A normative approach to multi-agent systems for intelligent buildings

Building Management Systems (BMS) are widely adopted in modern buildings around the world in order to provide high-quality building services, and reduce the running cost of the building. However, most BMS are functionality-oriented and do not consider user personalization. The aim of this research is to capture and represent building management rules using organizational semiotics methods. We implement Semantic Analysis, which determines semantic units in building management and their relationship patterns of behaviour, and Norm Analysis, which extracts and specifies the norms that establish how and when these management actions occur. Finally, we propose a multi-agent framework for norm based building management. This framework contributes to the design domain of intelligent building management system by defining a set of behaviour patterns, and the norms that govern the real-time behaviour in a building.

Separation of oligosaccharides from caprine milk whey, prior to prebiotic evaluation

Milk oligosaccharides are believed to have beneficial biological properties. Caprine milk has a relatively high concentration of oligosaccharides in comparison to other ruminant milks and has the closest oligosaccharide profile to human milk. The first stage in recovering oligosaccharides from caprine milk whey, a by-product of cheese making, was accomplished by ultrafiltration to remove proteins and fat globules, leaving more than 97% of the initial carbohydrates, mainly lactose, in the permeate. The ultrafiltered permeate was further processed using a 1 kDa ‘tight’ ultrafiltration membrane, which retained less than 7% of the remaining lactose. The final retentate was fractionated by preparative scale molecular size exclusion chromatography, to yield 28 fractions, of which oligosaccharide-rich fractions were detected somewhere between fractions 9/10 to 16/17, suitable for functionality and gut health promotion testing. All fractions were evaluated for their oligosaccharide and carbohydrate profiles using three complementary analytical methods.

Automated organizational network analysis for enterprise 2.0

Social Networking Sites have recently become a mainstream communications technology for many people around the world. Major IT vendors are releasing social software designed for use in a business/commercial context. These Enterprise 2.0 technologies have impressive collaboration and information sharing functionality, but so far they do not have any organizational network analysis (ONA) features that reveal any patterns of connectivity within business units. This paper shows the impact of organizational network analysis techniques and social networks on organizational performance, we also give an overview on current enterprise social software, and most importantly, we highlight how Enterprise 2.0 can help automate an organizational network analysis.

Performance of palm- based fat blends with a low saturated fat content in puff pastry

Four fat blends based on palm fractions in combination with high oleic sunflower oil (HOSF) with a relatively low saturated fatty acid content (29.2±0.85%, i.e. less than 50% of that of butter) were prepared. The saturated fat was located in different triacylglycerols (TAG) structures in each blend. Principal saturated TAG were derived from palm stearin (POs, containing tripalmitoyl glycerol - PPP), palm mid fraction (PMF, containing 1,3-dipalmitoyl-2-oleoyl glycerol - POP) and interesterified PMF (inPMF, containing PPP, POP and rac-1,2-dipalmitoyl-3-oleoyl glycerol - PPO). Thus, in blend 1, composed of POs and HOSF, the saturates resided principally in PPP. In blend 2, composed of POs, PMF and HOSF, the principal saturate-containing TAG were PPP and POP. Blend 3, composed of inPMF and HOSF, was similar to blend 2 except that the disaturated TAG comprised a 2:1 mixture of PPO:POP. Finally, blend 4, a mixture of PMF and HOSF, had saturates present mainly as POP. The physical properties and the functionality of blends, as shortenings for puff pastry laminated in a warm bakery environment (20-30°C), were compared with each other, and with butter. Puff pastry prepared with blend 1 (POs:HOSF 29:71) and blend 4 (PMF:HOSF 41:59), was very hard; blend 2 (POs:PMF:HOSF 13:19:68) was most similar to butter in the compressibility of the baked product and it performed well in an independent baking trial; blend 3 (inPMF:HOSF 40:60) gave a product that required a higher force for compression than butter.

Effect of dairy-based protein sources and temperature on growth, acidification and exopolysaccharide production of Bifidobacterium strains in skim milk

The aim of the present study was to find out the best growing conditions for exopolysaccharide (EPS) producing bifidobacteria, which improve their functionality in yoghurt-like products. Two Bifidobacterium strains were used in this study, Bifidobacterium longum subsp. infantis CCUG 52486 and Bifidobacterium infantis NCIMB 702205. In the first part of the study the effect of casein hydrolysate, lactalbumin hydrolysate, whey protein concentrate and whey protein isolate, added at 1.5% w/v in skim milk, was evaluated in terms of cell growth and EPS production; skim milk supplemented with yeast extract served as the control. Among the various nitrogen sources, casein hydrolysate (CH) showed the highest cell growth and EPS production for both strains after 18 h incubation and therefore it was selected for subsequent work. Based on fermentation experiments using different levels of CH (from 0.5 to 2.5% w/v) it was deduced that 1.5% (w/v) CH resulted in the highest EPS production, yielding 102 and 285 mg L− 1 for B. infantis NCIMB 702205 and B. longum subsp. infantis CCUG 52486, respectively. The influence of temperature on growth and EPS production of both strains was further evaluated at 25, 30, 37 and 42 °C for up to 48 h in milk supplemented with 1.5% (w/v) CH. The temperature had a significant effect on growth, acidification and EPS production. The maximum growth and EPS production were recorded at 37 °C for both strains, whereas no EPS production was observed at 25 °C. Lower EPS production for both strains were observed at 42 °C, which is the common temperature used in yoghurt manufacturing compared to that at 37 °C. The results showed that the culture conditions have a clear effect on the growth, acidification and EPS production, and more specifically, that skim milk supplemented with 1.5% (w/v) CH could be used as a substrate for the growth of EPS-producing bifidobacteria, at 37 °C for 24 h, resulting in the production of a low fat yoghurt-like product with improved functionality.

A tutorial on pseudospectral methods for computational optimal control

[English] This paper is a tutorial introduction to pseudospectral optimal control. With pseudospectral methods, a function is approximated as a linear combination of smooth basis functions, which are often chosen to be Legendre or Chebyshev polynomials. Collocation of the differential-algebraic equations is performed at orthogonal collocation points, which are selected to yield interpolation of high accuracy. Pseudospectral methods directly discretize the original optimal control problem to recast it into a nonlinear programming format. A numerical optimizer is then employed to find approximate local optimal solutions. The paper also briefly describes the functionality and implementation of PSOPT, an open source software package written in C++ that employs pseudospectral discretization methods to solve multi-phase optimal control problems. The software implements the Legendre and Chebyshev pseudospectral methods, and it has useful features such as automatic differentiation, sparsity detection, and automatic scaling. The use of pseudospectral methods is illustrated in two problems taken from the literature on computational optimal control. [Portuguese] Este artigo e um tutorial introdutorio sobre controle otimo pseudo-espectral. Em metodos pseudo-espectrais, uma funcao e aproximada como uma combinacao linear de funcoes de base suaves, tipicamente escolhidas como polinomios de Legendre ou Chebyshev. A colocacao de equacoes algebrico-diferenciais e realizada em pontos de colocacao ortogonal, que sao selecionados de modo a minimizar o erro de interpolacao. Metodos pseudoespectrais discretizam o problema de controle otimo original de modo a converte-lo em um problema de programa cao nao-linear. Um otimizador numerico e entao empregado para obter solucoes localmente otimas. Este artigo tambem descreve sucintamente a funcionalidade e a implementacao de um pacote computacional de codigo aberto escrito em C++ chamado PSOPT. Tal pacote emprega metodos de discretizacao pseudo-spectrais para resolver problemas de controle otimo com multiplas fase. O PSOPT permite a utilizacao de metodos de Legendre ou Chebyshev, e possui caractersticas uteis tais como diferenciacao automatica, deteccao de esparsidade e escalonamento automatico. O uso de metodos pseudo-espectrais e ilustrado em dois problemas retirados da literatura de controle otimo computacional.

Towards the total synthesis of mycaperoxide B: probing biosynthetic rationale

Studies towards the biomimetic synthesis of mycaperoxide B (1) are described. We have established the synthesis of four diastereoisomers of mycaperoxide B methyl ester (1a) by employing a Michael addition across an α,β-unsaturated ester precursor 2 as the key step. This result strongly suggestsstereocontrol in the addition of the hydroperoxide functionality to the E double bond and discloses the importance of choosing the correct geometry of the α,β-unsaturated double bond when attempting to synthesise mycaperoxide B. Four diastereoisomeric tetrahydrofurans derived from an intramolecular rearrangement of the 1,2-dioxolane enolate 12 were also isolated and characterised.

Enhancing the catalytic repertoire of nucleic acids: a systematic study of linker length and rigidity

The incorporation of potentially catalytic groups in DNA is of interest for the in vitro selection of novel deoxyribozymes, A series of 10 C5-modified analogues of 2'-deoxyuridine triphosphate have been synthesised that possess side chains of differing flexibility and bearing a primary amino or imidazole functionality, For each series of nucleotide analogues differing degrees of flexibility of the C5 side chain was achieved through the use of alkynyl, alkenyl and alkyl moieties, The imidazole function was conjugated to these CS-amino-modified nucleotides using either imidazole 4-acetic acid or imidazole 4-acrylic acid (urocanic acid), The substrate properties of the nucleotides (fully replacing dTTP) with Taq polymerase during PCR have been investigated in order to evaluate their potential applications for in vitro selection experiments, 5-(3-Aminopropynyl)dUTP and 5-(E-3-aminopropenyl)dUTP and their imidazole 4-acetic acid- and urocanic acid-modified conjugates were found to be substrates, In contrast, C5-amino-modified dUTPs with alkane or Z-alkene linkers and their corresponding conjugates were not substrates, The incorporation of these analogues during PCR has been confirmed by inhibition of restriction enzyme digestion using XbaI and by mass spectrometry of the PCR products.

An Earth Observation Land Data Assimilation System (EO-LDAS)

Current methods for estimating vegetation parameters are generally sub-optimal in the way they exploit information and do not generally consider uncertainties. We look forward to a future where operational dataassimilation schemes improve estimates by tracking land surface processes and exploiting multiple types of observations. Dataassimilation schemes seek to combine observations and models in a statistically optimal way taking into account uncertainty in both, but have not yet been much exploited in this area. The EO-LDAS scheme and prototype, developed under ESA funding, is designed to exploit the anticipated wealth of data that will be available under GMES missions, such as the Sentinel family of satellites, to provide improved mapping of land surface biophysical parameters. This paper describes the EO-LDAS implementation, and explores some of its core functionality. EO-LDAS is a weak constraint variational dataassimilationsystem. The prototype provides a mechanism for constraint based on a prior estimate of the state vector, a linear dynamic model, and EarthObservationdata (top-of-canopy reflectance here). The observation operator is a non-linear optical radiative transfer model for a vegetation canopy with a soil lower boundary, operating over the range 400 to 2500 nm. Adjoint codes for all model and operator components are provided in the prototype by automatic differentiation of the computer codes. In this paper, EO-LDAS is applied to the problem of daily estimation of six of the parameters controlling the radiative transfer operator over the course of a year (> 2000 state vector elements). Zero and first order process model constraints are implemented and explored as the dynamic model. The assimilation estimates all state vector elements simultaneously. This is performed in the context of a typical Sentinel-2 MSI operating scenario, using synthetic MSI observations simulated with the observation operator, with uncertainties typical of those achieved by optical sensors supposed for the data. The experiments consider a baseline state vector estimation case where dynamic constraints are applied, and assess the impact of dynamic constraints on the a posteriori uncertainties. The results demonstrate that reductions in uncertainty by a factor of up to two might be obtained by applying the sorts of dynamic constraints used here. The hyperparameter (dynamic model uncertainty) required to control the assimilation are estimated by a cross-validation exercise. The result of the assimilation is seen to be robust to missing observations with quite large data gaps.

The potential for community groups to promote sustainable living

In recent times there has been a growing recognition amongst policy-makers of the role for community-based action in contributing to the broader aims of energy policy and climate change. In this paper, we will examine the potential for existing community groups to use their influence and elements of internal cohesion to encourage more widespread understanding and adoption of sustainable lifestyle habits; both amongst their members and within the broader communities of which they are a part. Findings are presented from recent empirical work with a range of well-established community groups for whom environmental issues are not their main priority. A central aspect of the research was to explore both the current status and potential role of groups that may have the capacity to reach and influence a broader sphere of the public than energy/environment specific initiatives of recent times have been able to achieve. Representing a diversity of interests, age groups and functionality, the results suggest that the potential for more effective ‘bottom-up’ engagement on climate change and sustainable living might be given fresh impetus by these types of established community groups and their networks. An assessment of what motivates participation and membership in the groups highlights a series of factors common to all groups and a smaller number that are significant for particular groups individually. It is argued that an appreciation of motivating factors can be useful in understanding more clearly how such groups are able to survive and maintain cohesion over time. The findings also suggest that climate change action means different things for different groups, with the diversity of the groups bringing with it the challenge of making sustainable living relevant to a range of interests and different shared values.

Environmental oestrogens and breast cancer: long-term low-dose effects of mixtures of various chemical combinations

The incidence of breast cancer has risen worldwide to unprecedented levels in recent decades, making it now the major cancer of women in many parts of the world.1 Although diet, alcohol, radiation and inherited loss of BRCA1/2 genes have all been associated with increased incidence, the main identified risk factors are life exposure to hormones including physiological variations associated with puberty/pregnancy/menopause,1 personal choice of use of hormonal contraceptives2 and/or hormone replacement therapy.3–6 On this basis, exposure of the human breast to the many environmental pollutant chemicals capable of mimicking or interfering with oestrogen action7 should also be of concern.8 Hundreds of such environmental chemicals have now been measured in human breast tissue from a range of dietary and domestic exposure sources7 ,9 including persistent organochlorine pollutants (POPs),10 polybrominated diphenylethers and polybromobiphenyls,11 polychlorinated biphenyls,12 dioxins,13 alkyl phenols,14 bisphenol-A and chlorinated derivatives,15 as well as other less lipophilic compounds such as parabens (alkyl esters of p-hydroxybenzoic acid),16 but studies investigating any association between raised levels of such compounds and the development of breast cancer remain inconclusive.7–16 However, the functionality of these chemicals has continued to be assessed on the basis of individual chemicals rather than the environmental reality of long-term low-dose exposure to complex mixtures. This misses the potential for individuals to have high concentrations of different compounds but with a common mechanism of action. It also misses the complex interactions between chemicals and physiological hormones which together may act to alter the internal homeostasis of the oestrogenic environment of mammary tissue.

ATD: a multiplatform for semiautomatic 3-D detection of kidneys and their pathology in real time

This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging.

Use of synthetic CaV2.2 Ca2+ channel peptides to study presynaptic function

Small, synthetic peptides based on specific regions of voltage-gated Ca2+ channels (VGCCs) have been widely used to study Ca2+ channel function and have been instrumental in confirming the contribution of specific amino acid sequences to interactions with putative binding partners. In particular, peptides based on the Ca2+ channel Alpha Interaction Domain (AID) on the intracellular region connecting domains I and II (the I-II loop) and the SYNaptic PRotein INTerction (synprint) site on the II-III loop have been widely used. Emerging evidence suggests that such peptides may themselves possess inherent functionality, a property that may be exploitable for future drug design. Here, we review our recent work using synthetic Ca2+ channel peptides based on sequences within the CaV2.2 amino terminal and I-II loop, originally identified as molecular determinates for G protein modulation, and their effects on VGCC function. These CaV2.2 peptides act as inhibitory modules to decrease Ca2+ influx with direct effects on VGCC gating, ultimately leading to a reduction of synaptic transmission. CaV2.2 peptides also attenuate G protein modulation of VGCCs. Amino acid substitutions generate CaV2.2 peptides with increased or decreased inhibitory effects suggesting that synthetic peptides can be used to further probe VGCC function and, potentially, form the basis for novel therapeutic development.

Estimation of wind storm impacts over Western Germany under future climate conditions using a statistical-dynamical downscaling approach

A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses. Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.

Assessment of the Wind Gust Estimate Method in mesoscale modelling of storm events over West Germany

A physically based gust parameterisation is added to the atmospheric mesoscale model FOOT3DK to estimate wind gusts associated with storms over West Germany. The gust parameterisation follows the Wind Gust Estimate (WGE) method and its functionality is verified in this study. The method assumes that gusts occurring at the surface are induced by turbulent eddies in the planetary boundary layer, deflecting air parcels from higher levels down to the surface under suitable conditions. Model simulations are performed with horizontal resolutions of 20 km and 5 km. Ten historical storm events of different characteristics and intensities are chosen in order to include a wide range of typical storms affecting Central Europe. All simulated storms occurred between 1990 and 1998. The accuracy of the method is assessed objectively by validating the simulated wind gusts against data from 16 synoptic stations by means of “quality parameters”. Concerning these parameters, the temporal and spatial evolution of the simulated gusts is well reproduced. Simulated values for low altitude stations agree particularly well with the measured gusts. For orographically exposed locations, the gust speeds are partly underestimated. The absolute maximum gusts lie in most cases within the bounding interval given by the WGE method. Focussing on individual storms, the performance of the method is better for intense and large storms than for weaker ones. Particularly for weaker storms, the gusts are typically overestimated. The results for the sample of ten storms document that the method is generally applicable with the mesoscale model FOOT3DK for mid-latitude winter storms, even in areas with complex orography.