Modelica - A Language for Physical System Modeling, Visualization and Interaction

Modelica is an object-oriented language for modeling of large, complex and heterogeneous physical systems. It is suited for multi-domain modeling, for example for modeling of mechatronics including cars, aircrafts and industrial robots which typically consist of mechanical, electrical and hydraulic subsystems as well as control systems. General equations are used for modeling of the physical phenomena, No particular variable needs to be solved for manually. A Modelica tool will have enough information to do that automatically. The language has been designed to allow tools to generate efficient code automatically. The modeling effort is thus reduced considerably since model components can be reused and tedious and error-prone manual manipulations are not needed. The principles of object-oriented modeling and the details of the Modelica language as well as several examples are presented

Circulation of a digital community currency

Circulation is the characteristic feature of successful currency systems, from community currencies to cryptocurrencies to national currencies. In this paper, we propose a network analysis methodology for studying circulation given a system's digital transaction records. This is applied to Sarafu, a digital community currency active in Kenya over a period that saw considerable economic disruption due to the COVID-19 pandemic. Representing Sarafu as a network of monetary flow among the 40,000 users reveals meaningful patterns at multiple scales. Circulation was highly modular, geographically localized, and occurring among users with diverse livelihoods. Network centrality highlights women's participation, early adopters, and the especially prominent role of community-based financial institutions. These findings have concrete implications for humanitarian and development policy, helping articulate when community currencies might best support interventions in marginalized areas. Overall, networks of monetary flow allow for studying circulation within digital currency systems at a striking level of detail

Inverse estimation of the transfer velocity of money

Monitoring the money supply is an important prerequisite for conducting sound monetary policy, yet monetary indicators are conventionally estimated in aggregate. This paper proposes a new methodology that is able to leverage micro-level transaction data from real-world payment systems. We apply a novel computational technique to measure the durations for which money is held in individual accounts, and compute the transfer velocity of money from its inverse. Our new definition reduces to existing definitions under conventional assumptions. However, inverse estimation remains suitable for payment systems where the total balance fluctuates and spending patterns change in time. Our method is applied to study Sarafu, a small digital community currency in Kenya, where transaction data is available from 25 January 2020 to 15 June 2021. We find that the transfer velocity of Sarafu was higher than it would seem, in aggregate, because not all units of Sarafu remained in active circulation. Moreover, inverse estimation reveals strong heterogineities and enables comparisons across subgroups of spenders. Some units of Sarafu were held for minutes, others for months, and spending patterns differed across communities using Sarafu. The rate of circulation and the effective balance of Sarafu changed substantially over time, as these communities experienced economic disruptions related to the COVID-19 pandemic and seasonal food insecurity. These findings contribute to a growing body of literature documenting the heterogeneous patterns underlying headline macroeconomic indicators and their relevance for policy. Inverse estimation may be especially useful in studying the response of spenders to targeted monetary operations

Spin effects in transport through non-Fermi liquid quantum dots

The current-voltage characteristic of a one dimensional quantum dot connected via tunnel barriers to interacting leads is calculated in the region of sequential tunneling. The spin of the electrons is taken into account. Non-Fermi liquid correlations implying spin-charge separation are assumed to be present in the dot and in the leads. It is found that the energetic distance of the peaks in the linear conductance shows a spin-induced parity effect at zero temperature T. The temperature dependence of the positions of the peaks depends on the non-Fermi liquid nature of the system. For non-symmetric tunnel barriers negative differential conductances are predicted, which are related to the participation in the transport of collective states in the quantum dot with larger spins. Without spin-charge separation the negative differential conductances do not occur. Taking into account spin relaxation destroys the spin-induced conductance features. The possibility of observing in experiment the predicted effects are briefly discussed.Comment: 15 pages, 16 figures, accepted for publication on Physical Review

Zero-temperature responses of a 3D spin glass in a field

We probe the energy landscape of the 3D Edwards-Anderson spin glass in a magnetic field to test for a spin glass ordering. We find that the spin glass susceptibility is anomalously large on the lattice sizes we can reach. Our data suggest that a transition from the spin glass to the paramagnetic phase takes place at B_c=0.65, though the possibility B_c=0 cannot be excluded. We also discuss the question of the nature of the putative frozen phase.Comment: RevTex, 4 pages, 4 figures, clarifications and added reference

Genetic effects on longitudinal cognitive decline during the early stages of Alzheimer's disease

Cognitive decline in early-stage Alzheimer’s disease (AD) may depend on genetic variability. In the Swedish BioFINDER study, we used polygenic scores (PGS) (for AD, intelligence, and educational attainment) to predict longitudinal cognitive change (measured by mini-mental state examination (MMSE) [primary outcome] and other cognitive tests) over a mean of 4.2 years. We included 260 β-amyloid (Aβ) negative cognitively unimpaired (CU) individuals, 121 Aβ-positive CU (preclinical AD), 50 Aβ-negative mild cognitive impairment (MCI) patients, and 127 Aβ-positive MCI patients (prodromal AD). Statistical significance was determined at Bonferroni corrected p value < 0.05. The PGS for intelligence (beta = 0.1, p = 2.9e−02) was protective against decline in MMSE in CU and MCI participants regardless of Aβ status. The polygenic risk score for AD (beta = − 0.12, p = 9.4e−03) was correlated with the rate of change in MMSE and was partially mediated by Aβ-pathology (mediation effect 20%). There was no effect of education PGS on cognitive measures. Genetic variants associated with intelligence mitigate cognitive decline independent of Aβ-pathology, while effects of genetic variants associated with AD are partly mediated by Aβ-pathology

Back-reaction and effective acceleration in generic LTB dust models

We provide a thorough examination of the conditions for the existence of back-reaction and an "effective" acceleration (in the context of Buchert's averaging formalism) in regular generic spherically symmetric Lemaitre-Tolman-Bondi (LTB) dust models. By considering arbitrary spherical comoving domains, we verify rigorously the fulfillment of these conditions expressed in terms of suitable scalar variables that are evaluated at the boundary of every domain. Effective deceleration necessarily occurs in all domains in: (a) the asymptotic radial range of models converging to a FLRW background, (b) the asymptotic time range of non-vacuum hyperbolic models, (c) LTB self-similar solutions and (d) near a simultaneous big bang. Accelerating domains are proven to exist in the following scenarios: (i) central vacuum regions, (ii) central (non-vacuum) density voids, (iii) the intermediate radial range of models converging to a FLRW background, (iv) the asymptotic radial range of models converging to a Minkowski vacuum and (v) domains near and/or intersecting a non-simultaneous big bang. All these scenarios occur in hyperbolic models with negative averaged and local spatial curvature, though scenarios (iv) and (v) are also possible in low density regions of a class of elliptic models in which local spatial curvature is negative but its average is positive. Rough numerical estimates between -0.003 and -0.5 were found for the effective deceleration parameter. While the existence of accelerating domains cannot be ruled out in models converging to an Einstein de Sitter background and in domains undergoing gravitational collapse, the conditions for this are very restrictive. The results obtained may provide important theoretical clues on the effects of back-reaction and averaging in more general non-spherical models.Comment: Final version accepted for publication in Classical and Quantum Gravity. 47 pages in IOP LaTeX macros, 12 pdf figure

Low-temperature conductivity of quasi-one-dimensional conductors: Luttinger liquid stabilized by impurities

A new non-Fermi-liquid state of quasi-one-dimensional conductors is suggested in which electronic system exists in a form of collection of bounded Luttinger liquids stabilized by impurities. This state is shown to be stable towards interchain electron hopping at low temperatures. Electronic spectrum of the system contains zero modes and collective excitations of the bounded Luttinger liquids in the segments between impurities. Zero modes give rise to randomly distributed localized electronic levels, and long-range interaction generates the Coulomb gap in the density of states at the Fermi energy. Mechanism of conductivity at low temperatures is phonon-assisted hopping via zero-mode states. At higher voltages the excitations of Luttinger liquid are involved in electron transport, and conductivity obeys power-law dependence on voltage. The results provide a qualitative explanation for recent experimental data for NbSe3 and TaS3 crystals.Comment: 12 pages, 1 figur