Effect of the crown design and interface lute parameters on the stress-state of a machined crown-tooth system: A finite element analysis

The effect of preparation design and the physical properties of the interface lute on the restored machined ceramic crown-tooth complex are poorly understood. The aim of this work was to determine, by means of three-dimensional finite element analysis (3D FEA) the effect of the tooth preparation design and the elastic modulus of the cement on the stress state of the cemented machined ceramic crown-tooth complex. The three-dimensional structure of human premolar teeth, restored with adhesively cemented machined ceramic crowns, was digitized with a micro-CT scanner. An accurate, high resolution, digital replica model of a restored tooth was created. Two preparation designs, with different occlusal morphologies, were modeled with cements of 3 different elastic moduli. Interactive medical image processing software (mimics and professional CAD modeling software) was used to create sophisticated digital models that included the supporting structures; periodontal ligament and alveolar bone. The generated models were imported into an FEA software program (hypermesh version 10.0, Altair Engineering Inc.) with all degrees of freedom constrained at the outer surface of the supporting cortical bone of the crown-tooth complex. Five different elastic moduli values were given to the adhesive cement interface 1.8 GPa, 4 GPa, 8 GPa, 18.3 GPa and 40 GPa; the four lower values are representative of currently used cementing lutes and 40 GPa is set as an extreme high value. The stress distribution under simulated applied loads was determined. The preparation design demonstrated an effect on the stress state of the restored tooth system. The cement elastic modulus affected the stress state in the cement and dentin structures but not in the crown, the pulp, the periodontal ligament or the cancellous and cortical bone. The results of this study suggest that both the choice of the preparation design and the cement elastic modulus can affect the stress state within the restored crown-tooth complex.

Assessing the distribution of social-ecological resilience and risk: Ireland as a case study of the uneven impact of famine

Explanations for the causes of famine and food insecurity often reside at a high level of aggregation or abstraction. Popular models within famine studies have often emphasised the role of prime movers such as population stress, or the political-economic structure of access channels, as key determinants of food security. Explanation typically resides at the macro level, obscuring the presence of substantial within-country differences in the manner in which such stressors operate. This study offers an alternative approach to analyse the uneven nature of food security, drawing on the Great Irish famine of 1845–1852. Ireland is often viewed as a classical case of Malthusian stress, whereby population outstripped food supply under a pre-famine demographic regime of expanded fertility. Many have also pointed to Ireland's integration with capitalist markets through its colonial relationship with the British state, and country-wide system of landlordism, as key determinants of local agricultural activity. Such models are misguided, ignoring both substantial complexities in regional demography, and the continuity of non-capitalistic, communal modes of land management long into the nineteenth century. Drawing on resilience ecology and complexity theory, this paper subjects a set of aggregate data on pre-famine Ireland to an optimisation clustering procedure, in order to discern the potential presence of distinctive social–ecological regimes. Based on measures of demography, social structure, geography, and land tenure, this typology reveals substantial internal variation in regional social–ecological structure, and vastly differing levels of distress during the peak famine months. This exercise calls into question the validity of accounts which emphasise uniformity of structure, by revealing a variety of regional regimes, which profoundly mediated local conditions of food security. Future research should therefore consider the potential presence of internal variations in resilience and risk exposure, rather than seeking to characterise cases based on singular macro-dynamics and stressors alone.

Assessing the Nonequilibrium Thermodynamics in a Quenched Quantum Many-Body System via Single Projective Measurements

We analyze the nature of the statistics of the work done on or by a quantum many-body system brought out of equilibrium. We show that, for the sudden quench and for an initial state that commutes with the initial Hamiltonian, it is possible to retrieve the whole nonequilibrium thermodynamics via single projective measurements of observables. We highlight, in a physically clear way, the qualitative implications for the statistics of work coming from considering processes described by operators that either commute or do not commute with the unperturbed Hamiltonian of a given system. We consider a quantum many-body system and derive an expression that allows us to give a physical interpretation, for a thermal initial state, to all of the cumulants of the work in the case of quenched operators commuting with the unperturbed Hamiltonian. In the commuting case, the observables that we need to measure have an intuitive physical meaning. Conversely, in the noncommuting case, we show that, although it is possible to operate fully within the single-measurement framework irrespectively of the size of the quench, some difficulties are faced in providing a clear-cut physical interpretation to the cumulants. This circumstance makes the study of the physics of the system nontrivial and highlights the nonintuitive phenomenology of the emergence of thermodynamics from the fully quantum microscopic description. We illustrate our ideas with the example of the Ising model in a transverse field showing the interesting behavior of the high-order statistical moments of the work distribution for a generic thermal state and linking them to the critical nature of the model itself.

Proteomics on porcine haptoglobin and IgG/IgA show protein species distribution and glycosylation pattern to remain similar in PCV2-SD infection

Haptoglobin (Hp) and immunoglobulins are plasma glycoproteins involved in the immune reaction of the organism after infection and/or inflammation. Porcine circovirus type 2-systemic disease (PCV2-SD), formerly known as postweaning multisystemic wasting syndrome (PMWS), is a globally spread pig disease of great economic impact. PCV2-SD affects the immunological system of pigs causing immunosuppression. The aim of this work was to characterize the Hp protein species of healthy and PCV2-SD affected pigs, as well as the protein backbone and the glycan chain composition of porcine Hp. PCV2-SD affected pigs had an increased overall Hp level, but it did not affect the ratio between Hp species. Glycoproteomic analysis of the Hp β subunits confirmed that porcine Hp is N-glycosylated and, unexpectedly, O-glycosylated, a PTM that is not found on Hp from healthy humans. The glyco-profile of porcine IgG and IgA heavy chains was also characterized; decreased levels of both proteins were found in the investigated group of PCV2-SD affected pigs. Obtained results indicate that no significant changes in the N- and O-glycosylation patterns of these major porcine plasma glycoproteins were detectable between healthy and PCV2-SD affected animals.

Loss-of-Mains Protection System by Application of Phasor Measurement Unit Technology with Experimentally Assessed Threshold Settings

Loss-of-mains protection is an important component of the protection systems of embedded generation. The role of loss-of-mains is to disconnect the embedded generator from the utility grid in the event that connection to utility dispatched generation is lost. This is necessary for a number of reasons, including the safety of personnel during fault restoration and the protection of plant against out-of-synchronism reclosure to the mains supply. The incumbent methods of loss-of-mains protection were designed when the installed capacity of embedded generation was low, and known problems with nuisance tripping of the devices were considered acceptable because of the insignificant consequence to system operation. With the dramatic increase in the installed capacity of embedded generation over the last decade, the limitations of current islanding detection methods are no longer acceptable. This study describes a new method of loss-of-mains protection based on phasor measurement unit (PMU) technology, specifically using a low cost PMU device of the authors' design which has been developed for distribution network applications. The proposed method addresses the limitations of the incumbent methods, providing a solution that is free of nuisance tripping and has a zero non-detection zone. This system has been tested experimentally and is shown to be practical, feasible and effective. Threshold settings for the new method are recommended based on data acquired from both the Great Britain and Ireland power systems.

Transatlantic distribution of the Alaskan White River Ash

Volcanic ash layers preserved within the geologic record represent precise time markers that correlate disparate depositional environments and enable the investigation of synchronous and/or asynchronous behaviors in Earth system and archaeological sciences. However, it is generally assumed that only exceptionally powerful events, such as supereruptions (≥450 km3 of ejecta as dense-rock equivalent; recurrence interval of ∼105 yr), distribute ash broadly enough to have an impact on human society, or allow us to address geologic, climatic, and cultural questions on an intercontinental scale. Here we use geochemical, age, and morphological evidence to show that the Alaskan White River Ash (eastern lobe; A.D. 833–850) correlates to the “AD860B” ash (A.D. 846–848) found in Greenland and northern Europe. These occurrences represent the distribution of an ash over 7000 km, linking marine, terrestrial, and ice-core records. Our results indicate that tephra from more moderate-size eruptions, with recurrence intervals of ∼100 yr, can have substantially greater distributions than previously thought, with direct implications for volcanic dispersal studies, correlation of widely distributed proxy records, and volcanic hazard assessment.

Fair charging strategies for EVs connected to a low-voltage distribution network

The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration. © 2013 IEEE.

Neuropeptides in Helminths: Occurrence and Distribution

Nematode neuropeptide systems comprise an exceptionally complex array of similar to 250 peptidic signaling molecules that operate within a structurally simple nervous system of similar to 300 neurons. A relatively complete picture of the neuropeptide complement is available for Caenorhabditis elegans, with 30 flp, 38 ins and 43 nlp genes having been documented; accumulating evidence indicates similar complexity in parasitic nematodes from clades I, III, IV and V. In contrast, the picture for parasitic platyhelminths is less clear, with the limited peptide sequence data available providing concrete evidence for only FMRFamide-like peptide (FLP) and neuropeptide F (NPF) signaling systems, each of which only comprises one or two peptides. With the completion of the Schmidtea meditteranea and Schistosoma mansoni genome projects and expressed sequence tag datasets for other flatworm parasites becoming available, the time is ripe for a detailed reanalysis of neuropeptide signaling in flatworms. Although the actual neuropeptides provide limited obvious value as targets for chemotherapeutic-based control strategies, they do highlight the signaling systems present in these helminths and provide tools for the discovery of more amenable targets such as neuropeptide receptors or neuropeptide processing enzymes. Also, they offer opportunities to evaluate the potential of their associated signaling pathways as targets through RNA interference (RNAi)-based, target validation strategies. Currently, within both helminth phyla, the flp signaling systems appear to merit further investigation as they are intrinsically linked with motor function, a proven target for successful anti-parasitics; it is clear that some nematode NLPs also play a role in motor function and could have similar appeal. At this time, it is unclear if flatworm NPF and nematode INS peptides operate in pathways that have utility for parasite control. Clearly, RNAi-based validation could be a starting point for scoring potential target pathways within neuropeptide signaling for parasiticide discovery programs. Also, recent successes in the application of in planta-based RNAi control strategies for plant parasitic nematodes reveal a strategy whereby neuropeptide encoding genes could become targets for parasite control. The possibility of developing these approaches for the control of animal and human parasites is intriguing, but will require significant advances in the delivery of RNAi-triggers.

An Architecture of a Multi-Agent System for SCADA - Dealing With Uncertainty, Plans and Actions

This paper presents a multi-agent system approach to address the difficulties encountered in traditional SCADA systems deployed in critical environments such as electrical power generation, transmission and distribution. The approach models uncertainty and combines multiple sources of uncertain information to deliver robust plan selection. We examine the approach in the context of a simplified power supply/demand scenario using a residential grid connected solar system and consider the challenges of modelling and reasoning with
uncertain sensor information in this environment. We discuss examples of plans and actions required for sensing, establish and discuss the effect of uncertainty on such systems and investigate different uncertainty theories and how they can fuse uncertain information from multiple sources for effective decision making in
such a complex system.

Electron-acoustic solitons in an electron-beam plasma system with kappa-distributed electrons

Interaction of a stream of high-energy electrons with the background plasma plays an important role in the astrophysical phenomena such as interplanetary and stellar bow shock and Earth's foreshock emission. It is not yet fully understood how electrostatic solitary waves are produced at the bow shock. Interestingly, a population of energetic suprathermal electrons were also found to exist in those environments. Previously, we have studied the properties of negative electrostatic potential solitary structures exist in such a plasma with excess suprathermal electrons. In the present study, we investigate the existence conditions and propagation properties of electron-acoustic solitary waves in a plasma consisting of an electron beam fluid, a cold electron fluid, and hot suprathermal electrons modeled by a kappa-distribution function. The Sagdeev pseudopotential method was used to investigate the occurrence of stationary-profile solitary waves. We have determined how the electron-acoustic soliton characteristics depend on the electron beam parameters. It is found that the existence domain for solitons becomes narrower with an increase in the suprathermality of hot electrons, increasing the beam speed, decreasing the beam-to-cold electron population ratio. These results lead to a better understanding of the formation of electron-acoustic solitary waves observed in those space plasma systems characterized by kappa-distributed electrons and inertial drifting (beam) electrons.

Electron-acoustic solitons in an electron-beam plasma system with kappa-distributed electrons

We investigate the existence conditions and propagation properties of electron-acoustic solitary waves in a plasma consisting of an electron beam fluid, a cold electron fluid, and a hot suprathermal electron component modeled by a k-distribution function. The Sagdeev pseudopotential method was used to investigate the occurrence of stationary-profile solitary waves. We have determined how the soliton characteristics depend on the electron beam parameters. It is found that the existence domain for solitons becomes narrower with an increase in the suprathermality of hot electrons, increasing the beam speed, and decreasing the beam-to-cold electron population ratio.

System flexibility provision using short term grid scale storage

This paper presents a novel analysis of the utilisation of small grid scale energy storage to mitigate negative system operational impacts due to high penetrations of wind power. This was investigated by artificially lowering the minimum stable generation level of a gas thermal generating unit coupled to a storage device over a five hour storage charging window using a unit commitment and economic dispatch model. The key findings of the analysis were a 0.18% reduction in wind curtailment, a 2.35 MW/min reduction in the ramping rate required to be met by all generators in the test system during a representative period and a total generation cost reduction of €6.5 million.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

A Continuous Time Markov Chain Based Sequential Analytical Approach for Composite Power System Reliability Assessment

This paper proposes a continuous time Markov chain (CTMC) based sequential analytical approach for composite generation and transmission systems reliability assessment. The basic idea is to construct a CTMC model for the composite system. Based on this model, sequential analyses are performed. Various kinds of reliability indices can be obtained, including expectation, variance, frequency, duration and probability distribution. In order to reduce the dimension of the state space, traditional CTMC modeling approach is modified by merging all high order contingencies into a single state, which can be calculated by Monte Carlo simulation (MCS). Then a state mergence technique is developed to integrate all normal states to further reduce the dimension of the CTMC model. Moreover, a time discretization method is presented for the CTMC model calculation. Case studies are performed on the RBTS and a modified IEEE 300-bus test system. The results indicate that sequential reliability assessment can be performed by the proposed approach. Comparing with the traditional sequential Monte Carlo simulation method, the proposed method is more efficient, especially in small scale or very reliable power systems.

Distribution of assimilated carbon within the plant and rhizosphere of Lolium perenne:Influence of temperature

Perennial rye-grass plants were pulse labelled with [¹⁴C]-CO₂ over a range of temperatures (5-25°C). The fate of the label was determined within the plant and soil. The temperature at which plants were pulse labelled had a marked effect on the distribution of the label within the plant and soil system. Root-soil respiration increased from 5.7 to 24.15% when expressed as a percentage of net assimilated label. The percentage of label remaining in the plant root and in the soil was greater at 5 and 25°C, with a minimum for both these components at 15°C. At 15°C the percentage of net assimilated label that remained in the shoots was greater than at other temperatures, with this percentage decreasing at the lower and higher temperatures. © 1989.