Multiscalar Model Research Articles

On self-dual Carrollian conformal nonlinear electrodynamics

In this work, we study the duality symmetry group of Carrollian (nonlinear) electrodynamics and propose a family of Carrollian ModMax theories, which are invariant under Carrollian SO(2) electromagnetic (EM) duality transformations and conformal transformation. We define the Carrollian SO(2) EM transformations, with the help of Hodge duality in Carrollian geometry, then we rederive the Gaillard-Zumino consistency condition for EM duality of Carrollian nonlinear electrodynamics. Together with the traceless condition for the energy-momentum tensor, we are able to determine the Lagrangian of the Carrollian ModMax theories among pure electrodynamics. We furthermore study their behaviors under the TT¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{T\\overline{T}} $$\\end{document} deformation flow, and show that these theories deform to each other and may reach two endpoints under the flow, with one of the endpoint being the Carrollian Maxwell theory. As a byproduct, we construct a family of two-dimensional Carrollian ModMax-like multiple scalar theories, which are closed under the TT¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{T\\overline{T}} $$\\end{document} flow and may flow to a BMS free multi-scalar model.

Co-Benefits Through Coordination of Climate Action and Peacebuilding: A System Dynamics Model

Climate disasters affect human security and development, moreso in fragile and conflict-affected contexts where population’ capacities to cope with climate change are compromised. Responses to such crises lie at the nexus of humanitarian assistance, development, and peacebuilding. Yet, there are still too few integrated programmatic responses coordinating peacebuilding and climate actions to ensure a progressive human development. This research develops a multi-scalar model to help actors identify thematic areas to inform synergistic efforts and programs at different scales to better coordinate their actions. Findings suggest that climate action and peacebuilding sectors can coordinate actions around climate and conflict risk assessments, the management of land and water resources, ecosystem restoration, nature-based climate adaptation, climate and conflict smart agriculture, natural resources governance, and sustainable market development. These collaborative efforts have the potential to generate co-benefits, such as increased social cohesion and livelihood creation.

Multiscalar Model-Based Predictive Torque Control Without Weighting Factors and Current Sensors for Induction Motor Drives

This article focuses on eliminating the weighting factor in traditional predictive torque control (PTC) and considers the control scheme without current sensors. A current sensorless direct PTC method without the weighting factor for induction motor (IM) drives is proposed. Based on the multiscalar model, the controller directly predicts the torque and its dual quantity, instead of predicting the stator flux and stator current in advance and then indirectly calculating the torque like PTC. Since the torque and its dual quantity (the inner and external products of the flux and stator current) have the same units and dimensions, the design of the cost function does not require a weighting factor. Furthermore, an adaptive virtual current observer is used to reconstruct the stator currents. The estimated currents replace the measured currents to realize current sensorless, which can avoid the measurement noise caused by the current sensors, thus reducing the current and torque ripples. Simulation and experimental results illustrate the effectiveness of the proposed approach under different working conditions.

Unifying inflation with early and late dark energy with multiple fields: Spontaneously broken scale invariant two measures theory

A unified multi scalar field model with three flat regions is discussed. The three flat regions are the inflation, early and late dark energy epochs. The potential is obtained by a spontaneous breaking of scale invariance generated by Non Riemannian Measures of integration (or Two Measures Theories (TMT)).We define the scale invariant couplings of the scalar fields to the different measures through exponential potentials. Spontaneous breaking of scale invariance takes place when integrating the fields that define the measures. When going to the Einstein frame we obtain: (i) An effective potential for the scalar fields with three flat regions which allows for a unified description of both early universe inflation (in the higher energy density flat region) as well as of present dark energy epoch which can be realized with a double phase, i.e., in two flat regions. (ii) In the slow roll inflation, only one field combination the ``dilaton", which transforms under scale transformations, has non trivial dynamics, the orthogonal one, which is scale invariant remains constant. (iv) In the late universe we define scale invariant couplings of Dark Matter to the dilaton. These couplings define a matter induced potential for the dilaton and extremizing this potential determines the scale invariant scalar field, while all exotic non canonical behavior of the Dark Matter as well as any possible $5^{th}$ force disappear. (v) We calculate the evolution of the late universe under these conditions with the realization of two different possible realizations of $\Lambda$CDM type scenarios depending of the flat region in the late universe. These two phases could appear at different times in the history of the universe.(vi) From the Planck data, we find the constraints on the parameters during the inflationary epoch and these values are used to obtain constraints relevant to the present epoch.

The promise of panarchy in managed retreat: converging psychological perspectives and complex adaptive systems theory

This paper interrogates the nature of climate resilience by adopting “panarchy” as a heuristic model to visualize how small-scale processes such as individual environmental risk perceptions are interrelated with broader social and ecological systems to confer community resilience. Thematic analysis of resident interviews from a pilot study conducted in the Rockaways, New York revealed the foundations of environmental risk perceptions and the ways in which they are both a product of and catalyst for social-ecological system (SES) resilience. The debate around managed retreat necessitates a complex systems perspective to promote equitable and just adaptation and transformation while avoiding unintended consequences which often result from single-scale inquiry. Integrating risk perception in the explicit multi-scalar model of panarchy proposes a new way to think about the complex social, economic, political, and psychological processes converging across space and time to confer community resilience and visualize the complexity inherent in relocation. In other words, connecting climate resilience and managed retreat with psychological processes like risk perception emphasizes the importance of implementing multi-scalar interventions to build community adaptive capacity.

Multiscalar field models: Interaction potentials, wave functions and cosmological solutions

We consider a multiscalar tensor cosmology model described by Friedmann–Robertson–Walker (FRW) spacetime with zero spatial curvature. Three specific scalar interaction potentials that characterize the model are analyzed under a set of coordinate transformations. By implication, we solve for the wave function of the universe, reduce the dimension of the underlying Hamiltonian system and consequently, establish analytical solutions of the multiscalar model’s field equations.

Migration as mobility? An intersectional approach

ABSTRACT Within the inclusive approach of mobility studies, migration has been referred to as one of the most prominent forms of mobility. However, discussing all migrants’ experiences as just “mobile” experiences shadows the range and nuances of migration. This paper argues and illustrates how migration can be a form of mobility and also addresses migration as a much nuanced form of mobility that has been rather silent in existing literature. We examine one social condition that has informed a range of international migrants’ experiences: their (re)organization of gender patterns within the family on the basis of transnational realities. We use a multi-scalar model of intersectionality to conceptualise migratory movements as mobility, particularly when the meaning is assigned to it on the basis of power relationships. This way, we suggest a fruitful intersectional analysis of migration and mobilities.

Paleolithic artifact deposits at Wadi Dabsa, Saudi Arabia: A multiscalar geoarchaeological approach to building an interpretative framework

AbstractSurface artifacts dominate the archaeological record of arid landscapes, particularly the Saharo‐Arabian belt, a pivotal region in dispersals out of Africa. Discarded by hominins, these artifacts are key to understanding past landscape use and dispersals, yet behavioral interpretation of present‐day artifact distributions cannot be carried out without understanding how geomorphological processes have controlled, and continue to control, artifact preservation, exposure and visibility at multiple scales. We employ a geoarchaeological approach to unraveling the formation of a surface assemblage of 2,970 Palaeolithic and later lithic artifacts at Wadi Dabsa, Saudi Arabia, the richest locality recorded to date in the southwestern Red Sea coastal region. Wadi Dabsa basin, within the volcanic Harrat Al Birk, contains extensive tufa deposits formed during wetter conditions. We employ regional landscape mapping and automatic classification of surface conditions using satellite imagery, field observations, local landform mapping, archaeological survey, excavation, and sedimentological analyses to develop a multiscalar model of landscape evolution and geomorphological controls acting on artifact distributions in the basin. The main artifact assemblage is identified as a palimpsest of activity, actively forming on a deflating surface, a model with significant implications for future study and interpretation of this, and other, surface artifact assemblages.

A Multiscalar Approach to Mapping Marginal Agricultural Land: Smallholder Agriculture in Malawi

Marginal agricultural lands are defined here by suboptimal biophysical conditions and historically variable or low agricultural production. We characterize these areas using remotely sensed information to disentangle the biophysical and possible social factors driving marginality. Considering both the modifiable areal unit problem and the ecological fallacy problem, the heuristic we propose is generalizable across geographies and scales and provides information at multiple decision-making levels through a multiscalar interannual variability model. We present results from our study of Malawi, where the landscape is densely cultivated and smallholder farmers frequently occupy marginal lands, to illustrate the potential of a multiscalar analysis in a place where food insecurity alleviation is needed and where remote sensing can provide necessary information. Our framework for identifying marginal agricultural lands consists of (1) locating long-term agricultural land, (2) measuring interannual productivity of long-term farmed locations, and (3) assessing marginal biophysical land characteristics and the fundamental climate niche for the dominant crop (in this case maize). Productivity and marginality in Malawi are spatially organized, and an assessment of productivity at multiple scales highlights the importance of presenting both global and local spatiotemporal variability for managing agroecological variance. By disaggregating broad classes of historically marginal production and the underlying drivers of marginality, different intervention efforts can intelligently target areas most likely to receive maximum benefit. These methodologies can be applied by both policymakers and scholars to identify and target marginal agricultural areas for improved productivity and for the support of smallholder farmer livelihoods.

Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data

BackgroundThe tumour stroma -or tumour microenvironment- is an important constituent of solid cancers and it is thought to be one of the main obstacles to quantitative translation of drug activity between the preclinical and clinical phases of drug development. The tumour-stroma relationship has been described as being both pro- and antitumour in multiple studies. However, the causality of this complex biological relationship between the tumour and stroma has not yet been explored in a quantitative manner in complex tumour morphologies.MethodsTo understand how these stromal and microenvironmental factors contribute to tumour physiology and how oxygen distributes within them, we have developed a lattice-based multiscalar cellular automaton model. This model uses principles of cytokine and oxygen diffusion as well as cell motility and plasticity to describe tumour-stroma landscapes. Furthermore, to calibrate the model, we propose an innovative modelling platform to extract model parameters from multiple in-vitro assays. This platform provides a novel way to extract meta-data that can be used to complement in-vivo studies and can be further applied in other contexts.ResultsHere we show the necessity of the tumour-stroma opposing relationship for the model simulations to successfully describe the in-vivo stromal patterns of the human lung cancer cell lines Calu3 and Calu6, as models of clinical and preclinical tumour-stromal topologies. This is especially relevant to drugs that target the tumour microenvironment, such as antiangiogenics, compounds targeting the hedgehog pathway or immune checkpoint inhibitors, and is potentially a key platform to understand the mechanistic drivers for these drugs.ConclusionThe tumour-stroma automaton model presented here enables the interpretation of complex in-vitro data and uses it to parametrise a model for in-vivo tumour-stromal relationships.

Downscaling material flow analysis: The case of the cereal supply chain in France

The spatial reconstruction of the production, trade, transformation and consumption flows of a specific material, can become an important decision-help tool for improving resource management and for studying environmental pressures from the producer's to the consumer's viewpoint. One of the obstacles preventing its actual use in the decision-making process is that building such studies at various geographical scales proves to be costly both in time and manpower. In this article, we propose a semi-automatic methodology to overcome this issue: we describe our multi-scalar model and its data-reconciliation component and apply it to cereal flows. Namely, using official databases (Insee, Agreste, FranceAgriMer, SitraM) as well as corporate sources, we reconstructed the supply chain flows of the 22 French regions as well as the flows of four nested territories: France, the Rhône-Alpes region, the Isère department and the territory of the SCoT of Grenoble. We display the results using Sankey diagrams and discuss the intervals of confidence of the model's outputs. We conclude on the perspectives of coupling this model with economic, social and environmental aspects that would provide key information to decision-makers.

Multiscalar model for the determination of spatially explicit riparian vegetation roughness

Improved understanding of the connection between riparian vegetation and channel change requires evaluating how fine‐scale interactions among stems, water, and sediment affect larger scale flow and sediment transport fields. We propose a spatially explicit model that resolves patch‐scale (submeter) patterns of hydraulic roughness over the reach scale caused by stands of shrubby riparian vegetation. We worked in tamarisk‐dominated stands on the Yampa and Green Rivers in Dinosaur National Monument, northwestern Colorado, USA, where questions remain regarding the role of vegetation in inducing or exacerbating documented channel changes. Hydraulic roughness patterns were derived from patch‐scale measurements made with detailed terrestrial laser scan (TLS) data that were extrapolated to reach scales based on correlation with light detection and ranging (LiDAR) (ALS) data. Two‐dimensional, patch‐scale, hydraulic models were used to parameterize the stage dependence of hydraulic roughness of typical patch types (i.e., sparse, moderate, and dense patches). We illustrate the value of using this approach to characterize vegetation roughness by applying our results to a two‐dimensional hydraulic model of flow for one of our study sites. Results from this work predict that the roughness of vegetated floodplains increases with flow depth and is dependent on patch‐scale stem organization. Geomorphically relevant patterns (i.e., areas of low or high shear stress that are likely to scour or fill during high flows) become apparent with the detail introduced by spatially explicit, depth‐dependent roughness. To our knowledge, the multiscalar analysis presented here is the first to mechanistically account for shrubby riparian vegetation stand structure, and associated hydraulic roughness of vegetation patches, at the reach scale.

Capturing multiscalar feedbacks in urban land change: a coupled system dynamics spatial logistic approach

In this paper we ask two questions: Does a multiscalar urban land-change model that couples a region-scale system dynamics model with a local-scale spatial logit model better predict the amount of urban land change than either model alone? Does a multiscalar urban land-change model that couples regional and local-scale factors better predict the spatial patterns of urban land change than a standalone local-scale spatial logit model? To examine these questions, we develop a coupled system dynamics spatial logit (CSDSL) model for the Pearl River Delta, China, that incorporates region-scale population and economic factors with local-scale biophysical and accessibility factors. In terms of predicting the amounts of urban land change, the CSDSL model is 15% and 18% more accurate than the standalone spatial logit and system dynamics models, respectively. In terms of predicting the spatial pattern of urban land change, the CSDSL model slightly outperforms the spatial logit model as measured by four spatial patte...

Broken rotor bar impact on sensorless control of induction machine

PurposeThe purpose of this paper is analysis of the sensorless control system of induction machine with broken rotor for diagnostic purposes. Increasing popularity of sensorless controlled variable speed drives requires research in area of reliability, range of stable operation, fault symptoms and application of diagnosis methods.Design/methodology/approachT transformation used for conversion of instantaneous rotor currents electrical circuit representation to space vector components is investigated to apply with closed‐loop modeling algorithm. Evaluation of the algorithm is based on analysis of asymmetry influence to the orthogonal and zero components of space vector representation. Multiscalar model of the machine and selected structures of state observers are used for sensorless control system synthesis. Proposed method of frequency characteristics calculation is used for state observers analysis in open‐loop operation.FindingsNew algorithm of applying the T transformation allows for closed‐loop and sensorless control system simulation with asymmetric machine due to broken rotor. Compensating effect of the closed‐loop control system with speed measurements and diagnosis information in control system variables are identified. Proposed frequency analysis of state observers is presented and applied. Variables with amplified characteristic frequency components related to rotor asymmetry are compared for selected structures of state observers and with closed‐loop and open‐loop operation. Method of improving the sensorless system stability is proposed.Practical implicationsIn closed‐loop and sensorless control system rotor fault can be diagnosed by using PI output controllers variables. Compensating effect of mechanical variables sets limitation to specified diagnosis methods. Rotor asymmetry affects sensorless control system stability depending on estimator structure.Originality/valueThis paper concentrates upon sensorless control system operation with machine asymmetry and indicates rotor fault symptoms.

INDUCTION MOTOR DRIVE SYSTEM WITH ADAPTIVE FUZZY LOGIC CONTROLLER

Abstract The aim of this paper is to present a control system for a squirrel cage three-phase induction motor with an adaptive speed controller. The adaptive speed controller is based on fuzzy logic theory and is applied for nonlinear sensorless control. A multiscalar model of induction motor is used for machine control, while an adaptive fuzzy controller is supposed to provide better machine response for different operating points than the conventional PI one. A comparative study of Fuzzy based controller with the PI type of controller is done. Simulation and experimental results are provided to validate the proposed concept.

Properties of sensorless control systems based on multiscalar models of the induction motor

PurposeTo develop general forms of multiscalar models of the induction motor and to present properties of the sensorless control systems based on such models.Design/methodology/approachPreviously presented multiscalar model of the induction motor based on a stator current and rotor flux vector is generalized as a model of type 1. New model of type 2 is defined for stator current and the vector which is directly controlled by a voltage vector. The above models are applied in a sensorless control system with speed observer. Dynamical properties of the sensorless control systems are investigated by simulations and experiments.FindingsApplication of the multiscalar model of type 2 results in higher exactness of sensorless control system than application of the multiscalar model of type 1. Controlled variables are more smooth in transients.Research limitations/implicationsThis is not an analytical proof of stability of the control systems.Practical implicationsProvides very useful information for development of sensorless control systems for the induction motor.Originality/valueThis paper extends the known method of nonlinear control of the induction motor to the general form. It is possible to choose the sensorless control system of better properties than those used so far.

MULTISCALAR MODEL OF RURAL HOUSEHOLDS AND COMMUNITIES IN LATE CLASSIC COPAN MAYA SOCIETY

A variety of models contribute to our understanding of Classic Maya sociopolitical structure. Few, however, consider the variability that existed within Maya systems, and the temporal and spatial scales of analysis have often been limited, especially with respect to the commoner segment of society. One model that has focused attention on this component of the Maya is thesian otot, described by Charles Wisdom (1940The Chorti Indians of Guatemala. University of Chicago Press) and introduced for the Copan Maya by William Fash (1983 Deducing Social Organization from Classic Maya Settlement Patterns: A Case Study from the Copan Valley. InCivilization in the Ancient Americas: Essays in Honor of Gordon R. Willey. University of New Mexico Press and Peabody Museum of Archaeology and Ethnology, Harvard University). Based on data from a 135-km2regional settlement survey and excavations of the Copan Valley in Honduras, it is argued that this model, in conjunction with other, broader models of Classic Maya society, offers a useful perspective from which to construct a multiscalar model of ancient Copan social organization. The variability amongsian otot, particularly in terms of economic production, is considered. The ceramic data from Copan suggest that ceramic production among commoner units was communal, and the possibility for community cooperatives is raised. Finally, the dynamic scale and productive relations among the commoners are considered in light of broader sociopolitical changes in the processual history of the Copan polity. It is concluded that the intersection of social, political, and economic institutional frameworks needs to be more comprehensively investigated from varied scales, both temporal and settlement, to appreciate fully the diversity of Maya social organization during the Late Classic/Terminal Classic transition.

Multiscalar processors

Multiscalar processors use a new, aggressive implementation paradigm for extracting large quantities of instruction level parallelism from ordinary high level language programs. A single program is divided into a collection of tasks by a combination of software and hardware. The tasks are distributed to a number of parallel processing units which reside within a processor complex. Each of these units fetches and executes instructions belonging to its assigned task. The appearance of a single logical register file is maintained with a copy in each parallel processing unit. Register results are dynamically routed among the many parallel processing units with the help of compiler-generated masks. Memory accesses may occur speculatively without knowledge of preceding loads or stores. Addresses are disambiguated dynamically, many in parallel, and processing waits only for true data dependences.This paper presents the philosophy of the multiscalar paradigm, the structure of multiscalar programs, and the hardware architecture of a multiscalar processor. The paper also discusses performance issues in the multiscalar model, and compares the multiscalar paradigm with other paradigms. Experimental results evaluating the performance of a sample of multiscalar organizations are also presented.

Nonlinear Feedback and Control Strategy of the Induction Motor

Abstract A mathematical model of the induction motor is analyzed using the Lagrange function. The number of degrees of freedom is reduced by introducing the equations of constrains. One of the equations of constrains results directly from the form of the Lagrange function for the vector components. Hew variables are introduced for which nonlinear differential equations are derived. It is shown that further transformation of the variables leads to partial linearization of the drive system with the induction motor. The multiscalar model of thee induction motor is received. The nonlinear feedback decouples the drive system into two subsystem. Control strategies with the constant and variable rotor flux are investigated using simulation method. An influence of nonlinear feedback on dynamic properties of the system with these strategies is presented.

Control Systems of Doubly Fed Induction Machine Based on Multiscalar Model

A new multiscalar model of the induction motor developed in recent years is used for control system synthesis of a doubly-fed induction machine (DFM). Scalar and vector products of the stator flux and rotor current vectors and square of the stator flux vector are chosen as new variables. Differential equations of the DFM for the chosen variables are received and steady state analysis is made. A control system with a nonlinear feedback based on the proposed model is synthesised. Stability problem appearing in the proposed system is analised and the same problem in a system based on vector methods is pointed out. For stabilization of the motor torque better results are received in the proposed system.