Structural changes in quasi-one-dimensional many-electron systems: From linear to zigzag and beyond

Many-electron systems confined to a quasi-one-dimensional geometry by a cylindrical distribution of positive charge have been investigated by density functional computations in the unrestricted local spin density approximation. Our investigations have been focused on the low-density regime, in which electrons are localized. The results reveal a wide variety of different charge and spin configurations, including linear and zig-zag chains, single-and double-strand helices, and twisted chains of dimers. The spin-spin coupling turns from weakly antiferromagnetic at relatively high density, to weakly ferromagnetic at the lowest densities considered in our computations. The stability of linear chains of localized charge has been investigated by analyzing the radial dependence of the self-consistent potential and by computing the dispersion relation of low-energy harmonic excitations.

Local network-based measures to assess the inferability of different regulatory networks

The purpose of this study is to compare the inferability of various synthetic as well as real biological regulatory networks. In order to assess differences we apply local network-based measures. That means, instead of applying global measures, we investigate and assess an inference algorithm locally, on the level of individual edges and subnetworks. We demonstrate the behaviour of our local network-based measures with respect to different regulatory networks by conducting large-scale simulations. As inference algorithm we use exemplarily ARACNE. The results from our exploratory analysis allow us not only to gain new insights into the strength and weakness of an inference algorithm with respect to characteristics of different regulatory networks, but also to obtain information that could be used to design novel problem-specific statistical estimators.

Sensory systems and spatial memory in the fruit bat Rousettus aegyptiacus

The megachiropteran fruit bat Rousettus aegyptiacus is able to orient and navigate using both vision and echolocation. These two sensory systems have different environmental constraints however, echolocation being relatively short range when compared with vision. Despite this difference, an experiment testing their memory of a perch location demonstrates that once the location of a perch is learned R. aegyptiacus is not influenced by the movement of local landmark cues in the vicinity of the perch under either light or dark conditions. Thus despite the differing constraints of vision and echolocation, this suggests a place is remembered as a location in space and not by associations with landmarks in the vicinity. A decrease in initial performance when the task was repeated in the dark suggested the possibility that a memory of a location learned using vision does not generalize to echolocation.

Press perturbations and indirect effects in real food webs

The prediction of the effects of disturbances in natural systems is limited by the general lack of knowledge on the strength of species interactions, i.e., the effect of one species on the population growth rate of another, and by the uncertainty of the effects that may be manifested via indirect pathways within the food web. Here we explored the consequences of changes in species populations for the remaining species within nine exceptionally well-characterized empirical food webs, for which, unlike the vast majority of other published webs, feeding links have been fully quantied. Using the inverse of the Jacobian matrix, we found that perturbations to species with few connections have larger net effects (considering both direct and indirect pathways between two species) on the rest of the food web than do disturbances to species that are highly connected. For 40% of predator-prey links, predators had positive net effects on prey populations, due to the predominance of indirect interactions. Our results highlight the fundamental, but often counterintuitive, role of indirect effects for the maintenance of food web complexity and biodiversity.

An Autopilot Based on a Local Control Network Design for an Unmanned Surface Vehicle

Over recent years, a number of marine autopilots designed using linear techniques have underperformed owing to their inability to cope with nonlinear vessel dynamics. To this end, a new design framework for the development of nonlinear autopilots is proposed herein. Local control networks (LCNs) can be used in the design of nonlinear control systems. In this paper, a LCN approach is taken in the design of a nonlinear autopilot for controlling the nonlinear yaw dynamics of an unmanned surface vehicle known as Springer. It is considered the approach is the first of its kind to be used in marine control systems design. Simulation results are presented and the performance of the nonlinear autopilot is compared with that of an existing Springer linear quadratic Gaussian (LQG) autopilot using standard system performance criteria. From the results it can be concluded the LCN autopilot out performed that based on LQG techniques in terms of the selected criteria. Also it provided more energy saving control strategies and would thereby increase operational duration times for the vehicle during real-time missions.

Food intake, milk production, and tissue changes of Holstein-Friesian and Jersey x Holstein-Friesian dairy cows within a medium-input grazing system and a high-input total confinement system

Although interest in crossbreeding within dairy systems has increased, the role of Jersey crossbred cows within high concentrate input systems has received little attention. This experiment was designed to examine the performance of Holstein-Friesian (HF) and Jersey x Holstein-Friesian (J x HF) cows within a high concentrate input total confinement system (CON) and a medium concentrate input grazing system (GRZ). Eighty spring-calving dairy cows were used in a 2 (cow genotype) x 2 (milk production system) factorial design experiment. The experiment commenced when cows calved and encompassed a full lactation. With GRZ, cows were offered diets containing grass silage and concentrates [70:30 dry matter (DM) ratio] until turnout, grazed grass plus 1.0 kg of concentrate/day during a 199-d grazing period, and grass silage and concentrates (75:25 DM ratio) following rehousing and until drying-off. With CON, cows were confined throughout the lactation and offered diets containing grass silage and concentrates (DM ratio; 40:60, 50:50, 40:40, and 75:25 during d 1 to 100, 101 to 200, 201 to 250, and 251 until drying-off, respectively). Full-lactation concentrate DM intakes were 791 and 2,905 kg/cow for systems GRZ and CON, respectively. Although HF cows had a higher lactation milk yield than J x HF cows, the latter produced milk with a higher fat and protein content, so that solids-corrected milk yield (SCM) was unaffected by genotype. Somatic cell score was higher with the J x HF cows. Throughout lactation, HF cows were on average 37 kg heavier than J x HF cows, whereas the J x HF cows had a higher body condition score. Within each system, food intake did not differ between genotypes, whereas full-lactation yields of milk, fat plus protein, and SCM were higher with CON than with GRZ. A significant genotype x environment interaction was observed for milk yield, and a trend was found for an interaction with SCM. Crossbred cows on CON gained more body condition than HF cows, and overall pregnancy rate was unaffected by either genotype or management system. In summary, milk and SCM yields were higher with CON than with GRZ, whereas genotype had no effect on SCM. However, HF cows exhibited a greater milk yield response and a trend toward a greater SCM yield response with increasing concentrate levels compared with the crossbred cows.

Weak interactions, omnivory and emergent food-web properties

Empirical studies have shown that, in real ecosystems, species-interaction strengths are generally skewed in their distribution towards weak interactions. Some theoretical work also suggests that weak interactions, especially in omnivorous links, are important for the local stability of a community at equilibrium. However, the majority of theoretical studies use uniform distributions of interaction strengths to generate artificial communities for study. We investigate the effects of the underlying interaction-strength distribution upon the return time, permanence and feasibility of simple Lotka-Volterra equilibrium communities. We show that a skew towards weak interactions promotes local and global stability only when omnivory is present. It is found that skewed interaction strengths are an emergent property of stable omnivorous communities, and that this skew towards weak interactions creates a dynamic constraint maintaining omnivory. Omnivory is more likely to occur when omnivorous interactions are skewed towards weak interactions. However, a skew towards weak interactions increases the return time to equilibrium, delays the recovery of ecosystems and hence decreases the stability of a community. When no skew is imposed, the set of stable omnivorous communities shows an emergent distribution of skewed interaction strengths. Our results apply to both local and global concepts of stability and are robust to the definition of a feasible community. These results are discussed in the light of empirical data and other theoretical studies, in conjunction with their broader implications for community assembly.

A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.

Food-poisoning and commercial air travel

With the introduction of budget airlines and greater competitiveness amongst all airlines, air travel has now become an extremely popular form of travel, presenting its own unique set of risks from food poisoning. Foodborne illness associated with air travel is quite uncommon in the modern era. However, when it occurs, it may have serious implications for passengers and when crew are affected, has the potential to threaten safety. Quality, safe, in-flight catering relies on high standards of food preparation and storage; this applies at the airport kitchens (or at subcontractors' facilities), on the aircraft and in the transportation vehicles which carry the food from the ground source to the aircraft. This is especially challenging in certain countries. Several foodborne outbreaks have been recorded by the airline industry as a result of a number of different failures of these systems. These have provided an opportunity to learn from past mistakes and current practice has, therefore, reached such a standard so as to minimise risk of failures of this kind. This review examines: (i) the origin of food safety in modern commercial aviation; (ii) outbreaks which have occurred previously relating to aviation travel; (iii) the microbiological quality of food and water on board commercial aircraft; and (iv) how Hazard Analysis Critical Control Points may be employed to maintain food safety in aviation travel.

Development of a rapid low cost fluorescent biosensor for the detection of food contaminants

A prototype fluorescent based biosensor has been developed for the antibody based detection of food related contaminants. Its performance was characterised and showed a typical antibody binding signal of 200-2000 mV, a short term noise of 9.1 mV, and baseline slope of -0.016 mV/s over 4 h. Bulk signal detection repeatability (n=23) and reproducibility (n=3) were less than 2.4%CV. The biosensor detection unit was evaluated using two food related model systems proving its ability to monitor both binding using commercial products and inhibition through the development of an assay. This assay development potential was evaluated by observing the biosensor's performance whilst appraising several labelled antibody and glass slide configurations. The molecular interaction between biotin and an anti-biotin antibody was shown to be inhibited by 41% due to the presence of biotin in a sample. A food toxin (domoic acid) calibration curve was produced, with %CVs ranging from 2.7 to 7.8%, and a midpoint of approximately 17 ng/ml with further optimisation possible. The ultimate aim of this study was to demonstrate the working principles of this innovative biosensor as a potential portable tool with the opportunity of interchangeable assays. The biosensor design is applicable for the requirements of routine food contaminant analysis, with respect to performance, functionality and cost. (C) 2012 Elsevier B.V. All rights reserved.

“Boundary-setting as a core activity in complex public systems”

Title: Boundary-setting as a core activity in complex public systems
Authors: Joanne Murphy & Mary Lee Rhodes

The definition of the boundary of a system is at the core of any systems approach (Midgley 2000; 2003). By defining boundaries we enable – and delimit – the range of outcomes sought and the actions and resources that can be brought to bear. In complex adaptive systems (CAS) analysis, the conceptualisaion and definition of boundaries is particularly challenging as they are constantly undergoing redefinition through agent action, interaction and entry/exit. (Rhodes et al 2011). The concept of ‘boundaries’ appears regularly in a wide range of literature around public management, administration, geopolitics, regeneration and organisational development. Discussions around boundaries focus on many things from concrete physical manifestations and barriers, to virtual interfaces between one organisational unit and another, or even entirely theoretical demarcations between different schools of thought (Kaboolian, 1998, Levi-Faur, 2004, Agranoff & McGuire, 2004).

However, managing ‘beyond’ such boundaries is a routinely recurring aspiration that transcends sectors and local concerns. Unsurprisingly then, there is an increasing understanding of the need to acknowledge and manage such boundaries (whether they be physical, social or organisational) within public management as a discipline (Currie et al 2007, Fitzsimmons and White, 1997, Murtagh, 2002). This paper explores the impact of boundaries on public management strategic decision-making in the sectors of urban regeneration and healthcare. In particular, it focuses on demarcations to physical space, communal identity and within professional relationships in these sectors.

The first section describes the research that gave rise to the paper and the cases examined. Next we briefly define what we mean by boundaries. We explore issues that have emerged from our analysis of urban regeneration and health care singularly, before looking at how the concept of boundaries is a recurrent concern across the sectors. The main contribution of the paper is an exploration of how a CAS lens can bring a new insight into the concept of boundaries and decision-making in the two sets of case studies. This discussion will concentrate on initial conditions, bifurcation and adaptation as key CAS factors in relation to boundaries. We conclude with a brief discussion on the benefits of a CAS lens to an analysis of boundaries in public management decision-making.
References:

Agranoff, R. and McGuire, M. (2003) Collaborative Public Management: Strategies for Local Government. Washington, DC: Georgetown Univ. Press.

Currie, G., Lockett, A. (2007) “A critique of transformational leadership: moral, professional & contingent dimensions of leadership within public services organizations”. Human Relations 60: 341-370.

Fitzsimmons and White, (1997) "Crossing boundaries: communication between professional groups", Journal of Management in Medicine, Vol. 11 Iss: 2, pp.96 – 101

Kaboolian, L. (1998) “The New Public Management: Challenging the Boundaries of the Management vs. Administration Debate” Public Administration Review Vol. 58, No. 3 pp.189-193

Levi-Faur D. and Vigoda-Gadot Eran (eds) (2004) International Public Policy and Management: Policy Learning Beyond Regional, Cultural and Political Boundaries, Marcel Dekker,
Midgley, G. (ed) (2003) Systems Thinking. London: Sage Publications

Midgley, G. (2000) Systemic Intervention: Philosophy, Methodology and Practice. New York, NY: Kluwer.

Murtagh, B. (2002). The Politics of Territory: Policy and Segregation in Northern Ireland. Basingstoke, Palgrave.

Rhodes, ML, Joanne Murphy, Jenny Muir, John Murray (2011) Public Management & Complexity Theory: Richer Decision Making in Irish Public Services, UK: Routledge

Macroscopic limit of time-dependent density-functional theory for adiabatic local approximations of the exchange-correlation kernel

Time-dependent density-functional theory is a rather accurate and efficient way to compute electronic excitations for finite systems. However, in the macroscopic limit (systems of increasing size), for the usual adiabatic random-phase, local-density, or generalized-gradient approximations, one recovers the Kohn-Sham independent-particle picture, and thus the incorrect band gap. To clarify this trend, we investigate the macroscopic limit of the exchange-correlation kernel in such approximations by means of an algebraical analysis complemented with numerical studies of a one-dimensional tight-binding model. We link the failure to shift the Kohn-Sham spectrum of these approximate kernels to the fact that the corresponding operators in the transition space act only on a finite subspace.

Compositional Divergence and Convergence in Local Communities and Spatially Structured Landscapes

Community structure depends on both deterministic and stochastic processes. However, patterns of community dissimilarity (e.g. difference in species composition) are difficult to interpret in terms of the relative roles of these processes. Local communities can be more dissimilar (divergence) than, less dissimilar (convergence) than, or as dissimilar as a hypothetical control based on either null or neutral models. However, several mechanisms may result in the same pattern, or act concurrently to generate a pattern, and much research has recently been focusing on unravelling these mechanisms and their relative contributions. Using a simulation approach, we addressed the effect of a complex but realistic spatial structure in the distribution of the niche axis and we analysed patterns of species co-occurrence and beta diversity as measured by dissimilarity indices (e.g. Jaccard index) using either expectations under a null model or neutral dynamics (i.e., based on switching off the niche effect). The strength of niche processes, dispersal, and environmental noise strongly interacted so that niche-driven dynamics may result in local communities that either diverge or converge depending on the combination of these factors. Thus, a fundamental result is that, in real systems, interacting processes of community assembly can be disentangled only by measuring traits such as niche breadth and dispersal. The ability to detect the signal of the niche was also dependent on the spatial resolution of the sampling strategy, which must account for the multiple scale spatial patterns in the niche axis. Notably, some of the patterns we observed correspond to patterns of community dissimilarities previously observed in the field and suggest mechanistic explanations for them or the data required to solve them. Our framework offers a synthesis of the patterns of community dissimilarity produced by the interaction of deterministic and stochastic determinants of community assembly in a spatially explicit and complex context.