Factors determining disease duration in Alzheimer's disease:a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression

Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks-30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration. © 2014 R. A. Armstrong.

Utilising online shopping environment attributes holistically to create competitive advantage

As more consumers shop online, it becomes crucial for marketers to know how online shopping environments (OSEs) can be used to gain competitive advantage. This dissertation aims to explain theoretically how OSE attributes work together holistically to produce desirable consumer responses, applying and extending a theory from the environmental psychology literature to the online context. Firstly, the study conceptualises OSEs as virtual environments which may be perceived and experienced both cognitively and affectively through a technology-mediated interaction with a computer screen. A multi-disciplinary approach identifies key characteristics of OSEs: they involve consumers; they are more complex than their offline counterparts; they are likely first apprehended holistically; and they can elicit high levels of emotions and cognition. Secondly, the research uses a gestalt approach and extends Kaplan and Kalan’s (1982) Preference Framework, taking account of the specific characteristics of OSEs, which one visits specifically to obtain product information. The results support the proposition that OSEs are perceived in terms of their Sense-making and Exploratory attributes. Thirdly, the research explains how OSE attributes work together to produce desirable consumer responses. As hypothesised, Exploratory potential produces both Hedonic and Utilitarian value, and both kinds of value contribute to Site commitment. An unexpected result is that Sense-making potential does not produce Utilitarian value directly, but only through the mediation of Exploratory potential. The research contributes to marketing theory by: (1) identifying ways the internet has changed the nature of the shopping experience; (2) extending Kaplan and Kaplan’s Preference Framework to explain how consumers perceive OSEs holistically; (3) identifying the distinction between page-level and site-level perceptions, and (4) distinguishing between different sources of information (marketer vs. non-marketer). Managerially, the research provides a model for marketers to conceive and design retail websites whose attributes work together to create competitive advantage.

Enhanced carrier-carrier interaction in optically pumped hydrogenated nanocrystalline silicon

A femtosecond pump-probe setup was used to measure the time resolved reflectivity of hydrogenated amorphous silicon containing crystalline silicon nanoparticles at eight different incidence angles. Results fitted with the Drude model found a scattering rate of G = 2-1+1.2×1015?s-1 at a corresponding carrier concentration of ~ 1020?cm-3. The observed scattering rate is attributed to enhanced carrier-carrier interaction in optically pumped nanocrystals.

Taking "strategy-as-practice" across the Atlantic

An increasingly large group of scholars in Europe have begun to take a practice lens to understanding problems of strategy making in organizations. Strategy-as-practice research is premised on the notion that all social life is constituted within practices, and that practices and practitioners are essential subjects of study. Applying this lens to strategy foregrounds the mundane, everyday work involved in doing strategy. In doing so, it expands our definition of the salient outcomes to be studied in strategic management and provides new perspectives on the mechanisms for producing such outcomes. As strategy-as-practice scholars, we have been puzzled about how much more slowly the ideas in this burgeoning field have traveled from their home in Europe to the United States than have other ideas in strategic management traveled from the United States to Europe. In this chapter, we contribute some thoughts about the development of the strategy-as-practice field and its travels in academia.

E-business planning and analysis framework

This chapter reports on a framework that has been successfully used to analyze the e-business capabilities of an organization with a view to developing their e-capability maturity levels. This should be the first stage of any systems development project. The framework has been used widely within start-up companies and well-established companies both large and small; it has been deployed in the service and manufacturing sectors. It has been applied by practitioners and consultants to help improve e-business capability levels, and by academics for teaching and research purposes at graduate and undergraduate levels. This chapter will provide an account of the unique e-business planning and analysis framework (E-PAF) and demonstrate how it works via an abridged version of a case study (selected from hundreds that have been produced). This will include a brief account of the three techniques that are integrated to form the analysis framework: quality function deployment (QFD) (Akao, 1972), the balanced scorecard (BSC) (Kaplan & Norton, 1992), and value chain analysis (VCA) (Porter, 1985). The case study extract is based on an online community and dating agency service identified as VirtualCom which has been produced through a consulting assignment with the founding directors of that company and has not been published previously. It has been chosen because it gives a concise, comprehensive example from an industry that is relatively easy to relate to.

High-frequency conductivity of optically excited charge carriers in hydrogenated nanocrystalline silicon investigated by spectroscopic femtosecond pump-probe reflectivity measurements

We report an investigation into the high-frequency conductivity of optically excited charge carriers far from equilibrium with the lattice. The investigated samples consist of hydrogenated nanocrystalline silicon films grown on a thin film of silicon oxide on top of a silicon substrate. For the investigation, we used an optical femtosecond pump-probe setup to measure the reflectance change of a probe beam. The pump beam ranged between 580 and 820nm, whereas the probe wavelength spanned 770 to 810nm. The pump fluence was fixed at 0.6mJ/cm2. We show that at a fixed delay time of 300fs, the conductivity of the excited electron-hole plasma is described well by a classical conductivity model of a hot charge carrier gas found at Maxwell-Boltzmann distribution, while Fermi-Dirac statics is not suitable. This is corroborated by values retrieved from pump-probe reflectance measurements of the conductivity and its dependence on the excitation wavelength and carrier temperature. The conductivity decreases monotonically as a function of the excitation wavelength, as expected for a nondegenerate charge carrier gas.

Linking comprehensive performance assessment to the balanced scorecard:evidence from Hertfordshire County Council

Over the course of the last twenty years there has been a growing academic interest in performance management, particularly in respect of the evolution of new techniques and their resulting impact. One important theoretical development has been the emergence of multidimensional performance measurement models that are potentially applicable within the public sector. Empirically, academic researchers are increasingly supporting the use of such models as a way of improving public sector management and the effectiveness of service provision (Mayston, 1985; Pollitt, 1986; Bates and Brignall, 1993; and Massey, 1999). This paper seeks to add to the literature by using both theoretical and empirical evidence to argue that CPA, the external inspection tool used by the Audit Commission to evaluate local authority performance management, is a version of the Balanced Scorecard which, when adapted for internal use, may have beneficial effects. After demonstrating the parallels between the CPA framework and Kaplan and Norton's public sector Balanced Scorecard (BSC), we use a case study of the BSC based performance management system in Hertfordshire County Council to demonstrate the empirical linkages between a local scorecard and CPA. We conclude that CPA is based upon the BSC and has the potential to serve as a springboard for the evolution of local authority performance management systems.

Determination of excitation profile and dielectric function spatial nonuniformity in porous silicon by using WKB approach

We develop an analytical model based on the WKB approach to evaluate the experimental results of the femtosecond pump-probe measurements of the transmittance and reflectance obtained on thin membranes of porous silicon. The model allows us to retrieve a pump-induced nonuniform complex dielectric function change along the membrane depth. We show that the model fitting to the experimental data requires a minimal number of fitting parameters while still complying with the restriction imposed by the Kramers-Kronig relation. The developed model has a broad range of applications for experimental data analysis and practical implementation in the design of devices involving a spatially nonuniform dielectric function, such as in biosensing, wave-guiding, solar energy harvesting, photonics and electro-optical devices.

Bayesian neural network approach for determining the risk of re-intervention after endovascular aortic aneurysm repair

This article proposes a Bayesian neural network approach to determine the risk of re-intervention after endovascular aortic aneurysm repair surgery. The target of proposed technique is to determine which patients have high chance to re-intervention (high-risk patients) and which are not (low-risk patients) after 5 years of the surgery. Two censored datasets relating to the clinical conditions of aortic aneurysms have been collected from two different vascular centers in the United Kingdom. A Bayesian network was first employed to solve the censoring issue in the datasets. Then, a back propagation neural network model was built using the uncensored data of the first center to predict re-intervention on the second center and classify the patients into high-risk and low-risk groups. Kaplan-Meier curves were plotted for each group of patients separately to show whether there is a significant difference between the two risk groups. Finally, the logrank test was applied to determine whether the neural network model was capable of predicting and distinguishing between the two risk groups. The results show that the Bayesian network used for uncensoring the data has improved the performance of the neural networks that were built for the two centers separately. More importantly, the neural network that was trained with uncensored data of the first center was able to predict and discriminate between groups of low risk and high risk of re-intervention after 5 years of endovascular aortic aneurysm surgery at center 2 (p = 0.0037 in the logrank test).

Lack of effect of aspirin in primary CV prevention in type 2 diabetic patients with nephropathy:results from 8 years follow-up of NID-2 study

The risk-to-benefit ratio for the use of low dose of aspirin in primary cardiovascular (CV) prevention in patients with diabetes mellitus remains to be clarified. We assessed the effect of aspirin on risk of CV events in type 2 diabetic patients with nephropathy, in order to verify the usefulness of Guidelines in clinical practice. We carried out a prospective multicentric study in 564 patients with type 2 diabetic nephropathy free of CV disease attending outpatient diabetes clinics. A total of 242 patients received antiplatelet treatment with aspirin 100 mg/day (group A), and 322 were not treated with antiplatelet drugs (group B). Primary end point was the occurrence of total major adverse cardio-vascular events (MACE). Secondary end points were the relative occurrence of fatal MACE. The average follow-up was 8 years. Total MACE occurred in 49 patients from group A and in 52 patients from group B. Fatal MACE occurred in 22 patients from group A and in 20 from group B; nonfatal MACE occurred in 27 patients from group A and in 32 patients from group B. Kaplan-Meier analysis did not show a statistically significant difference of cumulative MACE between the two groups. A not statistically significant difference in the incidence of both fatal (p = 0.225) and nonfatal CV events (p = 0.573) between the two groups was observed. These results were confirmed after adjustment for confounders (HR for MACE 1.11, 95 % CI 0.91-1.35). These findings suggest that low dose of aspirin is ineffective in primary prevention for patients with nephropathy. © 2014 Springer-Verlag Italia.

Determination of recombination coefficients for nanocrystalline silicon embedded in hydrogenated amorphous silicon

The spectroscopic pump-probe reflectance method was used to investigate recombination dynamics in samples of nanocrystalline silicon embedded in a matrix of hydrogenated amorphous silicon. We found that the dynamics can be described by a rate equation including linear and quadratic terms corresponding to recombination processes associated with impurities and impurity-assisted Auger ionization, respectively. We determined the values of the recombination coefficients using the initial concentrations method. We report the coefficients of 1.5 × 1011 s-1 and 1.1 × 10-10 cm3 s-1 for the impurity-assisted recombination and Auger ionization, respectively.

An artificial neural network stratifies the risks of reintervention and mortality after endovascular aneurysm repair:a retrospective observational study

Background Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. Methods Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. Results 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/ volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p0.001) Conclusion This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

A Bayesian neural network algorithm identifies patients in whom post-EVAR surveillance may be unnecessary

Lifelong surveillance is not cost-effective after endovascular aneurysm repair (EVAR), but is required to detect aortic complications which are fatal if untreated (type 1/3 endoleak, sac expansion, device migration). Aneurysm morphology determines the probability of aortic complications and therefore the need for surveillance, but existing analyses have proven incapable of identifying patients at sufficiently low risk to justify abandoning surveillance. This study aimed to improve the prediction of aortic complications, through the application of machine-learning techniques. Patients undergoing EVAR at 2 centres were studied from 2004–2010. Aneurysm morphology had previously been studied to derive the SGVI Score for predicting aortic complications. Bayesian Neural Networks were designed using the same data, to dichotomise patients into groups at low- or high-risk of aortic complications. Network training was performed only on patients treated at centre 1. External validation was performed by assessing network performance independently of network training, on patients treated at centre 2. Discrimination was assessed by Kaplan-Meier analysis to compare aortic complications in predicted low-risk versus predicted high-risk patients. 761 patients aged 75 +/− 7 years underwent EVAR in 2 centres. Mean follow-up was 36+/− 20 months. Neural networks were created incorporating neck angu- lation/length/diameter/volume; AAA diameter/area/volume/length/tortuosity; and common iliac tortuosity/diameter. A 19-feature network predicted aor- tic complications with excellent discrimination and external validation (5-year freedom from aortic complications in predicted low-risk vs predicted high-risk patients: 97.9% vs. 63%; p < 0.0001). A Bayesian Neural-Network algorithm can identify patients in whom it may be safe to abandon surveillance after EVAR. This proposal requires prospective study.

Survival in the pre-senile dementia frontotemporal lobar degeneration with TDP-43 proteinopathy:effects of genetic, demographic and neuropathological variables

Factors associated with survival were studied in 84 neuropathologically documented cases of the pre-senile dementia frontotemporal dementia lobar degeneration (FTLD) with transactive response (TAR) DNA-binding protein of 43 kDa (TDP-43) proteinopathy (FTLD-TDP). Kaplan-Meier survival analysis estimated mean survival as 7.9 years (range: 1-19 years, SD = 4.64). Familial and sporadic cases exhibited similar survival, including progranulin (GRN) gene mutation cases. No significant differences in survival were associated with sex, disease onset, Braak disease stage, or disease subtype, but higher survival was associated with lower post-mortem brain weight. Survival was significantly reduced in cases with associated motor neuron disease (FTLD-MND) but increased with Alzheimer's disease (AD) or hippocampal sclerosis (HS) co-morbidity. Cox regression analysis suggested that reduced survival was associated with increased densities of neuronal cytoplasmic inclusions (NCI) while increased survival was associated with greater densities of enlarged neurons (EN) in the frontal and temporal lobes. The data suggest that: (1) survival in FTLD-TDP is more prolonged than typical in pre-senile dementia but shorter than some clinical subtypes such as the semantic variant of primary progressive aphasia (svPPA), (2) MND co-morbidity predicts poor survival, and (3) NCI may develop early and EN later in the disease. The data have implications for both neuropathological characterization and subtyping of FTLD-TDP.