Fitting Empirical Fundamental Diagrams of Road Traffic: A Comprehensive Review and Comparison of Models Using an Extensive Data Set

<div>Understanding the inter-relationships between traffic flow, density, and speed through the study of the fundamental diagram of road traffic is critical for traffic modelling and management. Consequently, over the last 85 years, a wealth of models have been developed for its functional form. However, there has been no clear answer as to which model is the most appropriate for observed (i.e. empirical) fundamental diagrams and under which conditions. A lack of data has been partly to blame. Motivated by shortcomings in previous reviews, we first present a comprehensive literature review on modelling the functional form of empirical fundamental diagrams. We then perform fits of 50 previously proposed models to a high quality sample of 10,150 empirical fundamental diagrams pertaining to 25 cities. Comparing the fits using information criteria, we find that the non-parametric Sun model greatly outperforms all of the other models. The Sun model maintains its winning position regardless of road type and congestion level. Our study, the first of its kind when considering the number of models tested and the amount of data used, finally provides a definitive answer to the question ``Which model for the functional form of an empirical fundamental diagram is currently the best?''. The word ``currently'' in this question is key, because previously proposed models adopt an inappropriate Gaussian noise model with constant variance. We advocate that future research should shift focus to exploring more sophisticated noise models. This will lead to an improved understanding of empirical fundamental diagrams and their underlying functional forms.</div><div><br></div><div>Accepted by IEEE Transactions On Intelligent Transportation Systems on 14th Dec 2021<br></div><br>

Equations of State for Hadronic Matter and Mass-Radius Relations of Neutron Stars with Strong Magnetic Fields

Neutron star is an important object for us to verify the equation of state of hadronic matter. For a specific choice of equations of state, mass and radius of a neutron star are determined, for which there are constraints from observations. According to some previous studies, since the strong magnetic field acts as a repulsive force, there is a possibility that neutron stars with strong magnetic fields may have relatively heavier masses than other non-magnetized neutron stars. In this paper, the structure of a neutron star with a strong internal magnetic field is investigated by changing its internal functional form to see how much the neutron star can be massive and also how radius of a neutron star can be within a certain range.

Dynamic generation of power function gradient profiles in a universal microfluidic gradient generator by controlling the inlet flow rates

We report a two-inlet universal microfluidic gradient generator capable of generating gradient profiles of the functional form xp in the same device by controlling only the inlet flow rates. We...

Spurious Correlation Due to Scaling

Scaling is common in empirical accounting research. It is often done to mitigate heteroscedasticity or the influence of firm size on parameter estimates. However, Barth and Clinch conclude that common diagnostic tools are ineffective in detecting various scale effects. Using analytic results and Monte Carlo simulations, we show that common forms of scaling, when misapplied, induce substantial spurious correlation via biased parameter estimates. Researchers, when uncertain about the exact functional form of scale effect, are typically better off dealing with both heteroscedasticity and the influence of larger firms using techniques other than scaling.

New Modified Burr III Distribution, Properties and Applications

In this article, Burr III distribution is proposed with a significantly improved functional form. This new modification has enhanced the flexibility of the classical distribution with the ability to model all shapes of hazard rate function including increasing, decreasing, bathtub, upside-down bathtub, and nearly constant. Some of its elementary properties, such as rth moments, sth incomplete moments, moment generating function, skewness, kurtosis, mode, ith order statistics, and stochastic ordering, are presented in a clear and concise manner. The well-established technique of maximum likelihood is employed to estimate model parameters. Middle-censoring is considered as a modern general scheme of censoring. The efficacy of the proposed model is asserted through three applications consisting of complete and censored samples.

Nonlocal gravity cosmology: An overview

We discuss some main aspects of theories of gravity containing nonlocal terms in view of cosmological applications. In particular, we consider various extensions of general relativity based on geometrical invariants as [Formula: see text], [Formula: see text] and [Formula: see text] gravity where [Formula: see text] is the Ricci curvature scalar, [Formula: see text] is the Gauss–Bonnet topological invariant, [Formula: see text] the torsion scalar and the operator [Formula: see text] gives rise to nonlocality. After selecting their functional form by using Noether symmetries, we find out exact solutions in a cosmological background. It is possible to reduce the dynamics of selected models and to find analytic solutions for the equations of motion. As a general feature of the approach, it is possible to address the accelerated expansion of the Hubble flow at various epochs, in particular the dark energy issues, by taking into account nonlocality corrections to the gravitational Lagrangian. On the other hand, it is possible to search for gravitational nonlocal effects also at astrophysical scales. In this perspective, we search for symmetries of [Formula: see text] gravity also in a spherically symmetric background and constrain the free parameters, Specifically, by taking into account the S2 star orbiting around the Galactic Center SgrA[Formula: see text], it is possible to study how nonlocality affects stellar orbits around such a massive self-gravitating object.

Valorization of Oil Waste for Biodetergent Production Using Serratia Marcescens N2 and Gamma Irradiation Assisted Biorecovery

The aim of the present work is to valorize previously used frying oil and use it as biodetergent. Serratia marscens N2 valorized 20% used oil and 8% cell concentration, the biosurfactant produced was a negatively charged lipopeptide with surface tension of 26.8 mN/m. Gamma radiation was used to obtain the higher yield of the biosurfactant by exposing the cells after growth under optimal conditions to low dose gamma radiation. The results showed that the use of radiation led to an increase in the amount of biosurfactant, and the biorecovery took place in a shorter time than usual. The chemical or functional form of the substance did not change at doses of 500 and 1000 gray, while there was a change in production and chemical and functional form at the dose of 2000 gray. The produced biosurfactant was used before and after irradiation to wash oil soiled cloths, the results showed 87% removal at 60oC under stirring conditions. Skin irritation tests performed on experimental mice showed that the surfactant does not cause any inflammation or red spots. Optical images of cloth patches showed no effect on fabric threads post washing the oil soiled cloth patches with biosurfactant. This study proved that 1) previously used oil can be bioconverted into biosurfactant and 2) the use of low doses gamma radiation results in an increase in biosurfactant yield by creating holes in the bacterial cell wall, which helps to recover more quantities of the biosurfactant without change in its chemical or functional form.

Some Model Assisted Estimators Using Functional Form Calibration Approach

The Model assisted estimators are approximately design unbiased, consistent and provides robustness in the case of large sample sizes. The model assisted estimators result in reduction of the design variance if underlying model reasonably defines the regression relationship. If the model is misspecified, then model assisted estimators might result in an increase of the design variance but remain approximately design unbiased and show robustness against model-misspecification. The well-known model assisted estimators, generalized regression estimators are members of a larger class of calibration estimators. Calibration method generates calibration weights that meet the calibration constraints and have minimum distance from the sampling design weights. By using different distance measures, classical calibration approach generates different calibration estimators but with asymptotically identical properties. The constraint of distance minimization was reduced for studying the properties of calibration estimators by proposing a simple functional form approach. The approach generates calibration weights that prove helpful to control the changes in calibration weights by using different choices of auxiliary variable’s functions. This paper is an extended work on model assisted approach by using functional form of calibration weights. Some new model assisted estimators are considered to get efficient and stabilized regression weights by introducing a control matrix. The asymptotic un-biasedness of the proposed estimators is verified and the expressions for MSE are derived in three different cases. A simulation study is done to compare and evaluate the efficiency of the proposed estimators with some existing model assisted estimators.