Variability Model Research Articles

Stratospheric vacillations in a minimal contour dynamics model

AbstractA low-dimensional dynamical system that describes dynamical variability of the stratospheric polar vortex is presented. The derivation is based on a linearized, contour-dynamics representation of quasigeostrophic shallow water flow on a polar f-plane. The model consists of a single linear wave mode propagating on a near-circular patch of constant potential vorticity (PV). The PV jump at the vortex edge serves as an additional degree of freedom. The wave is forced by surface topography, and interacts with the vortex through a simplified parameterization of diabatic wave/mean flow interaction. The approach can be generalized to other geometries.The resulting three-component system depends on four non-dimensional parameters, and the structure of the steady state solutions can be determined analytically in some detail. Despite its extreme simplification, the model exhibits variability that is closely analogous to the Holton-Mass model, a well-known and more complex dynamical model of stratospheric variability. The present model exhibits two stable steady solutions, one consisting of a strong vortex with a small amplitude wave and the second consisting of a weak vortex with a large amplitude wave. Periodic and aperiodic limit cycles are also identified, analogous to similar solutions in the Holton-Mass model. Model trajectories also exhibit a number of behaviors that have been identified in observations. A key insight is that the time-mean state of the vortex is predominantly controlled by the properties of the linear mode, while the strength of the topographic forcing plays a far weaker role away from bifurcations.

(Invited) Compact Model for Short-Channel Organic Thin-Film Transistors with Extension for Non-Quasistatic Circuit Simulation and Variability Analysis

We present a compact model for organic thin-film transistors (TFTs) that covers both below-threshold and above-threshold operation with a single charge-based current expression [1]. The effect of hopping transport is included by a power-law mobility model. Contact resistances for staggered and coplanar device structures (Fig. 1) are considered, which can be nonlinear in the case of work-function mismatch between contacts and organic semiconductor [2]. Short-channel effects in submicron transistors, such as threshold-voltage roll-off and drain-induced barrier lowering (DIBL), are included [3].From the expression for the accumulated channel charge, a closed-form model for the drain-current variability due to carrier-number and correlated mobility fluctuations has been derived, relating these statistical variations to the trap density in the channel [4].Furthermore, by applying a partitioning scheme, charges are explicitly attributed to the source and drain contacts, allowing the derivation of a charge-based capacitance model valid for quasi-static operation [5]. Charges in the gate-to-contact overlap regions have been included.Utilizing this device model in a transmission-line approach, a circuit simulation including non-quasistatic effects is possible [6]. In the circuit-simulation netlist, the TFT is replaced by a macro model consisting of a finite number of n single transistors, whereby each single transistor represents a section of the intrinsic channel capacitance and a segment of the intrinsic channel resistance. This model is able to capture the charging and discharging of the channel capacitance of each segment through the channel resistance of the adjacent transistors. In this way, the frequency dependence of the node-to-node capacitances of the full device is obtained.The compact model has been implemented in the hardware description language Verilog-A and verified using results of measurements performed on organic p-channel TFTs fabricated on flexible polyethylene naphthalate (PEN) substrates by stencil lithography (Figs. 2, 3). The TFTs consist of 25-nm-thick aluminum gate electrodes, a 5.3-nm-thick hybrid AlOx/SAM gate dielectric, 30-nm-thick gold (Au) source and drain contacts coated with a pentafluorobenzenethiol (PFBT) monolayer, and a 25-nm-thick vacuum-deposited layer of the small-molecule organic semiconductor DPh-DNTT [7,8]. The transmission-line approach has been verified with good accuracy by comparison with frequency-dependent admittance measurements and numerical simulations of the transient switching behavior of organic TFTs. For a transient analysis, the optimum number of segments required to achieve good agreement between the results from the model and those from TCAD simulations is approximately n=6.In conclusion, the model presented here is fully capable of providing accurate results in dc, small-signal ac, and transient circuit simulations, including short-channel effects. Furthermore, the same set of equations allows an estimation of the drain-current variability due to charge trapping. Acknowledgements: This project was funded by the German Federal Ministry of Education and Research ("SOMOFLEX", No. 13FH015IX6), German Research Foundation (DFG) under Grant KL 1042/9-2 (SPP FFlexCom), and EU H2020 RISE ("DOMINO", No. 645760). We acknowledge AdMOS GmbH, Germany for support.

Detection Limits of Low-mass, Long-period Exoplanets Using Gaussian Processes Applied to HARPS-N Solar Radial Velocities

Abstract Radial velocity (RV) searches for Earth-mass exoplanets in the habitable zone around Sun-like stars are limited by the effects of stellar variability on the host star. In particular, suppression of convective blueshift and brightness inhomogeneities due to photospheric faculae/plage and starspots are the dominant contribution to the variability of such stellar RVs. Gaussian process (GP) regression is a powerful tool for statistically modeling these quasi-periodic variations. We investigate the limits of this technique using 800 days of RVs from the solar telescope on the High Accuracy Radial velocity Planet Searcher for the Northern hemisphere (HARPS-N) spectrograph. These data provide a well-sampled time series of stellar RV variations. Into this data set, we inject Keplerian signals with periods between 100 and 500 days and amplitudes between 0.6 and 2.4 m s−1. We use GP regression to fit the resulting RVs and determine the statistical significance of recovered periods and amplitudes. We then generate synthetic RVs with the same covariance properties as the solar data to determine a lower bound on the observational baseline necessary to detect low-mass planets in Venus-like orbits around a Sun-like star. Our simulations show that discovering planets with a larger mass (∼0.5 m s−1) using current-generation spectrographs and GP regression will require more than 12 yr of densely sampled RV observations. Furthermore, even with a perfect model of stellar variability, discovering a true exo-Venus (∼0.1 m s−1) with current instruments would take over 15 yr. Therefore, next-generation spectrographs and better models of stellar variability are required for detection of such planets.

مطالعه تغییرپذیری پارامترهای فیزیکی(دما و شوری) آبهای خلیج فارس ناشی از تغییرات اقلیم با استفاده از یک مدلسازی عددی و برخی دادههای اندازهگیری

Salinity and water temperature are considered as important characteristics of water of different seas. The absolute values and variability of them in time and space determine life sustainability conditions, development of plants and animals and also types of human activity in seas. Water temperature and salinity are important because of their effects on chemical and biochemical reactions of hydro-organisms. In this research the effects of climate change on physical characteristics of Persian Gulf including water temperature and salinity has been studied using numerical simulations and some observations. To carry out numerical simulation, the 1-dimension oceanic numerical model PROBE was used. The input data of the model includes meteorological information obtained from ECMWF and also initial values of the station. To simulate the vertical turbulence, the relations of Axcell-Liungman, Omstedt, Rodi, Pacanovski and Marchuk have been used for a station in the Persian Gulf and the results have been compared with some measurements and similar studies. The results of investigations show that limits of seawater and salinity variability model outputs are similar but the Omstedt relation shows more detailed changes in comparison to the others. The numerical results indicate that the temperature increase of the Persian Gulf over a decade can be as large as one to two degree Celsius, with some salinity increase as well.

The 2018 update of the US National Seismic Hazard Model: Ground motion models in the western US

The U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous U.S. NSHM includes significant changes to the underlying ground motion models (GMMs), most of which are necessary to enable the new multi-period response spectra (MPRS) requirements of seismic design regulations that use hazard results for 22 spectral periods and eight site classes. This article focuses on the GMMs used in the western United States (WUS) and is a companion to a recent article on the GMMs used in the central and eastern United States (CEUS). In the WUS, for crustal and subduction earthquakes, two models used in previous versions of the NSHM are excluded to provide consistency over all considered periods and site classes. To more accurately estimate ground motions at long periods in the vicinity of Los Angeles, San Francisco, Salt Lake City, and Seattle, the 2018 NSHM incorporates deep sedimentary basin depth from local seismic velocity models. The subduction GMMs considered lack basin depth terms and are modified to include an additional scale factor to account for this. This article documents the WUS GMMs used in the 2018 NSHM update and provides detail on the changes to GMM medians, aleatory variability, epistemic uncertainty, and site-effect models. It compares each of these components with those considered in prior NSHMs and discusses their total effect on hazard.

“It just sounds proper common”: Exploring the social meanings expressed by nonstandard grammar

It has been suggested that morphosyntax has more constrained social meanings than phonological variation, despite the scarcity of empirical research evidencing this claim. By using frequency correlations to isolate stylized moments of grammatical variation, this paper provides evidence of the rich social meanings constructed by nonstandard11We use the term ‘nonstandard’ to refer to linguistic variants that are not codified in the standardised variety of a language. This reflects usual practice in variationist sociolinguistics. We recognize the hegemony of standard language ideologies and the potential for the term ‘nonstandard’ to further marginalize highly regular and frequent modes of language. However, alternative terms such as ‘regional dialect forms’ do not capture the fact that grammatical items are employed across regional and social styles of speech. Also, as our paper demonstrates, variants identified as ‘nonstandard’ are routinely stigmatized, whereas forms described as ‘regional’ are not always sanctioned in the same way or to the same degree; compare, for instance, the use of negative concord (I didn’t do nothing to mean ‘I didn’t do anything’) with the use of a variant like multiple modals (I might could do it to mean ‘I might be able to do it’). Our use of ‘nonstandard’ is intended to identify variants which undergo prescription precisely because of comparison with standardised alternatives. However, note that we refer to individual nonstandard variants as elements of a person’s diverse repertoire (Snell 2013), without presuming that a specific instance of a nonstandard form equates to speaking in a ‘nonstandard dialect’. grammar. In particular, we show that, whilst definite article reduction (DAR), nonstandard were, and negative concord work together in one British working class young person's speech to produce an intimate, collaborative style, these variants are used strategically to index subtly different states and alignments. We also show that other grammatical variants – use of nonstandard irregular preterit forms and demonstrative them – are not used strategically to convey interactional positioning. The different function of these variants demonstrates the diversity of morphosyntax, raising questions about the relationship between grammar and social meaning, ideology, pragmatics and linguistic processing. We argue that addressing these questions not only benefits our understanding of social meaning across different levels of linguistic architecture, it also provides us with better evidence to advocate for alternative (and more suitable) models of linguistic variability in educational discourse.

A high order robust numerical scheme for the generalized Stein's model of neuronal variability

This paper continues the authors's study of robust numerical scheme for generalized Stein's model of neuronal variability, which is a singularly perturbed parabolic partial differential–difference equation with general values of shift arguments. The work on this class of problems is initiated in the papers [K. Bansal and K.K. Sharma, Parameter-robust numerical scheme for time dependent singularly perturbed reaction- diffusion problem with large delay, Numer. Funct. Anal. Optim. 39(2) (2018), pp. 127–154] for unit shift argument and in [K. Bansal and K.K. Sharma, Parameter uniform numerical scheme for time dependent singularly perturbed convection- diffusion-reaction problems with general shift arguments, Numer. Algorithms 75(1) (2017), pp. 113–145] for general shift arguments. In the present paper, this work is further extended to the development of numerical scheme based on Mickens techniques, interpolation and θ scheme. The advantage of this work over the previous research is that it deals with the problem having general values of the shift arguments with higher order of convergence and without any constraints on the number of intervals.

Handling Quantity in Variability Models for System-of-Systems

Problem: Modern systems contain parts that are themselves systems. Such complex systems thus have sets of subsystems that have their own variability. These subsystems contribute to the functionality of a whole system-of-systems (SoS). Such systems have a very high degree of variability. Therefore, a modeling technique for the variability of an entire SoS is required to express two different levels of variability: variability of the SoS as a whole and variability of subsystems. If these levels are described together, the model becomes hard to understand. When the variability model of the SoS is described separately, each variability model is represented by a tree structure and these models are combined in a further tree structure. For each node in a variability model, a quantity is assigned to express the multiplicity of its instances per one instance of its parent node. Quantities of the whole system may refer to the number of subsystem instances in the system. From the viewpoint of the entire system, constraints and requirements written in natural language are often ambiguous regarding the quantities of subsystems. Such ambiguous constraints and requirements may lead to misunderstandings or conflicts in an SoS configuration. Approach: A separate notion is proposed for variability of an SoS; one model considers the SoS as an undivided entity, while the other considers it as a combination of subsystems. Moreover, a domain-specific notation is proposed to express relationships among the variability properties of systems, to solve the ambiguity of quantities and establish the total validity. This notation adapts an approach, named Pincer Movement, which can then be used to automatically deduce the quantities for the constraints and requirements. Validation: The descriptive capability of the proposed notation was validated with four examples of cloud providers. In addition, the proposed method and description tool were validated through a simple experiment on describing variability models with real practitioners.

A Robust computational method for singularly perturbed delay parabolic convection-diffusion equations arising in the modeling of neuronal variability

In this study, a robust computational method involving exponential cubic spline for solving singularly perturbed parabolic convection-diffusion equations arising in the modeling of neuronal variability has been presented. Some numerical examples are considered to validate the theoretical findings. The proposed scheme is shown to be an e-uniformly convergent accuracy of order O(Δt+h^2 ).

Numerical modelling of alongshore variability in waves and wave-driven currents during the morphodynamic change of a laboratory beach

A non-hydrostatic phase-resolving numerical model (SWASH) is used to investigate the wave-driven nearshore hydrodynamics corresponding to new observations from a three-dimensional physical model in a wave basin. In the physical model, waves from a passing storm are simulated by varying the energy and duration of waves generated by a paddle over time and the beach morphology is surveyed in high spatial-resolution using a 3D laser scanner after each segment of the storm. An oblique incident wave angle introduces spatially variability in wave energy along the beach and results in morphologic differences during the storm, with active transport of beach sand by the wave-driven circulation. SWASH is validated using wave and current observations at each stage of the storm, indicating low root-mean-squared errors between model results and wave measurements, where the high-resolution model is able to predict wave shoaling, breaking and generation of the alongshore current. Model-data agreement is not as high for the velocity, suggesting spatial variability in bottom friction and horizontal mixing, and evolution of the bed in the physical model, could explain the differences. The detailed numerical model results indicate that the alongshore current is generated by wave breaking in the nearshore zone, and it increases in speed across a wider surf zone for increasing wave energy during the storm. This is associated with a bottom shear stress that exceeds the critical bed shear stress, with the potential to initiate motion and transport sediment in agreement with the experimental observations.

Tumor growth inhibition modeling of individual lesion dynamics and interorgan variability in HER2-negative breast cancer patients treated with docetaxel.

Information on individual lesion dynamics and organ location are often ignored in pharmacometric modeling analyses of tumor response. Typically, the sum of their longest diameters is utilized. Herein, a tumor growth inhibition model was developed for describing the individual lesion time‐course data from 183 patients with metastatic HER2‐negative breast cancer receiving docetaxel. The interindividual variability (IIV), interlesion variability (ILV), and interorgan variability of parameters describing the lesion time‐courses were evaluated. Additionally, a model describing the probability of new lesion appearance and a time‐to‐event model for overall survival (OS), were developed. Before treatment initiation, the lesions were largest in the soft tissues and smallest in the lungs, and associated with a significant IIV and ILV. The tumor growth rate was 2.6 times higher in the breasts and liver, compared with other metastatic sites. The docetaxel drug effect in the liver, breasts, and soft tissues was greater than or equal to 1.2 times higher compared with other organs. The time‐course of the largest lesion, the presence of at least 3 liver lesions, and the time since study enrollment, increased the probability of new lesion appearance. New lesion appearance, along with the time to growth and time‐course of the largest lesion at baseline, were identified as the best predictors of OS. This tumor modeling approach, incorporating individual lesion dynamics, provided a more complete understanding of heterogeneity in tumor growth and drug effect in different organs. Thus, there may be potential to tailor treatments based on lesion location, lesion size, and early lesion response to provide better clinical outcomes.

Pacific sea surface temperature anomalies as important boundary forcing in driving the interannual Warm Arctic-Cold Continent pattern over the North American sector

AbstractThe leading interannual mode of winter surface air temperature over the North American (NA) sector, characterized by a “Warm Arctic, Cold Continents” (WACC) pattern, exerts pronounced influences on NA weather and climate, while its underlying mechanisms remain elusive. In this study, the relative roles of surface boundary forcing versus internal atmospheric processes for the formation of the WACC pattern are quantitatively investigated using a combined analysis of observations and large-ensemble atmospheric global climate model simulations. Internal atmospheric variability is found to play an important role in shaping the year-to-year WACC variability, contributing to about half of the total variance. An anomalous SST pattern resembling the North Pacific Mode is identified as a major surface boundary forcing pattern in driving the interannual WACC variability over the NA sector, with a minor contribution from sea ice variability over the Chukchi- Bering Seas. Findings from this study not only lead to improved understanding of underlying physics regulating the interannual WACC variability, but also provide important guidance for improved modeling and prediction of regional climate variability over NA and the Arctic region.

Forward modelling of Kepler-band variability due to faculae and spots

ABSTRACT Variability observed in photometric light curves of late-type stars (on time-scales longer than a day) is a dominant noise source in exoplanet surveys and results predominantly from surface manifestations of stellar magnetic activity, namely faculae and spots. The implementation of faculae in light-curve models is an open problem, with scaling typically based on spectra equivalent to hot stellar atmospheres or assuming a solar-derived facular contrast. We modelled rotational (single period) light curves of active G2, K0, M0, and M2 stars, with Sun-like surface distributions and realistic limb-dependent contrasts for faculae and spots. The sensitivity of light-curve variability to changes in model parameters such as stellar inclination, feature area coverage, spot temperature, facular region magnetic flux density, and active band latitudes is explored. For our light-curve modelling approach we used actress, a geometrically accurate model for stellar variability. actress generates two-sphere maps representing stellar surfaces and populates them with user-prescribed spot and facular region distributions. From this, light curves can be calculated at any inclination. Quiet star limb darkening and limb-dependent facular contrasts were derived from MURaM 3D magnetoconvection simulations using ATLAS9. 1D stellar atmosphere models were used for the spot contrasts. We applied actress in Monte Carlo simulations, calculating light-curve variability amplitudes in the Kepler band. We found that, for a given spectral type and stellar inclination, spot temperature and spot area coverage have the largest effect on variability of all simulation parameters. For a spot coverage of $1{{\ \rm per\ cent}}$, the typical variability of a solar-type star is around 2 parts per thousand. The presence of faculae clearly affects the mean brightness and light-curve shape, but has relatively little influence on the variability.

Allesfitter: Flexible Star and Exoplanet Inference from Photometry and Radial Velocity

Abstract We present allesfitter, a public and open-source Python software for flexible and robust inference of stars and exoplanets given photometric and radial velocity data. Allesfitter offers a rich selection of orbital and transit/eclipse models, accommodating multiple exoplanets, multistar systems, transit-timing variations, phase curves, stellar variability, starspots, stellar flares, and various systematic noise models, including Gaussian processes. It features both parameter estimation and Bayesian model selection, allowing either a Markov Chain Monte Carlo or Nested Sampling fit to be easily run. For novice users, a graphical user interface allows all input and perform analyses to be specified; for Python users, all modules can be readily imported into any existing script. Allesfitter also produces publication-ready tables, LaTeX commands, and figures. The software is publicly available (https://github.com/MNGuenther/allesfitter), pip-installable (pip install allesfitter), and well documented (www.allesfitter.com). Finally, we demonstrate the software’s capabilities in several examples and provide updates to the literature where possible for Pi Mensae, TOI-216, WASP-18, KOI-1003, and GJ 1243.

Satisfeitos e comprometidos: é assim a geração Y? Um estudo com professores de escolas municipais de Curitiba/PR

Por este texto apresenta-se resultados de estudo que teve por objetivo analisar a influência da satisfação no comprometimento de professores da geração Y que atuam nas escolas municipais de Curitiba/PR. Trata-se de uma pesquisa quantitativa, exploratória e descritiva utilizando-se a Escala de Satisfação no Trabalho (Siqueira, 2008), e das variáveis de comprometimento organizacional de Meyer e Allen (1991). Participaram da pesquisa os profissionais do magistério com até cinco anos de carreira e trinta anos de idade vinculados à rede municipal. Os dados foram tratados por meio de métodos estatísticos como medidas de tendência central, gráfico de variabilidade e modelo de regressão linear. Os resultados revelam que as dimensões de satisfação com a chefia, promoções e crescimento na carreira são as que impactam no comprometimento.

Mapping of Aluminum Concentration in Bauxite Mining Residues Using Sentinel-2 Imagery

There is a growing interest in the characterization of mining residues, both for environmental assessments and critical raw materials recovery. The lack of sufficient in situ samples hampers an effective geostatistical modelling of material concentrations variability. This paper proposes a method to characterize the aluminum spatial variability in a mine residue from remote sensing data and imprecise information from daily dumping procedures. The method is proposed for the mapping of aluminum within a Greek bauxite residue, using Sentinel-2 imagery. The spatial correlation between metal concentrations and remote sensing indicators (e.g., spectral band ratios) is the premise for mapping aluminum varieties. The proposed method is based on Conditional Gaussian Co-Simulation, where Sentinel-2 images can be used as auxiliary variables. Simulation results are compared with the Co-kriging estimation method. To perform the Co-kriging estimation, the same conditions as simulation are used (same inputs, models, and neighborhoods). Simulation results quantified the metals variability in mining residues, presenting the metal concentration of piled materials in two time periods. For results validation and selecting the best map, fourteen validation samples were used. For the best representative maps of aluminum concentration, a correlation coefficient of about 0.7 between the validation data and obtained aluminum concentration map was obtained.

Психічна трансформація логосу як проблема

The article dwells upon a vital matter of the logos’ mental transformation in metamodern logic, which determined its novelty. The article aims to conceptualize the concept of “logos” within the “depth sociology” (sociology of imagination) and study the socio-psychological process of its change in the current socio-crisis conditions. As the methodological basis of the research, the author suggests the psychoanalytic approach and rich scientific heritage of G. Durand, whose 100th anniversary would be celebrated on May 1, 2021, by the world scientific community. In the world, he is known as a sociologist and researcher of forms and functions of imagination, the author of the concept, theory and scientific method of “depth sociology” (sociology of imagination). The study also used general scientific and psychoanalytic methods of cognition and an interdisciplinary approach, which paved the way for the use of culturological and hermeneutic analysis methods. At the same time, other elements of culturological and sociological cases have been adopted, borrowing concepts and perspectives for explaining socio-psychological phenomena that have a complex psychological nature. Based on the theoretical analysis results, a generalized description of the logos is presented within the framework of its conceptualization in the topic of depth sociology, which to some extent reveals the psychological nature and meaning of the concept. The author proposes a modification of the paradigmatic model of logos variability. The socio-psychological process of its transformation is studied based on G. Durand’s construction. Based on the results of the analysis of the logos state in the current social crisis, the paper shows fragments of its varieties and probabilistic mechanisms of variability. Simultaneously, the institutional uncertainty of the modern geopolitical future in the world creates a basis for pressure on the “two-story” (socio-psychological) topic, where the prospect of further research will be the problem of synchronicity (according to C.-G. Jung).

Interpolation of extremely sparse geo-data by data fusion and collaborative Bayesian compressive sampling

In geotechnical or geological engineering, geo-data interpolation based on measurements is often needed for engineering design and analysis. However, measurements are sometimes extremely sparse (e.g., several, or even just a few, data points) because of limited access to the subsurface and the cost of tests. It is, therefore, difficult to properly interpolate the measurements. On the other hand, multiple data sources (e.g., standard penetration tests, SPT, and cone penetration tests, CPT) often exist in engineering practice, and data fusion methods (e.g., cokriging) have been developed to leverage the correlation among multiple data sources for interpolation of sparse geo-data. Performance of cokriging depends on proper modeling of spatial variability using variogram models. However, the construction of proper variogram models requires many measurement data points. Therefore, it is very challenging to properly interpolate extremely sparse geo-data due to the difficulty in obtaining suitable variogram models. In this study, a novel data fusion method, called collaborative Bayesian compressive sampling (Co-BCS), is proposed to tackle this problem. Equations of the proposed Co-BCS method are derived, and the method is illustrated using real data. The results show that the proposed method not only properly interprets extremely sparse geo-data by integrating correlated secondary data sources but also quantifies the associated interpolation uncertainty simultaneously.

Development of a Hybrid Product Breakdown Structure and Variability Model

ABSTRACTIn transforming from a project‐based engineering approach to a product line engineering (PLE) approach, the engineering teams must have support throughout the transition from evolving tools and methodologies. As an example, the Product Breakdown Structure (PBS) is traditionally a construction‐based decomposition of a complex system, where subsystems reflect a breakdown of the engineering elements with appropriate technical interfaces, subassemblies, and team responsibility delineations. However, when used for a product line with myriad variants, a traditional PBS format provides insufficient detail and structure. As such, using standard desktop software, the author developed a hybrid PBS‐Variability Model (VM), combining the familiar PBS structure with variability modeling aspects based on feature modeling and decision modeling approaches. This resulted in an engineering artifact recognizable as a PBS and easy to adapt to design evolution, yet sufficiently expansive to initially characterize variability. In this way, the traditional PBS evolves to the hybrid PBS‐VM before transitioning to a complete variability model, thereby supporting the engineering teams transitioning from a project‐based engineering approach to a PLE approach. In this paper, the author describes the traditional PBS limitations, the hybrid model development process with a custom‐developed syntax description, the resulting hybrid model, and conclusions on appropriate product line usage.

AUGMENTED BLOOD PRESSURE VARIABILITY FOLLOWING CONTINUOUS INFUSION OF NORADRENALINE IN RATS

Objective: Augmented blood pressure (BP) variability has been shown to be an independent cardiovascular risk factor. Activity of the sympathetic nervous system is an important determinant factor of the 24-h profile of BP variability, although it is unknown whether persistent adrenergic activation causes augmented BP variability or not. Here we report that continuous infusion of noradrenalin augments 24-h BP variability in rats, and our efforts were also made to explore the mechanism of action through which noradrenalin exerted this effect. Design and method: Nine-week-old male Wistar rats maintained under a 12-h light and 12-h dark cycle were continuously infused with subcutaneous 30 mg/h noradrenalin, 150 mg/h of the a1-adrenergic agonist phenylephrine, or 30 mg/h of the non-selective b-agonist isoproterenol, for 14 days. Noradrenalin-infused rats were also administered either oral 5 mg/day prazosin, an a1-blocker, or 50 mg/day atenolol, a b1-blocker, during the infusion period. BP variability was evaluated before and after 7 and 14 days of the infusion, using a coefficient of variation (CV) of BP recorded every 15 min under an unrestrained condition via an abdominal aortic catheter by a radiotelemetry system. Results: Continuous infusion of noradrenalin significantly increased BP variability at 7 and 14 days, slightly elevating BP levels, and this increase was observed similarly in the light and dark cycles. Noradrenalin-induced augmentation of BP variability was partially attenuated by oral administration of prazosin, but not by atenolol. This action of noradrenalin was mimicked by continuous infusion of phenylephrine, while isoproterenol failed to affect the BP variability. Conclusions: Continuous infusion of noradrenalin increased BP variability in rats through an a1-adrenergic receptor-mediated mechanism, suggesting that the noradrenalin-infused rat is an animal model of augmented BP variability induced by persistent adrenergic activation. This model could be useful in pharmacological screening of the suppressive action of candidate drugs on augmented BP variability in vivo.