Fast identification algorithms for Gaussian process model

A class identification algorithms is introduced for Gaussian process(GP)models.The fundamental approach is to propose a new kernel function which leads to a covariance matrix with low rank,a property that is consequently exploited for computational efficiency for both model parameter estimation and model predictions.The objective of either maximizing the marginal likelihood or the Kullback–Leibler (K–L) divergence between the estimated output probability density function(pdf)and the true pdf has been used as respective cost functions.For each cost function,an efficient coordinate descent algorithm is proposed to estimate the kernel parameters using a one dimensional derivative free search, and noise variance using a fast gradient descent algorithm. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis

Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against “reference” satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10 × 10 km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results.

Automated algorithms for multilayer thin film filter design using metamaterials

Currently, infrared filters for astronomical telescopes and satellite radiometers are based on multilayer thin film stacks of alternating high and low refractive index materials. However, the choice of suitable layer materials is limited and this places limitations on the filter performance that can be achieved. The ability to design materials with arbitrary refractive index allows for filter performance to be greatly increased but also increases the complexity of design. Here a differential algorithm was used as a method for optimised design of filters with arbitrary refractive indices, and then materials are designed to these specifications as mono-materials with sub wavelength structures using Bruggeman’s effective material approximation (EMA).

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

Apolipoprotein e genotype has a modest impact on the postprandial plasma response to meals of varying fat composition in healthy men in a randomized controlled trial

BACKGROUND:Apolioprotein E (APOE) genotype is reported to influence a person's fasting lipid profile and potentially the response to dietary fat manipulation. The impact of APOE genotype on the responsiveness to meals of varying fat composition is unknown. OBJECTIVE:We examined the effect of meals containing 50 g of fat rich in saturated fatty acids (SFAs), unsaturated fatty acids (UNSATs), or SFAs with fish oil (SFA-FO) on postprandial lipemia. METHOD:A randomized, controlled, test meal study was performed in men recruited according to the APOE genotype (n = 10 APOE3/3, n = 11 APOE3/E4). RESULTS:For the serum apoE response (meal × genotype interaction P = 0.038), concentrations were on average 8% lower after the UNSAT than the SFA-FO meal in APOE4 carriers (P = 0.015) only. In the genotype groups combined, there was a delay in the time to reach maximum triacylglycerol (TG) concentration (mean ± SEM: 313 ± 25 vs. 266 ± 27 min) and higher maximum nonesterified fatty acid (0.73 ± 0.05 vs. 0.60 ± 0.03 mmol/L) and glucose (7.92 ± 0.22 vs. 7.25 ± 0.22 mmol/L) concentrations after the SFA than the UNSAT meal, respectively (P ≤ 0.05). In the Svedberg flotation rate 60-400 TG-rich lipoprotein fraction, meal × genotype interactions were observed for incremental area under the curve (IAUC) for the TG (P = 0.038) and apoE (P = 0.016) responses with a 58% lower apoE IAUC after the UNSAT than the SFA meal (P = 0.017) in the E4 carriers. CONCLUSIONS:Our data indicate that APOE genotype had a modest impact on the postprandial response to meals of varying fat composition in normolipidemic men. The physiologic importance of greater apoE concentrations after the SFA-rich meals in APOE4 carriers may reflect an impact on TG-rich lipoprotein clearance from the circulation. This trial was registered at clinicaltrials.gov as NCT01522482.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Orange juice–derived flavanone and phenolic metabolites do not acutely affect cardiovascular risk biomarkers: a randomized, placebo-controlled, crossover trial in men at moderate risk of cardiovascular disease

Background: Epidemiological data suggest inverse associations between citrus flavanone intake and cardiovascular disease (CVD) risk. However, insufficient randomized controlled trial (RCT) data limit our understanding of mechanisms by which flavanones and their metabolites potentially reduce cardiovascular (CV) risk factors. Objective: We examined the effects of orange juice or a dose-matched hesperidin supplement on plasma concentrations of established and novel flavanone metabolites and their effects on CV risk biomarkers in men at moderate CVD risk. Methods: In an acute, randomized, placebo-controlled crossover trial, 16 fasted participants (aged 51-69 y) received orange juice or a hesperidin supplement (both providing 320 mg hesperidin) or control (all matched for sugar and vitamin C content). At baseline and 5 h post-intake, endothelial function (primary outcome), further CV risk biomarkers (i.e. blood pressure, arterial stiffness, cardiac autonomic function, platelet activation and NADPH oxidase gene expression) and plasma flavanone metabolites were assessed. Prior to each intervention, a diet low in flavonoids, nitrate/nitrite, alcohol and caffeine was followed and a standardized low-flavonoid evening meal was consumed. Results: Orange juice intake significantly elevated mean (± SEM) plasma concentrations of 8 flavanone (1.75 ± 0.35 µmol/L, P < 0.0001) and 15 phenolic metabolites (13.27 ± 2.22 µmol/L, P < 0.0001) compared with control at 5 h post-consumption. Despite increased plasma flavanone and phenolic metabolite concentrations, CV risk biomarkers were unaltered. Following hesperidin supplement intake, flavanone metabolites were not different to control, suggesting altered absorption/metabolism compared with the orange juice matrix. Conclusions: Following single-dose flavanone intake within orange juice, we detected circulating flavanone and phenolic metabolites collectively reaching a concentration of 15.20 ± 2.15 µmol/L but observed no effect on CV risk biomarkers. Longer-duration RCTs are required to further examine the previous associations between higher flavanone intakes and improved cardiovascular health and to ascertain the relative importance of food matrix and flavanone-derived phenolic metabolites.

Rapid preconditioning of data for accelerating convex hull algorithms

Given a dataset of two-dimensional points in the plane with integer coordinates, the method proposed reduces a set of n points down to a set of s points s ≤ n, such that the convex hull on the set of s points is the same as the convex hull of the original set of n points. The method is O(n). It helps any convex hull algorithm run faster. The empirical analysis of a practical case shows a percentage reduction in points of over 98%, that is reflected as a faster computation with a speedup factor of at least 4.

Distributed parallelization of greedy Mobile Network Optimization algorithms

The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.

Asynchronous distributed parallelization of mobile network optimization algorithms

It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.

Replacement of saturated with unsaturated fats had no impact on vascular function but beneficial effects on lipid biomarkers, E-selectin and blood pressure: results from the randomized, controlled Dietary Intervention and VAScular function (DIVAS) study

Background: Public health strategies to lower cardiovascular disease (CVD) risk involve reducing dietary saturated fatty acid (SFA) intake to ≤10% of total energy (%TE). However, the optimal type of replacement fat is unclear. Objective: We investigated the substitution of 9.5-9.6%TE dietary SFA with either monounsaturated (MUFA) or n-6 polyunsaturated fatty acids (PUFA) on vascular function and other CVD risk factors. Design: Using a randomized, controlled, single-blind, parallel group dietary intervention, 195 men and women aged 21-60 y with moderate CVD risk (≥50% above the population mean) from the United Kingdom followed one of three 16-wk isoenergetic diets (%TE target compositions, total fat:SFA:MUFA:n-6 PUFA): SFA-rich (36:17:11:4, n = 65), MUFA-rich (36:9:19:4, n = 64) or n-6 PUFA-rich (36:9:13:10, n = 66). The primary outcome measure was flow-mediated dilatation (%FMD); secondary outcome measures included fasting serum lipids, microvascular reactivity, arterial stiffness, ambulatory blood pressure, and markers of insulin resistance, inflammation and endothelial activation. Results: Replacing SFA with MUFA or n-6 PUFA did not significantly impact on %FMD (primary endpoint) or other measures of vascular reactivity. Of the secondary outcome measures, substitution of SFA with MUFA attenuated the increase in night systolic blood pressure (-4.9 mm Hg, P = 0.019) and reduced E-selectin (-7.8%, P = 0.012). Replacement with MUFA or n-6 PUFA lowered fasting serum total cholesterol (TC; -8.4% and -9.2%, respectively), low-density lipoprotein cholesterol (-11.3% and -13.6%) and TC to high-density lipoprotein cholesterol ratio (-5.6% and -8.5%) (P ≤ 0.001). These changes in low-density lipoprotein cholesterol equate to an estimated 17-20% reduction in CVD mortality. Conclusions: Substitution of 9.5-9.6%TE dietary SFA with either MUFA or n-6 PUFA did not impact significantly on %FMD or other measures of vascular function. However, the beneficial effects on serum lipid biomarkers, blood pressure and E-selectin offer a potential public health strategy for CVD risk reduction.

Impact of cocoa flavanol intake on age-dependent vascular stiffness in healthy men: a randomized, controlled, double-masked trial

Increased vascular stiffness, endothelial dysfunction, and isolated systolic hypertension are hallmarks of vascular aging. Regular cocoa flavanol (CF) intake can improve vascular function in healthy young and elderly at-risk individuals. However, the mechanisms underlying CF bioactivity remain largely unknown. We investigated the effects of CF intake on cardiovascular function in healthy young and elderly individuals without history, signs, or symptoms of cardiovascular disease by applying particular focus on functional endpoints relevant to cardiovascular aging. In a randomized, controlled, double-masked, parallel-group dietary intervention trial, 22 young (<35yrs) and 20 elderly (50-80yrs) healthy, male non- smokers consumed either a CF-containing drink (450mg CF) or nutrient-matched, CF-free control drink bi-daily for 14 days. The primary endpoint was endothelial function as measured by flow-mediated vasodilation (FMD). Secondary endpoints included cardiac output, vascular stiffness, conductance of conduit and resistance arteries, and perfusion in the microcirculation. Following 2 weeks of CF intake, FMD improved in young (6.1±0.7% vs. 7.6±0.7%, p<0.001) and elderly (4.9±0.6% vs. 6.3±0.9%, p<0.001). Secondary outcomes demonstrated in both groups that CF intake decreased pulse wave velocity and lowered total peripheral resistance, increased arteriolar- and microvascular vasodilator capacity, red cell deformability, and diastolic blood pressure, while cardiac output remained affected. In the elderly, baseline systolic blood pressure was elevated, driven by an arterial stiffness-related augmentation. CF intake decreased aortic augmentation index (-9%), and thus systolic blood pressure (-7mmHg). (Clinicaltrials.gov:NCT01639781) CF intake reverses age-related burden of cardiovascular risk in healthy elderly, highlighting the potential of dietary flavanols to maintain cardiovascular health.

Effects of a web-based personalized intervention on physical activity in European adults: a randomized controlled trial

Background: The high prevalence of physical inactivity worldwide calls for innovative and more effective ways to promote physical activity (PA). There are limited objective data on the effectiveness of Web-based personalized feedback on increasing PA in adults. Objective: It is hypothesized that providing personalized advice based on PA measured objectively alongside diet, phenotype, or genotype information would lead to larger and more sustained changes in PA, compared with nonpersonalized advice. Methods: A total of 1607 adults in seven European countries were randomized to either a control group (nonpersonalized advice, Level 0, L0) or to one of three personalized groups receiving personalized advice via the Internet based on current PA plus diet (Level 1, L1), PA plus diet and phenotype (Level 2, L2), or PA plus diet, phenotype, and genotype (Level 3, L3). PA was measured for 6 months using triaxial accelerometers, and self-reported using the Baecke questionnaire. Outcomes were objective and self-reported PA after 3 and 6 months. Results: While 1270 participants (85.81% of 1480 actual starters) completed the 6-month trial, 1233 (83.31%) self-reported PA at both baseline and month 6, but only 730 (49.32%) had sufficient objective PA data at both time points. For the total cohort after 6 months, a greater improvement in self-reported total PA (P=.02) and PA during leisure (nonsport) (P=.03) was observed in personalized groups compared with the control group. For individuals advised to increase PA, we also observed greater improvements in those two self-reported indices (P=.006 and P=.008, respectively) with increased personalization of the advice (L2 and L3 vs L1). However, there were no significant differences in accelerometer results between personalized and control groups, and no significant effect of adding phenotypic or genotypic information to the tailored feedback at month 3 or 6. After 6 months, there were small but significant improvements in the objectively measured physical activity level (P<.05), moderate PA (P<.01), and sedentary time (P<.001) for individuals advised to increase PA, but these changes were similar across all groups. Conclusions: Different levels of personalization produced similar small changes in objective PA. We found no evidence that personalized advice is more effective than conventional “one size fits all” guidelines to promote changes in PA in our Web-based intervention when PA was measured objectively. Based on self-reports, PA increased to a greater extent with more personalized advice. Thus, it is crucial to measure PA objectively in any PA intervention study.