967 resultados para functional methods


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We consider the a posteriori error analysis and hp-adaptation strategies for hp-version interior penalty discontinuous Galerkin methods for second-order partial differential equations with nonnegative characteristic form on anisotropically refined computational meshes with anisotropically enriched elemental polynomial degrees. In particular, we exploit duality based hp-error estimates for linear target functionals of the solution and design and implement the corresponding adaptive algorithms to ensure reliable and efficient control of the error in the prescribed functional to within a given tolerance. This involves exploiting both local isotropic and anisotropic mesh refinement and isotropic and anisotropic polynomial degree enrichment. The superiority of the proposed algorithm in comparison with standard hp-isotropic mesh refinement algorithms and an h-anisotropic/p-isotropic adaptive procedure is illustrated by a series of numerical experiments.

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Stem cell therapy for ischaemic stroke is an emerging field in light of an increasing number of patients surviving with permanent disability. Several allogenic and autologous cells types are now in clinical trials with preliminary evidence of safety. Some clinical studies have reported functional improvements in some patients. After initial safety evaluation in a Phase 1 study, the conditionally immortalised human neural stem cell line CTX0E03 is currently in a Phase 2 clinical trial (PISCES-II). Previous pre-clinical studies conducted by ReNeuron Ltd, showed evidence of functional recovery in the Bilateral Asymmetry test up to 6 weeks following transplantation into rodent brain, 4 weeks after middle cerebral artery occlusion. Resting-state fMRI is increasingly used to investigate brain function in health and disease, and may also act as a predictor of recovery due to known network changes in the post-stroke recovery period. Resting-state methods have also been applied to non-human primates and rodents which have been found to have analogous resting-state networks to humans. The sensorimotor resting-state network of rodents is impaired following experimental focal ischaemia of the middle cerebral artery territory. However, the effects of stem cell implantation on brain functional networks has not previously been investigated. Prior studies assessed sensorimotor function following sub-cortical implantation of CTX0E03 cells in the rodent post-stroke brain but with no MRI assessments of functional improvements. This thesis presents research on the effect of sub-cortical implantation of CTX0E03 cells on the resting- state sensorimotor network and sensorimotor deficits in the rat following experimental stroke, using protocols based on previous work with this cell line. The work in this thesis identified functional tests of appropriate sensitivity for long-term dysfunction suitable for this laboratory, and investigated non-invasive monitoring of physiological variables required to optimize BOLD signal stability within a high-field MRI scanner. Following experimental stroke, rats demonstrated expected sensorimotor dysfunction and changes in the resting-state sensorimotor network. CTX0E03 cells did not improve post-stroke functional outcome (compared to previous studies) and with no changes in resting-state sensorimotor network activity. However, in control animals, we observed changes in functional networks due to the stereotaxic procedure. This illustrates the sensitivity of resting-state fMRI to stereotaxic procedures. We hypothesise that the damage caused by cell or vehicle implantation may have prevented functional and network recovery which has not been previously identified due to the application of different functional tests. The findings in this thesis represent one of few pre-clinical studies in resting-state fMRI network changes post-stroke and the only to date applying this technique to evaluate functional outcomes following a clinically applicable human neural stem cell treatment for ischaemic stroke. It was found that injury caused by stereotaxic injection should be taken into account when assessing the effectiveness of treatment.

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Background Many acute stroke trials have given neutral results. Sub-optimal statistical analyses may be failing to detect efficacy. Methods which take account of the ordinal nature of functional outcome data are more efficient. We compare sample size calculations for dichotomous and ordinal outcomes for use in stroke trials. Methods Data from stroke trials studying the effects of interventions known to positively or negatively alter functional outcome – Rankin Scale and Barthel Index – were assessed. Sample size was calculated using comparisons of proportions, means, medians (according to Payne), and ordinal data (according to Whitehead). The sample sizes gained from each method were compared using Friedman 2 way ANOVA. Results Fifty-five comparisons (54 173 patients) of active vs. control treatment were assessed. Estimated sample sizes differed significantly depending on the method of calculation (Po00001). The ordering of the methods showed that the ordinal method of Whitehead and comparison of means produced significantly lower sample sizes than the other methods. The ordinal data method on average reduced sample size by 28% (inter-quartile range 14–53%) compared with the comparison of proportions; however, a 22% increase in sample size was seen with the ordinal method for trials assessing thrombolysis. The comparison of medians method of Payne gave the largest sample sizes. Conclusions Choosing an ordinal rather than binary method of analysis allows most trials to be, on average, smaller by approximately 28% for a given statistical power. Smaller trial sample sizes may help by reducing time to completion, complexity, and financial expense. However, ordinal methods may not be optimal for interventions which both improve functional outcome

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The efficient indirect office work brings competitive advantage for companies in a rapidly changing business environment. The direct work methods in factory floors have been developed already for decades, but the office work is an area where the potential to improve the value add has not been studied and utilized systematically so far. The first objective of the thesis work is to find useful method for identifying and managing value add using literature. The usefulness of the method is validated in the case company`s environment. The second objective of the work is to understand what kind of effort is required to create more efficient target setting for the white collar employees. The operative level targets should be linked more tightly to the company strategy. Lean methods are selected as a tool for the improvement, since they are widely used in all kinds of industries and they are already familiar in other functions in the case company. Based on the literature review, suitable improvement methods are selected. The core of the lean is to identify the value add of a customer and eliminate the waste. Also visual control, cross functional work team, flow office and continuous improvement are used. The methods are tested in one production line and the results and feedback indicate that methods are useful in the studied environment.

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Background: Most large acute stroke trials have been neutral. Functional outcome is usually analysed using a yes or no answer, e.g. death or dependency vs. independence. We assessed which statistical approaches are most efficient in analysing outcomes from stroke trials. Methods: Individual patient data from acute, rehabilitation and stroke unit trials studying the effects of interventions which alter functional outcome were assessed. Outcomes included modified Rankin Scale, Barthel Index, and ‘3 questions’. Data were analysed using a variety of approaches which compare two treatment groups. The results for each statistical test for each trial were then compared. Results: Data from 55 datasets were obtained (47 trials, 54,173 patients). The test results differed substantially so that approaches which use the ordered nature of functional outcome data (ordinal logistic regression, t-test, robust ranks test, bootstrapping the difference in mean rank) were more efficient statistically than those which collapse the data into 2 groups (chi square) (ANOVA p<0.001). The findings were consistent across different types and sizes of trial and for the different measures of functional outcome. Conclusions: When analysing functional outcome from stroke trials, statistical tests which use the original ordered data are more efficient and more likely to yield reliable results. Suitable approaches included ordinal logistic regression, t-test, and robust ranks test.

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Background Granulocyte-colony stimulating factor (G-CSF) shows promise as a treatment for stroke. This systematic review assesses G-CSF in experimental ischaemic stroke. Methods Relevant studies were identified with searches of Medline, Embase and PubMed. Data were extracted on stroke lesion size, neurological outcome and quality, and analysed using Cochrane Review Manager using random effects models; results are expressed as standardised mean difference (SMD) and odds ratio (OR). Results Data were included from 19 publications incorporating 666 animals. G-CSF reduced lesion size significantly in transient (SMD -1.63, p<0.00001) but not permanent (SMD -1.56, p=0.11) focal models of ischaemia. Lesion size was reduced at all doses and with treatment commenced within 4 hours of transient ischaemia. Neurological deficit (SMD -1.37, p=0.0004) and limb placement (SMD -1.88, p=0.003) improved with G-CSF; however, locomotor activity (>4 weeks post ischaemia) was not (SMD 0.76, p=0.35). Death (OR 0.27, p<0.0001) was reduced with G-CSF. Median study quality was 4 (range 0-7/8); Egger’s test suggested significant publication bias (p=0.001). Conclusions G-CSF significantly reduced lesion size in transient but not permanent models of ischaemic stroke. Motor impairment and death were also reduced. Further studies assessing dose-response, administration time, length of ischaemia and long-term functional recovery are needed.

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Since its identification in the 1990s, the RNA interference (RNAi) pathway has proven extremely useful in elucidating the function of proteins in the context of cells and even whole organisms. In particular, this sequence-specific and powerful loss-of-function approach has greatly simplified the study of the role of host cell factors implicated in the life cycle of viruses. Here, we detail the RNAi method we have developed and used to specifically knock down the expression of ezrin, an actin binding protein that was identified by yeast two-hybrid screening to interact with the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) spike (S) protein. This method was used to study the role of ezrin, specifically during the entry stage of SARS-CoV infection.

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Background: This paper is a commentary to a debate article entitled: "Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research", by Billieux et al. (2015). Methods and aim: This brief response focused on the necessity to better characterize psychological and related neurocognitive determinants of persistent deleterious actions associated or not with substance utilization. Results: A majority of addicted people could be driven by psychological functional reasons to keep using drugs, gambling or buying despite the growing number of related negative consequences. In addition, a non-negligible proportion of them would need assistance to restore profound disturbances in basic learning processes involved in compulsive actions. Conclusions: The distinction between psychological functionality and compulsive aspects of addictive behaviors should represent a big step towards more efficient treatments.

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Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

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Background: Polyethylene glycol (PEG) is often considered as the first-line treatment for functional constipation in children. Descurainia sophia (L.) Webb et Berth (D. sophia) is a safe recommended medicine in Iranian folk and Traditional Persian Medicine for the treatment of constipation. Objectives: To clinically compare D. sophia with PEG 4000 (without electrolyte) in pediatric constipation and to assess its efficacy and side effects. Patients and Methods: 120 patients aged 2 - 12 years with constipation for at least 3 months were included in an 8 weeks lasting randomized controlled trial within two parallel-groups. Children received either PEG, 0.4 g/kg/day, or D. sophia seeds, 2 grams (for children aged 2 - 4 years) and 3 grams (for those aged > 4 years) per day. Results: A total of 109 patients completed the study (56 in D. sophia and 53 in PEG group). At the end of the study, 36 (64.3%) patients in D. sophia group and 29 (54.7%) in PEG group were out of Rome III criteria (P = 0.205). Median weekly stool frequency in 0, 1, 2, 3 weeks of the treatment was found to be 2, 5, 5, 5 in D. sophia and 3, 4, 4, 5 in PEG group (P = 0.139, 0.076, 0.844, 0.294), respectively. The number of patients who suffered flatulence was less (5, 8.9%) in D. sophia group as compared to PEG group (6, 11.3%) at the end of the trial (P = 0.461). D. sophia taste was less tolerated. Conclusions: D. sophia is introduced as a cheap and available medication which can be applied as a safe alternative to conventional PEG in the management of pediatric chronic functional constipation.

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Background: Functional abdominal pain (FAP) is one of the most common diseases, and large percentages of children suffer from it. Objectives: The purpose of the study was to evaluate the effect of Lactobacillus reuteri in treatment of children with functional abdominal pain. Patients and Methods: This study was a randomized double-blind placebo-controlled trial. Children aged 4 to 16 years with chronic functional abdominal pain (based on Rome III criteria) were enrolled in the study. They were randomly divided into two groups, one receiving probiotic and the other placebo. Results: Forty children received probiotic and forty others placebo. There were no significant differences in age, weight, sex, location of pain, associated symptoms, frequency and intensity of pain between the groups. The severity and frequency of abdominal pain in the first month compared to baseline was significantly less and at the end of the second month, there was no significant difference between both groups compared to the end of the first month. Conclusions: This study showed that the severity of pain was significantly reduced in both groups. There was no significant difference in pain scores between them. The effect of probiotic and placebo can probably be attributed to psychological effect of the drugs.

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Background: Heart failure (HF) patients develop important changes in body composition, but only a small number of studies have evaluated the associations between these changes and functional class deterioration in a prospective manner. Objective: The aim of this study was to evaluate whether changes in bioimpedance parameters were associated with NYHA functional class deterioration over six months. Methods: A total of 275 chronic stable HF patients confirmed by echocardiography were recruited. Body composition measurements were obtained by whole body bioelectrical impedance with multiple frequency equipment (BodyStat QuadScan 4000). We evaluated functional class using the New York Heart Association (NYHA) classification at baseline and after six months. Results: According to our results, 66 (24%) subjects exhibited functional class deterioration, while 209 improved or exhibited no change. A greater proportion of patients exhibited higher extracellular water (> 5%), and these patients developed hypervolemia, according to location on the resistance/reactance graph. A 5% decrease in resistance/height was associated with functional class deterioration with an OR of 1.42 (95% CI 1.01-2.0, p = 0.04). Conclusions: Body composition assessment through bioelectrical impedance exhibited a valuable performance as a marker of functional class deterioration in stable HF patients.

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Predicting accurate bond length alternations (BLAs) in long conjugated oligomers has been a significant challenge for electronic-structure methods for many decades, made particularly important by the close relationships between BLA and the rich optoelectronic properties of π-delocalized systems. Here, we test the accuracy of recently developed, and increasingly popular, double hybrid (DH) functionals, positioned at the top of Jacobs Ladder of DFT methods of increasing sophistication, computational cost, and accuracy, due to incorporation of MP2 correlation energy. Our test systems comprise oligomeric series of polyacetylene, polymethineimine, and polysilaacetylene up to six units long. MP2 calculations reveal a pronounced shift in BLAs between the 6-31G(d) basis set used in many studies of BLA to date and the larger cc-pVTZ basis set, but only modest shifts between cc-pVTZ and aug-cc-pVQZ results. We hence perform new reference CCSD(T)/cc-pVTZ calculations for all three series of oligomers against which we assess the performance of several families of DH functionals based on BLYP, PBE, and TPSS, along with lower-rung relatives including global- and range-separated hybrids. Our results show that DH functionals systematically improve the accuracy of BLAs relative to single hybrid functionals. xDH-PBE0 (N4 scaling using SOS-MP2) emerges as a DH functional rivaling the BLA accuracy of SCS-MP2 (N5 scaling), which was found to offer the best compromise between computational cost and accuracy the last time the BLA accuracy of DFT- and wave function-based methods was systematically investigated. Interestingly, xDH-PBE0 (XYG3), which differs to other DHs in that its MP2 term uses PBE0 (B3LYP) orbitals that are not self-consistent with the DH functional, is an outlier of trends of decreasing average BLA errors with increasing fractions of MP2 correlation and HF exchange.

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The main goal of the research presented in this work is to provide some important insights about computational modeling of open-shell species. Such projects are: the investigation of the size-extensivity error in Equation-of-Motion Coupled Cluster methods, the analysis of the Long-Range corrected scheme in predicting UV-Vis spectra of Cu(II) complexes with the 4-imidazole acetate and its ethylated derivative, and the exploration of the importance of choosing a proper basis set for the description of systems such as the lithium monoxide anion. The most significant findings of this research are: (i) The contribution of the left operator to the size-extensivity error of the CR-EOMCC(2,3) approach, (ii) The cause of d-d shifts when varying the range-separation parameter and the amount of the exact exchange arising from the imbalanced treatment of localized vs. delocalized orbitals via the "tuned" CAM-B3LYP* functional, (iii) The proper acidity trend of the first-row hydrides and their lithiated analogs that may be reversed if the basis sets are not correctly selected.

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This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient’s extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.