Toy model to describe the effect of positional blocklike disorder in metamaterials composites

We study theoretically the effect of a new type of blocklike positional disorder on the effective electromagnetic properties of one-dimensional chains of resonant, high-permittivity dielectric particles, where particles are arranged into perfectly well-ordered blocks whose relative position is a random variable. This creates a finite order correlation length that mimics the situation encountered in metamaterials fabricated through self-assembled techniques, whose structures often display short-range order between near neighbors but long-range disorder, due to stacking defects. Using a spectral theory approach combined with a principal component statistical analysis, we study, in the long-wavelength regime, the evolution of the electromagnetic response when the composite filling fraction and the block size are changed. Modifications in key features of the resonant response (amplitude, width, etc.) are investigated, showing a regime transition for a filling fraction around 50%.

Multi-impurity adsorption model for modeling crystal purity and shape evolution during crystallization processes in impure media

Peer reviewed

The reliability mathematical model of load-sharing parallel systems based on fatigue cumulative damage

Conventional reliability models for parallel systems are not applicable for the analysis of parallel systems with load transfer and sharing. In this short communication, firstly, the dependent failures of parallel systems are analyzed, and the reliability model of load-sharing parallel system is presented based on Miner cumulative damage theory and the full probability formula. Secondly, the parallel system reliability is calculated by Monte Carlo simulation when the component life follows the Weibull distribution. The research result shows that the proposed reliability mathematical model could analyze and evaluate the reliability of parallel systems in the presence of load transfer.

A Generic Model of Execution for Synthesizing Domain-Specific Models

Software engineering researchers are challenged to provide increasingly more pow- erful levels of abstractions to address the rising complexity inherent in software solu- tions. One new development paradigm that places models as abstraction at the fore- front of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code. Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process. The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources. At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM’s synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise. This dissertation investigates how to decouple the DSK from the MoE and sub- sequently producing a generic model of execution (GMoE) from the remaining appli- cation logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis com- ponent of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions. This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.

Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files

Sea ice models contain many different parameterizations of which one of the most commonly used is a subgrid-scale ice thickness distribution (ITD). The effect of this model component and the associated ice strength formulation on the reproduction of observed Arctic sea ice is assessed. To this end the model's performance in reproducing satellite observations of sea ice concentration, thickness and drift is evaluated. For an unbiased comparison, different model configurations with and without an ITD are tuned with an automated parameter optimization. The original combination of ITD and ice strength parameterization does not lead to better results than a simple single category model. Yet changing to a simpler ice strength formulation, which depends linearly on the mean ice thickness across all thickness categories, allows to clearly improve the model-data misfit when using an ITD. In the original formulation, the ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to thicker albeit weaker ice on average.

(Table 1) Age comparison between the GPTS and ODP Site 181-1123 age model for each chron base within the Middle Miocene section

Today the deep western boundary current (DWBC) east of New Zealand is the most important route for deep water entering the Pacific Ocean. Large-scale changes in deep water circulation patterns are thought to have been associated with the development of the East Antarctic Ice Sheet (EAIS) close to the main source of bottom water for the DWBC. Here we reconstruct the changing speed of the southwest Pacific DWBC during the middle Miocene from ~15.5-12.5 Ma, a period of significant global ice accumulation associated with EAIS growth. Sortable silt mean grain sizes from Ocean Drilling Program Site 1123 reveal variability in the speed of the Pacific inflow on the timescale of the 41 kyr orbital obliquity cycle. Similar orbital period flow changes have recently been demonstrated for the Pleistocene epoch. Collectively, these observations suggest that a strong coupling between changes in the speed of the deep Pacific inflow and high-latitude climate forcing may have been a persistent feature of the global thermohaline circulation system for at least the past 15 Myr. Furthermore, long-term changes in flow speed suggest an intensification of the DWBC under an inferred increase in Southern Component Water production. This occurred at the same time as decreasing Tethyan outflow and major EAIS growth between ~15.5 and 13.5 Ma. These results provide evidence that a major component of the deep thermohaline circulation was associated with the middle Miocene growth of the EAIS and support the view that this time interval represents an important step in the development of the Neogene icehouse climate.

(Table S1) Tie-points used in age model construction for ODP Leg 172 sites

ix Ocean Drilling Program (ODP) sites, in the Northwest Atlantic have been used to investigate kinematic and chemical changes in the "Western Boundary Undercurrent" (WBUC) during the development of full glacial conditions across the Marine Isotope Stage 5a/4 boundary (~70,000 years ago). Sortable silt mean grain size(sort s) measurements are employed to examine changes in near bottom flow speeds, together with carbon isotopes measured in benthic foraminifera and % planktic foraminiferal fragmentation as proxies for changes in water-mass chemistry. A depth transect of cores, spanning 1.8-4.6 km depth, allows changes in both the strength and depth of the WBUC to be constrained across millennial scale events. Sort s measurements reveal that the flow speed structure of the WBUC during warm intervals ("interstadials") was comparable to modern (Holocene) conditions. However, significant differences are observed during cold intervals, with higher relative flow speeds inferred for the shallow component of the WBUC (~2 km depth) during all cold "stadial" intervals (including Heinrich Stadial 6), and a substantial weakening of the deep component (~3-4 km) during full glacial conditions. Our results therefore reveal that the onset of full glacial conditions was associated with a regime shift to a shallower mode of circulation (involving Glacial North Atlantic Intermediate Water) that was quantitatively distinct from preceding cold stadial events. Furthermore, our chemical proxy data show that the physical response of the WBUC during the last glacial inception was probably coupled to basin-wide changes in the water-mass composition of the deep Northwest Atlantic.

Age model and palaeoclimate records over the past 22,000 years of sediment core GeoB10053-7

The Australian-Indonesian monsoon is an important component of the climate system in the tropical Indo-Pacific region. However, its past variability, relation with northern and southern high-latitude climate and connection to the other Asian monsoon systems are poorly understood. Here we present high-resolution records of monsoon-controlled austral winter upwelling during the past 22,000 years, based on planktic foraminiferal oxygen isotopes and faunal composition in a sedimentary archive collected offshore southern Java. We show that glacial-interglacial variations in the Australian-Indonesian winter monsoon were in phase with the Indian summer monsoon system, consistent with their modern linkage through cross-equatorial surface winds. Likewise, millennial-scale variability of upwelling shares similar sign and timing with upwelling variability in the Arabian Sea. On the basis of element composition and grain-size distribution as precipitation-sensitive proxies in the same archive, we infer that (austral) summer monsoon rainfall was highest during the Bølling-Allerød period and the past 2,500 years. Our results indicate drier conditions during Heinrich Stadial 1 due to a southward shift of summer rainfall and a relatively weak Hadley cell south of the Equator. We suggest that the Australian-Indonesian summer and winter monsoon variability were closely linked to summer insolation and abrupt climate changes in the northern hemisphere.

An impulsive differential equation model for Marek's disease

Many dynamical processes are subject to abrupt changes in state. Often these perturbations can be periodic and of short duration relative to the evolving process. These types of phenomena are described well by what are referred to as impulsive differential equations, systems of differential equations coupled with discrete mappings in state space. In this thesis we employ impulsive differential equations to model disease transmission within an industrial livestock barn. In particular we focus on the poultry industry and a viral disease of poultry called Marek's disease. This system lends itself well to impulsive differential equations. Entire cohorts of poultry are introduced and removed from a barn concurrently. Additionally, Marek's disease is transmitted indirectly and the viral particles can survive outside the host for weeks. Therefore, depopulating, cleaning, and restocking of the barn are integral factors in modelling disease transmission and can be completely captured by the impulsive component of the model. Our model allows us to investigate how modern broiler farm practices can make disease elimination difficult or impossible to achieve. It also enables us to investigate factors that may contribute to virulence evolution. Our model suggests that by decrease the cohort duration or by decreasing the flock density, Marek's disease can be eliminated from a barn with no increase in cleaning effort. Unfortunately our model also suggests that these practices will lead to disease evolution towards greater virulence. Additionally, our model suggests that if intensive cleaning between cohorts does not rid the barn of disease, it may drive evolution and cause the disease to become more virulent.

Supporting the Model-Driven Development of Real-time Embedded Systems with Run-Time Monitoring and Animation via Highly Customizable Code Generation

This paper presents a vision that allows the combined use of model-driven engineering, run-time monitoring, and animation for the development and analysis of components in real-time embedded systems. Key building block in the tool environment supporting this vision is a highly-customizable code generation process. Customization is performed via a configuration specification which describes the ways in which input is provided to the component, the ways in which run-time execution information can be observed, and how these observations drive animation tools. The environment is envisioned to be suitable for different activities ranging from quality assurance to supporting certification, teaching, and outreach and will be built exclusively with open source tools to increase impact. A preliminary prototype implementation is described.

Purine catabolic pathway revealed by transcriptomics in the model marine bacteriumRuegeria pomeroyiDSS-3

Purines are nitrogen-rich compounds that are widely distributed in the marine environment and are an important component of the dissolved organic nitrogen (DON) pool. Even though purines have been shown to be degraded by bacterioplankton, the identities of marine bacteria capable of purine degradation and their underlying catabolic mechanisms are currently unknown. This study shows that Ruegeria pomeroyi, a model marine bacterium and Marine Roseobacter Clade (MRC) representative, utilizes xanthine as a source of carbon and nitrogen. The R. pomeroyi genome contains putative genes that encode xanthine dehydrogenase (XDH), which is expressed during growth with xanthine. RNAseq-based analysis of the R. pomeroyi transcriptome revealed that the transcription of an XDH-initiated catabolic pathway is up-regulated during growth with xanthine, with transcription greatest when xanthine was the only available carbon source. The RNAseq-deduced pathway indicates that glyoxylate and ammonia are the key intermediates from xanthine degradation. Utilising a laboratory model, this study has identified the potential genes and catabolic pathway active during xanthine degradation. The ability of R. pomeroyi to utilize xanthine provides novel insights into the capabilities of the MRC that may contribute to their success in marine ecosystems and the potential biogeochemical importance of the group in processing DON.

Purine catabolic pathway revealed by transcriptomics in the model marine bacteriumRuegeria pomeroyiDSS-3

Purines are nitrogen-rich compounds that are widely distributed in the marine environment and are an important component of the dissolved organic nitrogen (DON) pool. Even though purines have been shown to be degraded by bacterioplankton, the identities of marine bacteria capable of purine degradation and their underlying catabolic mechanisms are currently unknown. This study shows that Ruegeria pomeroyi, a model marine bacterium and Marine Roseobacter Clade (MRC) representative, utilizes xanthine as a source of carbon and nitrogen. The R. pomeroyi genome contains putative genes that encode xanthine dehydrogenase (XDH), which is expressed during growth with xanthine. RNAseq-based analysis of the R. pomeroyi transcriptome revealed that the transcription of an XDH-initiated catabolic pathway is up-regulated during growth with xanthine, with transcription greatest when xanthine was the only available carbon source. The RNAseq-deduced pathway indicates that glyoxylate and ammonia are the key intermediates from xanthine degradation. Utilising a laboratory model, this study has identified the potential genes and catabolic pathway active during xanthine degradation. The ability of R. pomeroyi to utilize xanthine provides novel insights into the capabilities of the MRC that may contribute to their success in marine ecosystems and the potential biogeochemical importance of the group in processing DON.

Serum Amyloid P-Component Prevents Cardiac Remodeling in Hypertensive Heart Disease

The potential for serum amyloid P-component (SAP) to prevent cardiac remodeling and identify worsening diastolic dysfunction (DD) was investigated. The anti-fibrotic potential of SAP was tested in an animal model of hypertensive heart disease (spontaneously hypertensive rats treated with SAP [SHR - SAP] × 12 weeks). Biomarker analysis included a prospective study of 60 patients with asymptomatic progressive DD. Compared with vehicle-treated Wistar-Kyoto rats (WKY-V), the vehicle-treated SHRs (SHR-V) exhibited significant increases in left ventricular mass, perivascular collagen, cardiomyocyte size, and macrophage infiltration. SAP administration was associated with significantly lower left ventricular mass (p < 0.01), perivascular collagen (p < 0.01), and cardiomyocyte size (p < 0.01). Macrophage infiltration was significantly attenuated in the SHR-SAP group. Biomarker analysis showed significant decreases in SAP concentration over time in patients with progressive DD (p < 0.05). Our results indicate that SAP prevents cardiac remodeling by inhibiting recruitment of pro-fibrotic macrophages and that depleted SAP levels identify patients with advancing DD suggesting a role for SAP therapy.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

Use of Galleria mellonella as a model organism to study Legionella pneumophila infection.

Legionella pneumophila, the causative agent of a severe pneumonia named Legionnaires' disease, is an important human pathogen that infects and replicates within alveolar macrophages. Its virulence depends on the Dot/Icm type IV secretion system (T4SS), which is essential to establish a replication permissive vacuole known as the Legionella containing vacuole (LCV). L. pneumophila infection can be modeled in mice however most mouse strains are not permissive, leading to the search for novel infection models. We have recently shown that the larvae of the wax moth Galleria mellonella are suitable for investigation of L. pneumophila infection. G. mellonella is increasingly used as an infection model for human pathogens and a good correlation exists between virulence of several bacterial species in the insect and in mammalian models. A key component of the larvae's immune defenses are hemocytes, professional phagocytes, which take up and destroy invaders. L. pneumophila is able to infect, form a LCV and replicate within these cells. Here we demonstrate protocols for analyzing L. pneumophila virulence in the G. mellonella model, including how to grow infectious L. pneumophila, pretreat the larvae with inhibitors, infect the larvae and how to extract infected cells for quantification and immunofluorescence microscopy. We also describe how to quantify bacterial replication and fitness in competition assays. These approaches allow for the rapid screening of mutants to determine factors important in L. pneumophila virulence, describing a new tool to aid our understanding of this complex pathogen.