Real-time multi-model decadal climate predictions

We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.

Multi-year droughts in Europe: analysis of development and causes

Whilst hydrological systems can show resilience to short-term streamflow deficiencies during within-year droughts, prolonged deficits during multi-year droughts are a significant threat to water resources security in Europe. This study uses a threshold-based objective classification of regional hydrological drought to qualitatively examine the characteristics, spatio-temporal evolution and synoptic climatic drivers of multi-year drought events in 1962–64, 1975–76 and 1995–97, on a European scale but with particular focus on the UK. Whilst all three events are multi-year, pan-European phenomena, their development and causes can be contrasted. The critical factor in explaining the unprecedented severity of the 1975–76 event is the consecutive occurrence of winter and summer drought. In contrast, 1962–64 was a succession of dry winters, mitigated by quiescent summers, whilst 1995–97 lacked spatial coherence and was interrupted by wet interludes. Synoptic climatic conditions vary within and between multi-year droughts, suggesting that regional factors modulate the climate signal in streamflow drought occurrence. Despite being underpinned by qualitatively similar climatic conditions and commonalities in evolution and characteristics, each of the three droughts has a unique spatio-temporal signature. An improved understanding of the spatio-temporal evolution and characteristics of multi-year droughts has much to contribute to monitoring and forecasting capability, and to improved mitigation strategies.

Janus PEG-based dendrimers for use in combination therapy: controlled multi-drug loading and sequential release

The increasing use of drug combinations to treat disease states, such as cancer, calls for improved delivery systems that are able to deliver multiple agents. Herein, we report a series of novel Janus dendrimers with potential for use in combination therapy. Different generations (first and second) of PEG-based dendrons containing two different “model drugs”, benzyl alcohol (BA) and 3-phenylpropionic acid (PPA), were synthesized. BA and PPA were attached via two different linkers (carbonate and ester, respectively) to promote differential drug release. The four dendrons were coupled together via (3 + 2) cycloaddition chemistries to afford four Janus dendrimers, which contained varying amounts and different ratios of BA and PPA, namely, (BA)2-G1-G1-(PPA)2, (BA)4-G2-G1-(PPA)2, (BA)2-G1-G2-(PPA)4, and (BA)4-G2-G2-(PPA)4. Release studies in plasma showed that the dendrimers provided sequential release of the two model drugs, with BA being released faster than PPA from all of the dendrons. The different dendrimers allowed delivery of increasing amounts (0.15–0.30 mM) and in exact molecular ratios (1:2; 2:1; 1:2; 2:2) of the two model drug compounds. The dendrimers were noncytotoxic (100% viability at 1 mg/mL) toward human umbilical vein endothelial cells (HUVEC) and nontoxic toward red blood cells, as confirmed by hemolysis studies. These studies demonstrate that these Janus PEG-based dendrimers offer great potential for the delivery of drugs via combination therapy.

A conceptual framework for aligning business and information systems from organisational learning perspective

The three decades of on-going executives’ concerns of how to achieve successful alignment between business and information technology shows the complexity of such a vital process. Most of the challenges of alignment are related to knowledge and organisational change and several researchers have introduced a number of mechanisms to address some of these challenges. However, these mechanisms pay less attention to multi-level effects, which results in a limited un-derstanding of alignment across levels. Therefore, we reviewed these challenges from a multi-level learning perspective and found that business and IT alignment is related to the balance of exploitation and exploration strategies with the intellec-tual content of individual, group and organisational levels.

Multi-level planning for semi-autonomous vehicles in traffic scenarios based on separation maximization

The planning of semi-autonomous vehicles in traffic scenarios is a relatively new problem that contributes towards the goal of making road travel by vehicles free of human drivers. An algorithm needs to ensure optimal real time planning of multiple vehicles (moving in either direction along a road), in the presence of a complex obstacle network. Unlike other approaches, here we assume that speed lanes are not present and that different lanes do not need to be maintained for inbound and outbound traffic. Our basic hypothesis is to carry forward the planning task to ensure that a sufficient distance is maintained by each vehicle from all other vehicles, obstacles and road boundaries. We present here a 4-layer planning algorithm that consists of road selection (for selecting the individual roads of traversal to reach the goal), pathway selection (a strategy to avoid and/or overtake obstacles, road diversions and other blockages), pathway distribution (to select the position of a vehicle at every instance of time in a pathway), and trajectory generation (for generating a curve, smooth enough, to allow for the maximum possible speed). Cooperation between vehicles is handled separately at the different levels, the aim being to maximize the separation between vehicles. Simulated results exhibit behaviours of smooth, efficient and safe driving of vehicles in multiple scenarios; along with typical vehicle behaviours including following and overtaking.

Analysis of frequency and intensity of European winter storm events from a multi-model perspective, at synoptic and regional scales

This study focuses on the analysis of winter (October-November-December-January-February-March; ONDJFM) storm events and their changes due to increased anthropogenic greenhouse gas concentrations over Europe. In order to assess uncertainties that are due to model formulation, 4 regional climate models (RCMs) with 5 high resolution experiments, and 4 global general circulation models (GCMs) are considered. Firstly, cyclone systems as synoptic scale processes in winter are investigated, as they are a principal cause of the occurrence of extreme, damage-causing wind speeds. This is achieved by use of an objective cyclone identification and tracking algorithm applied to GCMs. Secondly, changes in extreme near-surface wind speeds are analysed. Based on percentile thresholds, the studied extreme wind speed indices allow a consistent analysis over Europe that takes systematic deviations of the models into account. Relative changes in both intensity and frequency of extreme winds and their related uncertainties are assessed and related to changing patterns of extreme cyclones. A common feature of all investigated GCMs is a reduced track density over central Europe under climate change conditions, if all systems are considered. If only extreme (i.e. the strongest 5%) cyclones are taken into account, an increasing cyclone activity for western parts of central Europe is apparent; however, the climate change signal reveals a reduced spatial coherency when compared to all systems, which exposes partially contrary results. With respect to extreme wind speeds, significant positive changes in intensity and frequency are obtained over at least 3 and 20% of the European domain under study (35–72°N and 15°W–43°E), respectively. Location and extension of the affected areas (up to 60 and 50% of the domain for intensity and frequency, respectively), as well as levels of changes (up to +15 and +200% for intensity and frequency, respectively) are shown to be highly dependent on the driving GCM, whereas differences between RCMs when driven by the same GCM are relatively small.

Fine-grained multi-phase array designs

Hybrid multiprocessor architectures which combine re-configurable computing and multiprocessors on a chip are being proposed to transcend the performance of standard multi-core parallel systems. Both fine-grained and coarse-grained parallel algorithm implementations are feasible in such hybrid frameworks. A compositional strategy for designing fine-grained multi-phase regular processor arrays to target hybrid architectures is presented in this paper. The method is based on deriving component designs using classical regular array techniques and composing the components into a unified global design. Effective designs with phase-changes and data routing at run-time are characteristics of these designs. In order to describe the data transfer between phases, the concept of communication domain is introduced so that the producer–consumer relationship arising from multi-phase computation can be treated in a unified way as a data routing phase. This technique is applied to derive new designs of multi-phase regular arrays with different dataflow between phases of computation.

Mid-Holocene monsoons: a multi-model analysis of the inter-hemispheric differences in the responses to orbital forcing and ocean feedbacks

The response of monsoon circulation in the northern and southern hemisphere to 6 ka orbital forcing has been examined in 17 atmospheric general circulation models and 11 coupled ocean–atmosphere general circulation models. The atmospheric response to increased summer insolation at 6 ka in the northern subtropics strengthens the northern-hemisphere summer monsoons and leads to increased monsoonal precipitation in western North America, northern Africa and China; ocean feedbacks amplify this response and lead to further increase in monsoon precipitation in these three regions. The atmospheric response to reduced summer insolation at 6 ka in the southern subtropics weakens the southern-hemisphere summer monsoons and leads to decreased monsoonal precipitation in northern South America, southern Africa and northern Australia; ocean feedbacks weaken this response so that the decrease in rainfall is smaller than might otherwise be expected. The role of the ocean in monsoonal circulation in other regions is more complex. There is no discernable impact of orbital forcing in the monsoon region of North America in the atmosphere-only simulations but a strong increase in precipitation in the ocean–atmosphere simulations. In contrast, there is a strong atmospheric response to orbital forcing over northern India but ocean feedback reduces the strength of the change in the monsoon although it still remains stronger than today. Although there are differences in magnitude and exact location of regional precipitation changes from model to model, the same basic mechanisms are involved in the oceanic modulation of the response to orbital forcing and this gives rise to a robust ensemble response for each of the monsoon systems. Comparison of simulated and reconstructed changes in regional climate suggest that the coupled ocean–atmosphere simulations produce more realistic changes in the northern-hemisphere monsoons than atmosphere-only simulations, though they underestimate the observed changes in precipitation in all regions. Evaluation of the southern-hemisphere monsoons is limited by lack of quantitative reconstructions, but suggest that model skill in simulating these monsoons is limited.

Improving the evaluation of hydrological multi-model forecast performance in the Upper Danube Catchment

Medium range flood forecasting activities, driven by various meteorological forecasts ranging from high resolution deterministic forecasts to low spatial resolution ensemble prediction systems, share a major challenge in the appropriateness and design of performance measures. In this paper possible limitations of some traditional hydrological and meteorological prediction quality and verification measures are identified. Some simple modifications are applied in order to circumvent the problem of the autocorrelation dominating river discharge time-series and in order to create a benchmark model enabling the decision makers to evaluate the forecast quality and the model quality. Although the performance period is quite short the advantage of a simple cost-loss function as a measure of forecast quality can be demonstrated.

Pragmatic oriented data interoperability for smart healthcare information systems

Smart healthcare is a complex domain for systems integration due to human and technical factors and heterogeneous data sources involved. As a part of smart city, it is such a complex area where clinical functions require smartness of multi-systems collaborations for effective communications among departments, and radiology is one of the areas highly relies on intelligent information integration and communication. Therefore, it faces many challenges regarding integration and its interoperability such as information collision, heterogeneous data sources, policy obstacles, and procedure mismanagement. The purpose of this study is to conduct an analysis of data, semantic, and pragmatic interoperability of systems integration in radiology department, and to develop a pragmatic interoperability framework for guiding the integration. We select an on-going project at a local hospital for undertaking our case study. The project is to achieve data sharing and interoperability among Radiology Information Systems (RIS), Electronic Patient Record (EPR), and Picture Archiving and Communication Systems (PACS). Qualitative data collection and analysis methods are used. The data sources consisted of documentation including publications and internal working papers, one year of non-participant observations and 37 interviews with radiologists, clinicians, directors of IT services, referring clinicians, radiographers, receptionists and secretary. We identified four primary phases of data analysis process for the case study: requirements and barriers identification, integration approach, interoperability measurements, and knowledge foundations. Each phase is discussed and supported by qualitative data. Through the analysis we also develop a pragmatic interoperability framework that summaries the empirical findings and proposes recommendations for guiding the integration in the radiology context.

Diversity for resilience : multi-scale application of agro-ecology

The integration of ecological principles into agricultural systems presents major opportunities for spreading risk at the crop and farm scale. This paper presents mechanisms by which diversity at several scales within the farming system can increase the stability of production. Diversity of above- and below-ground biota, but also genetic and phenotypic diversity within crops, has an essential role in safeguarding farm production. Novel mixtures of legume-grass leys have been shown to potentially provide significant benefits for pollinator and decomposer ecosystem services but to realise the greatest improvements carefully tailored farm management is needed such as mowing or grazing time, and the type and depth of cutivation. Complex farmland landscapes such as agroforestry systems have the potential to support pollinator abundance and diversity and spread risk across production enterprises. At the crop level, early results indicate that the vulnerability of pollen development, flowering and early grain set to abiotic stress can be ameliorated by managing flowering time through genotypic selection, and through the buffering effects of pollinators. Finally, the risk of sub-optimal quality in cereals can be mitigated through integration of near isogenic lines selected to escape specific abiotic stress events. We conclude that genotypic, phenotypic and community diversity can all be increased at multiple scales to enhance resilience in agricultural systems.

A benchmark-driven modelling approach for evaluating deployment choices on a multi-core architecture

The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.

Multi-finger grasps in a dynamic environment

Most current state-of-the-art haptic devices render only a single force, however almost all human grasps are characterised by multiple forces and torques applied by the fingers and palms of the hand to the object. In this chapter we will begin by considering the different types of grasp and then consider the physics of rigid objects that will be needed for correct haptic rendering. We then describe an algorithm to represent the forces associated with grasp in a natural manner. The power of the algorithm is that it considers only the capabilities of the haptic device and requires no model of the hand, thus applies to most practical grasp types. The technique is sufficiently general that it would also apply to multi-hand interactions, and hence to collaborative interactions where several people interact with the same rigid object. Key concepts in friction and rigid body dynamics are discussed and applied to the problem of rendering multiple forces to allow the person to choose their grasp on a virtual object and perceive the resulting movement via the forces in a natural way. The algorithm also generalises well to support computation of multi-body physics

Situation assessment through multi-modal sensing of dynamic environments to support cognitive robot control

Awareness of emerging situations in a dynamic operational environment of a robotic assistive device is an essential capability of such a cognitive system, based on its effective and efficient assessment of the prevailing situation. This allows the system to interact with the environment in a sensible (semi)autonomous / pro-active manner without the need for frequent interventions from a supervisor. In this paper, we report a novel generic Situation Assessment Architecture for robotic systems directly assisting humans as developed in the CORBYS project. This paper presents the overall architecture for situation assessment and its application in proof-of-concept Demonstrators as developed and validated within the CORBYS project. These include a robotic human follower and a mobile gait rehabilitation robotic system. We present an overview of the structure and functionality of the Situation Assessment Architecture for robotic systems with results and observations as collected from initial validation on the two CORBYS Demonstrators.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.