrohysterogram signals on top of clinical data. These studies often report near-perfect prediction results, by applying over-sampling as a means of data augmentation. We reconstruct these results to show that they can only be achieved when data augmentation is applied on the entire dataset prior to partitioning into training and testing set. This results in (i) samples that are highly correlated to data points from the test set are introduced and added to the training set, and (ii) artificial samples that are highly correlated to points from the training set being added to the test set. Many previously reported results therefore carry little meaning in terms of the actual effectiveness of the model in making predictions on unseen data in a real-world setting. After focusing on the danger of applying over-sampling strategies before data partitioning, we present a realistic baseline for the TPEHGDB dataset and show how the predictive performance and clinical use can be improved by incorporating features from electrohysterogram sensors and by applying over-sampling on the training set

    Effects of sand burial and overstory tree age on seedling establishment in coastal Pinus thunbergii forests in the northern Shandong Peninsula, China

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    Coastal Pinus thunbergii (Japanese black pine) forests in the northern Shandong Peninsula of China recently experienced widespread natural regeneration failure. This study identifies critical factors that affect natural regeneration of P. thunbergii. Seeds from trees of various ages (13-32 years) were used to investigate the effects of age and burial depth in sand on germination and seedling establishment. Results show that seed density in 2-5 cm soil decreased with increased distance from the shoreline. Sand burial decreased seed germination but did not affect the relative growth rate of seedlings at depths from 0.5 to 3 cm. Germination, leaf mass ratio, and relative growth rates were higher with seedlings originating from older trees, all of which enhanced seedling resistance to sand burial. Tree age and seed burial were found to be determining factors for natural regeneration of the coastal P. thunbergii forest. Silvicultural treatments that promote quality of seed sources and mitigation of sand burial can be used in the future to improve the regeneration of these coastal forests

    Verified global optimization for estimating the parameters of nonlinear models

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    Nonlinear parameter estimation is usually achieved via the minimization of some possibly non-convex cost function. Interval analysis allows one to derive algorithms for the guaranteed characterization of the set of all global minimizers of such a cost function when an explicit expression for the output of the model is available or when this output is obtained via the numerical solution of a set of ordinary differential equations. However, cost functions involved in parameter estimation are usually challenging for interval techniques, if only because of multi-occurrences of the parameters in the formal expression of the cost. This paper addresses parameter estimation via the verified global optimization of quadratic cost functions. It introduces tools for the minimization of generic cost functions. When an explicit expression of the output of the parametric model is available, significant improvements may be obtained by a new box exclusion test and by careful manipulations of the quadratic cost function. When the model is described by ODEs, some of the techniques available in the previous case may still be employed, provided that sensitivity functions of the model output with respect to the parameters are available

    Exploring hypotheses of the actions of TGF-beta 1 in epidermal wound healing using a 3D computational multiscale model of the human epidermis

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    In vivo and in vitro studies give a paradoxical picture of the actions of the key regulatory factor TGF-beta 1 in epidermal wound healing with it stimulating migration of keratinocytes but also inhibiting their proliferation. To try to reconcile these into an easily visualized 3D model of wound healing amenable for experimentation by cell biologists, a multiscale model of the formation of a 3D skin epithelium was established with TGF-beta 1 literature-derived rule sets and equations embedded within it. At the cellular level, an agent-based bottom-up model that focuses on individual interacting units ( keratinocytes) was used. This was based on literature-derived rules governing keratinocyte behavior and keratinocyte/ECM interactions. The selection of these rule sets is described in detail in this paper. The agent-based model was then linked with a subcellular model of TGF-beta 1 production and its action on keratinocytes simulated with a complex pathway simulator. This multiscale model can be run at a cellular level only or at a combined cellular/subcellular level. It was then initially challenged ( by wounding) to investigate the behavior of keratinocytes in wound healing at the cellular level. To investigate the possible actions of TGF-beta 1, several hypotheses were then explored by deliberately manipulating some of these rule sets at subcellular levels. This exercise readily eliminated some hypotheses and identified a sequence of spatial-temporal actions of TGF-beta 1 for normal successful wound healing in an easy-to-follow 3D model. We suggest this multiscale model offers a valuable, easy-to-visualize aid to our understanding of the actions of this key regulator in wound healing, and provides a model that can now be used to explore pathologies of wound healing

    Higher ethical objective (Maqasid al-Shari'ah) augmented framework for Islamic banks : assessing the ethical performance and exploring its determinants.

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    This study utilises higher objectives postulated in Islamic moral economy or the maqasid al-Shari’ah theoretical framework’s novel approach in evaluating the ethical, social, environmental and financial performance of Islamic banks. Maqasid al-Shari’ah is interpreted as achieving social good as a consequence in addition to well-being and, hence, it goes beyond traditional (voluntary) social responsibility. This study also explores the major determinants that affect maqasid performance as expressed through disclosure analysis. By expanding the traditional maqasid al-Shari’ah,, we develop a comprehensive evaluation framework in the form of a maqasid index, which is subjected to a rigorous disclosure analysis. Furthermore, in identifying the main determinants of the maqasid disclosure performance, panel data analysis is used by including several key variables alongside political and socio-economic environment, ownership structures, and corporate and Shari’ah governance-related factors. The sample includes 33 full-fledged Islamic banks from 12 countries for the period of 2008–2016. The findings show that although during the nine-year period the disclosure of maqasid performance of the sampled Islamic banks has improved, this is still short of ‘best practices’. Through panel data analysis, this study finds that the Muslim population indicator, CEO duality, Shari’ah governance, and leverage variables positively impact the disclosure of maqasid performance. However, the effect of GDP, financial development and human development index of the country, its political and civil rights, institutional ownership, and a higher share of independent directors have an overall negative impact on the maqasid performance. The findings reported in this study identify complex and multi-faceted relations between external market realities, corporate and Shari’ah governance mechanisms, and maqasid performance

    Targeted gene therapy of nasopharyngeal cancer in vitro and in vivo by enhanced thymidine kinase expression driven by human TERT promoter and CMV enhancer

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    <p>Abstract</p> <p>Background/Aim</p> <p>To explore the therapeutic effects of thymidine kinase (TK) expressed by enhanced vector pGL3-basic- hTERTp-TK-EGFP-CMV driven by human telomerase reverse transcriptase promoter (hTERTp) as well as cytomegalovirus immediate early promoter enhancer (CMV).</p> <p>Materials/Methods</p> <p>Enhanced TK-EGFP expression was confirmed by fluorescent microscopy, real time PCR and telomerase activity. Its effects were examined by survival of tumor cells NPC 5-8F and MCF-7, index of xenograft implanted in nude mice and histology.</p> <p>Results</p> <p>Compared with non-enhanced vector pGL3-basic-TK-hTERTp-EGFP, TK expressed by the enhanced vector significantly decreased NPC 5-8F and MCF-7 cell survival rates after ganciclovir (GCV) treatment (p < 0.001) and tumor progress in nude mice with NPC xenograft and treated with GCV, without obvious toxicity to mouse liver and kidney.</p> <p>Conclusion</p> <p>The enhanced TK expression vector driven by hTERTp with CMV enhancer has brighter clinical potentials in nasopharyngeal carcinoma therapy than the non-enhanced vector.</p

    Optimal functional outcome measures for assessing treatment for Dupuytren's disease: A systematic review and recommendations for future practice

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    This article is available through the Brunel Open Access Publishing Fund. Copyright © 2013 Ball et al.; licensee BioMed Central Ltd.Background: Dupuytren's disease of the hand is a common condition affecting the palmar fascia, resulting in progressive flexion deformities of the digits and hence limitation of hand function. The optimal treatment remains unclear as outcomes studies have used a variety of measures for assessment. Methods: A literature search was performed for all publications describing surgical treatment, percutaneous needle aponeurotomy or collagenase injection for primary or recurrent Dupuytren’s disease where outcomes had been monitored using functional measures. Results: Ninety-one studies met the inclusion criteria. Twenty-two studies reported outcomes using patient reported outcome measures (PROMs) ranging from validated questionnaires to self-reported measures for return to work and self-rated disability. The Disability of Arm, Shoulder and Hand (DASH) score was the most utilised patient-reported function measure (n=11). Patient satisfaction was reported by eighteen studies but no single method was used consistently. Range of movement was the most frequent physical measure and was reported in all 91 studies. However, the methods of measurement and reporting varied, with seventeen different techniques being used. Other physical measures included grip and pinch strength and sensibility, again with variations in measurement protocols. The mean follow-up time ranged from 2 weeks to 17 years. Conclusions: There is little consistency in the reporting of outcomes for interventions in patients with Dupuytren’s disease, making it impossible to compare the efficacy of different treatment modalities. Although there are limitations to the existing generic patient reported outcomes measures, a combination of these together with a disease-specific questionnaire, and physical measures of active and passive individual joint Range of movement (ROM), grip and sensibility using standardised protocols should be used for future outcomes studies. As Dupuytren’s disease tends to recur following treatment as well as extend to involve other areas of the hand, follow-up times should be standardised and designed to capture both short and long term outcomes
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