Climate-Driven Range Shifts Within Benthic Habitats Across a Marine Biogeographic Transition Zone.

Anthropogenic climate change is causing unprecedented rapid responses in marine communities, with species across many different taxonomic groups showing faster shifts in biogeographic ranges than in any other ecosystem. Spatial and temporal trends for many marine species are difficult to quantify, however, due to the lack of long-term datasets across complete geographical distributions and the occurrence of small-scale variability from both natural and anthropogenic drivers. Understanding these changes requires a multidisciplinary approach to bring together patterns identified within long-term datasets and the processes driving those patterns using biologically relevant mechanistic information to accurately attribute cause and effect. This must include likely future biological responses, and detection of the underlying mechanisms in order to scale up from the organismal level to determine how communities and ecosystems are likely to respond across a range of future climate change scenarios. Using this multidisciplinary approach will improve the use of robust science to inform the development of fit-for-purpose policy to effectively manage marine environments in this rapidly changing world.

Equipping young people to engage with media driven science experiences: beyond science knowledge to science literacy and discerning consumers of news.

This paper reports on a study of a curricular intervention for pupils (age 10-13 years) in the UK aimed at supporting critical engagement with science based media reports. In particular the study focused on core elements of knowledge, skills and attitudes identified in previous studies that characterize critical consumers of science presented as news. This was an empirical study based on classroom observation. Data included responses from individual pupils, in addition video recording of group activity and intentional conversations between pupils and teachers were scrutinised. Analysis focused on core tasks relating to different elements of critical reading. Pupils demonstrated a grasp of questioning and evaluating text, however the capacity to translate this experience in support of a critical response to a media report with a science component is limited in assessing the credibility of text and as an element in critical reading.

Molecular characterization of immunoglobulin gene rearrangements in diffuse large B-cell lymphoma: antigen-driven origin and IGHV4-34 as a particular subgroup of the non-GCB subtype.

The pathogenesis of diffuse large B-cell lymphoma (DLBCL) remains partially unknown. The analysis of the B-cell receptor of the malignant cells could contribute to a better understanding of the DLBCL biology. We studied the molecular features of the immunoglobulin heavy chain (IGH) rearrangements in 165 patients diagnosed with DLBCL not otherwise specified. Clonal IGH rearrangements were amplified according to the BIOMED-2 protocol and PCR products were sequenced directly. We also analyzed the criteria for stereotyped patterns in all complete IGHV-IGHD-IGHJ (V-D-J) sequences. Complete V-D-J rearrangements were identified in 130 of 165 patients. Most cases (89%) were highly mutated, but 12 sequences were truly unmutated or minimally mutated. Three genes, IGHV4-34, IGHV3-23, and IGHV4-39, accounted for one third of the whole cohort, including an overrepresentation of IGHV4-34 (15.5% overall). Interestingly, all IGHV4-34 rearrangements and all unmutated sequences belonged to the nongerminal center B-cell-like (non-GCB) subtype. Overall, we found three cases following the current criteria for stereotyped heavy chain VH CDR3 sequences, two of them belonging to subsets previously described in CLL. IGHV gene repertoire is remarkably biased, implying an antigen-driven origin in DLBCL. The particular features in the sequence of the immunoglobulins suggest the existence of particular subgroups within the non-GCB subtype.

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

Model-driven development of sensor network applications with optimization of non-functional constraints

Wireless sensor networks (WSNs) differ from conventional distributed systems in many aspects. The resource limitation of sensor nodes, the ad-hoc communication and topology of the network, coupled with an unpredictable deployment environment are difficult non-functional constraints that must be carefully taken into account when developing software systems for a WSN. Thus, more research needs to be done on designing, implementing and maintaining software for WSNs. This thesis aims to contribute to research being done in this area by presenting an approach to WSN application development that will improve the reusability, flexibility, and maintainability of the software. Firstly, we present a programming model and software architecture aimed at describing WSN applications, independently of the underlying operating system and hardware. The proposed architecture is described and realized using the Model-Driven Architecture (MDA) standard in order to achieve satisfactory levels of encapsulation and abstraction when programming sensor nodes. Besides, we study different non-functional constrains of WSN application and propose two approaches to optimize the application to satisfy these constrains. A real prototype framework was built to demonstrate the developed solutions in the thesis. The framework implemented the programming model and the multi-layered software architecture as components. A graphical interface, code generation components and supporting tools were also included to help developers design, implement, optimize, and test the WSN software. Finally, we evaluate and critically assess the proposed concepts. Two case studies are provided to support the evaluation. The first case study, a framework evaluation, is designed to assess the ease at which novice and intermediate users can develop correct and power efficient WSN applications, the portability level achieved by developing applications at a high-level of abstraction, and the estimated overhead due to usage of the framework in terms of the footprint and executable code size of the application. In the second case study, we discuss the design, implementation and optimization of a real-world application named TempSense, where a sensor network is used to monitor the temperature within an area.

From data to applications in the Internet of Things

Con la crescita in complessità delle infrastrutture IT e la pervasività degli scenari di Internet of Things (IoT) emerge il bisogno di nuovi modelli computazionali basati su entità autonome capaci di portare a termine obiettivi di alto livello interagendo tra loro grazie al supporto di infrastrutture come il Fog Computing, per la vicinanza alle sorgenti dei dati, e del Cloud Computing per offrire servizi analitici complessi di back-end in grado di fornire risultati per milioni di utenti. Questi nuovi scenarii portano a ripensare il modo in cui il software viene progettato e sviluppato in una prospettiva agile. Le attività dei team di sviluppatori (Dev) dovrebbero essere strettamente legate alle attività dei team che supportano il Cloud (Ops) secondo nuove metodologie oggi note come DevOps. Tuttavia, data la mancanza di astrazioni adeguata a livello di linguaggio di programmazione, gli sviluppatori IoT sono spesso indotti a seguire approcci di sviluppo bottom-up che spesso risulta non adeguato ad affrontare la compessità delle applicazione del settore e l'eterogeneità dei compomenti software che le formano. Poichè le applicazioni monolitiche del passato appaiono difficilmente scalabili e gestibili in un ambiente Cloud con molteplici utenti, molti ritengono necessaria l'adozione di un nuovo stile architetturale, in cui un'applicazione dovrebbe essere vista come una composizione di micro-servizi, ciascuno dedicato a uno specifica funzionalità applicativa e ciascuno sotto la responsabilità di un piccolo team di sviluppatori, dall'analisi del problema al deployment e al management. Poichè al momento non si è ancora giunti a una definizione univoca e condivisa dei microservices e di altri concetti che emergono da IoT e dal Cloud, nè tantomento alla definzione di linguaggi sepcializzati per questo settore, la definzione di metamodelli custom associati alla produzione automatica del software di raccordo con le infrastrutture potrebbe aiutare un team di sviluppo ad elevare il livello di astrazione, incapsulando in una software factory aziendale i dettagli implementativi. Grazie a sistemi di produzione del sofware basati sul Model Driven Software Development (MDSD), l'approccio top-down attualmente carente può essere recuperato, permettendo di focalizzare l'attenzione sulla business logic delle applicazioni. Nella tesi viene mostrato un esempio di questo possibile approccio, partendo dall'idea che un'applicazione IoT sia in primo luogo un sistema software distribuito in cui l'interazione tra componenti attivi (modellati come attori) gioca un ruolo fondamentale.

Rational Function Interpolation of Electromagnetic Transfer Functions of High-Speed Interconnect Systems from Discrete Time-Domain and Frequency-Domain Data

We present new methodologies to generate rational function approximations of broadband electromagnetic responses of linear and passive networks of high-speed interconnects, and to construct SPICE-compatible, equivalent circuit representations of the generated rational functions. These new methodologies are driven by the desire to improve the computational efficiency of the rational function fitting process, and to ensure enhanced accuracy of the generated rational function interpolation and its equivalent circuit representation. Toward this goal, we propose two new methodologies for rational function approximation of high-speed interconnect network responses. The first one relies on the use of both time-domain and frequency-domain data, obtained either through measurement or numerical simulation, to generate a rational function representation that extrapolates the input, early-time transient response data to late-time response while at the same time providing a means to both interpolate and extrapolate the used frequency-domain data. The aforementioned hybrid methodology can be considered as a generalization of the frequency-domain rational function fitting utilizing frequency-domain response data only, and the time-domain rational function fitting utilizing transient response data only. In this context, a guideline is proposed for estimating the order of the rational function approximation from transient data. The availability of such an estimate expedites the time-domain rational function fitting process. The second approach relies on the extraction of the delay associated with causal electromagnetic responses of interconnect systems to provide for a more stable rational function process utilizing a lower-order rational function interpolation. A distinctive feature of the proposed methodology is its utilization of scattering parameters. For both methodologies, the approach of fitting the electromagnetic network matrix one element at a time is applied. It is shown that, with regard to the computational cost of the rational function fitting process, such an element-by-element rational function fitting is more advantageous than full matrix fitting for systems with a large number of ports. Despite the disadvantage that different sets of poles are used in the rational function of different elements in the network matrix, such an approach provides for improved accuracy in the fitting of network matrices of systems characterized by both strongly coupled and weakly coupled ports. Finally, in order to provide a means for enforcing passivity in the adopted element-by-element rational function fitting approach, the methodology for passivity enforcement via quadratic programming is modified appropriately for this purpose and demonstrated in the context of element-by-element rational function fitting of the admittance matrix of an electromagnetic multiport.

Biofuels and high value added products from the yeast Rhodosporidium toruloides NCYC 921: Strategies towards a true cost-effective and environmentally sustainable integrated multiproduct driven biorefinery [Poster]

Single-cell oils (SCO) have been considered a promising source of 3rd generation biofuels mainly in the final form of biodiesel. However, its high production costs have been a barrier towards the commercialization of this commodity. The fast growing yeast Rhodosporidium toruloides NCYC 921 has been widely reported as a potential SCO producing yeast. In addition to its well-known high lipid content (that can be converted into biodiesel), is rich in high value added products such as carotenoids with commercial interest. The process design and integration may contribute to reduce the overall cost of biofuels and carotenoid production and is a mandatory step towards their commercialization. The present work addresses the biomass disruption, extraction, fractionation and recovery of products with special emphasis on high added valued carotenoids (beta-carotene, torulene, torularhodin) and fatty acids directed to biodiesel. The chemical structure of torularhodin with a terminal carboxylic group imposes an additional extra challenge in what concern its separation from fatty acids. The proposed feedstock is fresh biomass pellet obtained directly by centrifugation from a 5L fed-batch fermentation culture broth. The use of a wet instead of lyophilised biomass feedstock is a way to decrease processing energy costs and reduce downstream processing time. These results will contribute for a detailed process design. Gathered data will be of crucial importance for a further study on Life-Cycle Assessment (LCA).

Consequences of big data on the individual: Interview

The speed with which data has moved from being scarce, expensive and valuable, thus justifying detailed and careful verification and analysis to a situation where the streams of detailed data are almost too large to handle has caused a series of shifts to occur. Legal systems already have severe problems keeping up with, or even in touch with, the rate at which unexpected outcomes flow from information technology. The capacity to harness massive quantities of existing data has driven Big Data applications until recently. Now the data flows in real time are rising swiftly, become more invasive and offer monitoring potential that is eagerly sought by commerce and government alike. The ambiguities as to who own this often quite remarkably intrusive personal data need to be resolved – and rapidly - but are likely to encounter rising resistance from industrial and commercial bodies who see this data flow as ‘theirs’. There have been many changes in ICT that has led to stresses in the resolution of the conflicts between IP exploiters and their customers, but this one is of a different scale due to the wide potential for individual customisation of pricing, identification and the rising commercial value of integrated streams of diverse personal data. A new reconciliation between the parties involved is needed. New business models, and a shift in the current confusions over who owns what data into alignments that are in better accord with the community expectations. After all they are the customers, and the emergence of information monopolies needs to be balanced by appropriate consumer/subject rights. This will be a difficult discussion, but one that is needed to realise the great benefits to all that are clearly available if these issues can be positively resolved. The customers need to make these data flow contestable in some form. These Big data flows are only going to grow and become ever more instructive. A better balance is necessary, For the first time these changes are directly affecting governance of democracies, as the very effective micro targeting tools deployed in recent elections have shown. Yet the data gathered is not available to the subjects. This is not a survivable social model. The Private Data Commons needs our help. Businesses and governments exploit big data without regard for issues of legality, data quality, disparate data meanings, and process quality. This often results in poor decisions, with individuals bearing the greatest risk. The threats harbored by big data extend far beyond the individual, however, and call for new legal structures, business processes, and concepts such as a Private Data Commons. This Web extra is the audio part of a video in which author Marcus Wigan expands on his article "Big Data's Big Unintended Consequences" and discusses how businesses and governments exploit big data without regard for issues of legality, data quality, disparate data meanings, and process quality. This often results in poor decisions, with individuals bearing the greatest risk. The threats harbored by big data extend far beyond the individual, however, and call for new legal structures, business processes, and concepts such as a Private Data Commons.

FLOW REGIME DRIVEN THERMAL ENHANCEMENT IN INTERNALLY-GROOVED TUBES

Internally-grooved refrigeration tubes maximize tube-side evaporative heat transfer rates and have been identified as a most promising technology for integration into compact cold plates. Unfortunately, the absence of phenomenological insights and physical models hinders the extrapolation of grooved-tube performance to new applications. The success of regime-based heat transfer correlations for smooth tubes has motivated the current effort to explore the relationship between flow regimes and enhanced heat transfer in internally-grooved tubes. In this thesis, a detailed analysis of smooth and internally-grooved tube data reveals that performance improvement in internally-grooved tubes at low-to-intermediate mass flux is a result of early flow regime transition. Based on this analysis, a new flow regime map and corresponding heat transfer coefficient correlation, which account for the increased wetted angle, turbulence, and Gregorig effects unique to internally-grooved tubes, were developed. A two-phase test facility was designed and fabricated to validate the newly-developed flow regime map and regime-based heat transfer coefficient correlation. As part of this setup, a non-intrusive optical technique was developed to study the dynamic nature of two-phase flows. It was found that different flow regimes result in unique temporally varying film thickness profiles. Using these profiles, quantitative flow regime identification measures were developed, including the ability to explain and quantify the more subtle transitions that exist between dominant flow regimes. Flow regime data, based on the newly-developed method, and heat transfer coefficient data, using infrared thermography, were collected for two-phase HFE-7100 flow in horizontal 2.62mm - 8.84mm diameter smooth and internally-grooved tubes with mass fluxes from 25-300 kg/m²s, heat fluxes from 4-56 kW/m², and vapor qualities approaching 1. In total, over 6500 combined data points for the adiabatic and diabatic smooth and internally-grooved tubes were acquired. Based on results from the experiments and a reinterpretation of data from independent researchers, it was established that heat transfer enhancement in internally-grooved tubes at low-to-intermediate mass flux is primarily due to early flow regime transition to Annular flow. The regime-based heat transfer coefficient outperformed empirical correlations from the literature, with mean and absolute deviations of 4.0% and 32% for the full range of data collected.

Global change and climate-driven invasion of the Pacific oyster (Crassostrea gigas) along European coasts: a bioenergetics modelling approach

Aim The spread of non-indigenous species in marine ecosystems world-wide is one of today's most serious environmental concerns. Using mechanistic modelling, we investigated how global change relates to the invasion of European coasts by a non-native marine invertebrate, the Pacific oyster Crassostrea gigas. Location Bourgneuf Bay on the French Atlantic coast was considered as the northern boundary of C. gigas expansion at the time of its introduction to Europe in the 1970s. From this latitudinal reference, variations in the spatial distribution of the C. gigas reproductive niche were analysed along the north-western European coast from Gibraltar to Norway. Methods The effects of environmental variations on C. gigas physiology and phenology were studied using a bioenergetics model based on Dynamic Energy Budget theory. The model was forced with environmental time series including in situ phytoplankton data, and satellite data of sea surface temperature and suspended particulate matter concentration. Results Simulation outputs were successfully validated against in situ oyster growth data. In Bourgneuf Bay, the rise in seawater temperature and phytoplankton concentration has increased C. gigas reproductive effort and led to precocious spawning periods since the 1960s. At the European scale, seawater temperature increase caused a drastic northward shift (1400 km within 30 years) in the C. gigas reproductive niche and optimal thermal conditions for early life stage development. Main conclusions We demonstrated that the poleward expansion of the invasive species C. gigas is related to global warming and increase in phytoplankton abundance. The combination of mechanistic bioenergetics modelling with in situ and satellite environmental data is a valuable framework for ecosystem studies. It offers a generic approach to analyse historical geographical shifts and to predict the biogeographical changes expected to occur in a climate-changing world.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

Exploring coordination-driven self-assembly with autonomous chemical robots

The work presented herein focused on the automation of coordination-driven self assembly, exploring methods that allow syntheses to be followed more closely while forming new ligands, as part of the fundamental study of the digitization of chemical synthesis and discovery. Whilst the control and understanding of the principle of pre-organization and self-sorting under non-equilibrium conditions remains a key goal, a clear gap has been identified in the absence of approaches that can permit fast screening and real-time observation of the reaction process under different conditions. A firm emphasis was thus placed on the realization of an autonomous chemical robot, which can not only monitor and manipulate coordination chemistry in real-time, but can also allow the exploration of a large chemical parameter space defined by the ligand building blocks and the metal to coordinate. The self-assembly of imine ligands with copper and nickel cations has been studied in a multi-step approach using a self-built flow system capable of automatically controlling the liquid-handling and collecting data in real-time using a benchtop MS and NMR spectrometer. This study led to the identification of a transient Cu(I) species in situ which allows for the formation of dimeric and trimeric carbonato bridged Cu(II) assemblies. Furthermore, new Ni(II) complexes and more remarkably also a new binuclear Cu(I) complex, which usually requires long and laborious inert conditions, could be isolated. The study was then expanded to the autonomous optimization of the ligand synthesis by enabling feedback control on the chemical system via benchtop NMR. The synthesis of new polydentate ligands has emerged as a result of the study aiming to enhance the complexity of the chemical system to accelerate the discovery of new complexes. This type of ligand consists of 1-pyridinyl-4-imino-1,2,3-triazole units, which can coordinate with different metal salts. The studies to test for the CuAAC synthesis via microwave lead to the discovery of four new Cu complexes, one of them being a coordination polymer obtained from a solvent dependent crystallization technique. With the goal of easier integration into an automated system, copper tubing has been exploited as the chemical reactor for the synthesis of this ligand, as it efficiently enhances the rate of the triazole formation and consequently promotes the formation of the full ligand in high yields within two hours. Lastly, the digitization of coordination-driven self-assembly has been realized for the first time using an in-house autonomous chemical robot, herein named the ‘Finder’. The chemical parameter space to explore was defined by the selection of six variables, which consist of the ligand precursors necessary to form complex ligands (aldehydes, alkineamines and azides), of the metal salt solutions and of other reaction parameters – duration, temperature and reagent volumes. The platform was assembled using rounded bottom flasks, flow syringe pumps, copper tubing, as an active reactor, and in-line analytics – a pH meter probe, a UV-vis flow cell and a benchtop MS. The control over the system was then obtained with an algorithm capable of autonomously focusing the experiments on the most reactive region (by avoiding areas of low interest) of the chemical parameter space to explore. This study led to interesting observations, such as metal exchange phenomena, and also to the autonomous discovery of self assembled structures in solution and solid state – such as 1-pyridinyl-4-imino-1,2,3-triazole based Fe complexes and two helicates based on the same ligand coordination motif.