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Vanadium-doped quaternary bioactive glass systems 46 SiO2, (24–x/2) Na2O, (24–x/2) CaO, 6P2O5, xV, where x = 0, 0.5, 2.5, 2.8, and 5 mass% of vanadium through the use of V2O5 oxide, were successfully synthesized by the melt-quenching technique. Several physicochemical methods were employed to study the effects of vanadium on the physical, structural, and thermal properties of all doped bioactive glasses 46S6-xV. Density (ρg), molar volume (Vm), oxygen molar volume (VO), and oxygen packing density (OPD) variations were correlated with the decrease in compactness of the vitreous network upon the introduction of 2.8 mass% vanadium. Investigations revealed that the bioactive glass network is less polymerized with an increase in vanadium content up to 2.8 mass%. The thermal characteristics and excess entropy ΔSex of doped bioactive glasses were determined. Calculated thermal stability factors show the high forming ability of elaborated bioactive glass. The obtained results show that the introduction of 2.8 mass% of vanadium on the glass matrix induces a significant decrease in ∆Tg (49 K) and ∆Tf (250 K). Increases in excess entropy confirm that the presence of vanadium leads to a more disordered 46S6 glass matrix. The studied 46S6 glass exhibits better thermal properties when vanadium is incorporated, making it more useful for various industrial and technological applications. [ABSTRACT FROM AUTHOR]

Ever since the discovery of graphene sheets and carbon nanotubes (CNT) nearly seven decades ago, their potential applications have grown manifold; such ideas now include the construction of cheaper biosensors and nanofiltration devices. It has been observed from previous studies that the water molecules flow through hydrophobic confinement, by maintaining a single chain-like structure or making distinct layers depending upon the nanochannel dimensions. Our previous study reported the anomalous behavior of confined water up to a certain length of the nanotube in the presence of a cosolvent hexafluoro-2-propanol (HFIP). Our current work showcases the interplay between density deviation and the dynamical fluctuations of confined water molecules at different time points along with different length scales of the carbon nanotube in the presence or absence of the aforementioned cosolvent. In this article we elaborate on the effect of cosolvent impurity within hydrophobic confinement of single-walled carbon nanotubes (SWCNT) of variable length scale; through density deviation-based entropic estimation coupled with dynamical fluctuation. The study lends important insight into hydration behavior inside nanoconfinement alongside the non-covalent surface functionalization of CNT. [ABSTRACT FROM AUTHOR]

Long-term memory behavior is one of the most important phenomena that has appeared in the time series analysis. Different from most definitions of second-order properties, an excess entropy approach is developed for stationary time series to classify long-term and short-term memory. A stationary sequence with finite block entropy is long-term memory if its excess entropy is infinite. The simulation results are graphically demonstrated after some theoretical results are simply presented by various stochastic sequences. Such an approach has advantages over the traditional ways that the excess entropy of stationary sequence with finite block entropy is invariant under instantaneous one-to-one transformation, and that it only requires very weak moment conditions rather than second-order moment conditions and thus can be applied to distinguish the LTM behavior of stationary sequences with unbounded second moment (e.g., heavy tail distribution). Finally, several applications on real data are exhibited. [ABSTRACT FROM AUTHOR]

Fluoride (F) is important for enhancing illogical activity of bioceramics. To increase fluoride content of derived Hench bioactive glass (BaG), bioactive fluorosilicate glasses (BaG-F x) were synthesized by using melting method and characterized using different physico-chemical analyses. Fluoride-containing BaGs were synthesized at a temperature of 1350°C. Structural and thermal effect of calcium fluoride (CaF 2) insertion into the glass network in the BaG: SiO 2 –CaO–Na 2 O–P 2 O 5 quaternary system was studied. Indeed, the incorporated amounts of fluorine (CaF 2) (from 5% to 20% by mass) induced significant physico-chemical changes. Through the structural study by X-ray diffraction (XRD), the amorphous character of our fluorosilicate glasses is proven. Infrared (IR) spectroscopy proved the incorporation of fluorine into the glass matrix. In the microstructural framework, we revealed the morphological changes of the glass powders as a function of the CaF 2 content. These results were confirmed by Brunauer, Emmett and Teller (BET) measurements. Through Differential Scanning Calorimetry (DSC) thermal analysis we established the impact of fluoride ions on the structural dynamics and thermodynamic properties of these newly developed bioactive glasses. Accordingly, it was possible for the first time to incorporate as much as 20 wt% of CaF 2 in BaG respecting the conditions of bioactivity and biodegradability required by Hench. After detailed analyses of the transformation entropies of BG-F x as a function of the added CaF 2 content, it can be stated that the intermolecular movements within the fluorosilicate network are more limited as a function of the added CaF 2 amount. This slows down the ion exchange phenomena and subsequently the dissociation of the material in vitro , which can be anticipated to occur after implantation in vivo. [ABSTRACT FROM AUTHOR]

The attainment of true equilibrium conditions is a dynamic process that encompasses a time span. For slow relaxing systems, non-equilibrium steady states can often look like equilibrium states. This is the case of viscoelastic systems, whose properties reflect their thermo-rheological history. After a summary of the seminal woks by Eyring, Adam & Gibbs and Angell, and mention of promising recent approaches that imply updated theoretical and experimental techniques, the paper suggests a simplified approach for aqueous systems, through a modified expression of the chemical potential of water and use of the "dynamic" phase diagram, so far proposed by Slade and Levine. For homogeneous systems (aqueous solutions), an extra term in the expression of the chemical potential accounts for the energy related to the residual strains produced during the thermo-rheological history of the system. This approach allows estimation of the effect of viscosity on the observed freezing point of polymer solutions. For heterogeneous systems (hydrogels, colloidal glasses), changes of the phase boundaries in the phase diagram explain the gel/sol hysteresis and the syneresis process as the result of water exchange between hosting meshes and trapped aqueous solution. Finally, physical hurdles that hinder inter-phase water displacements and/or the access to the headspace of the system can lead to the coexistence of aqueous phases with different aW within the same heterogeneous system. [ABSTRACT FROM AUTHOR]

We measured the shear viscosity of 14 metallic glasses (MGs) differing with their mixing entropy Δ S mix. It is found that the viscosity at the glass transition temperature T g significantly increases with Δ S mix. Using calorimetric data, we calculated the excess entropy Δ S of all MGs with respect to their maternal crystalline states as a function of temperature. It is shown that the excess entropy Δ S both at room temperature and at T g decreases with Δ S mix. It is concluded that glasses with 'high mixing entropy' Δ S mix correspond to MGs with low excess entropy Δ S. The origin of the increased shear viscosity at T g of glasses with high Δ S mix is determined by their reduced excess entropy Δ S. • Shear viscosity of 14 metallic glasses differing by the mixing entropy is measured. • Glasses with higher mixing entropy have higher viscosity at Tg. • Using calorimetric data, the excess entropy is determined. • Glasses with higher excess entropy have lower viscosity at Tg. • "High entropy glasses" are glasses with reduced excess entropy. [ABSTRACT FROM AUTHOR]

The paper discusses density and molar volume of liquid alloys of iron with C, B, Si, P, Cu, Al, Ni, Cr and Mn. Liquid alloys of iron with other metals are considered as substitutional solutions using the hard-sphere model. Deviations of molar volumes of Fe-Cu and Fe-Al alloys from the ideal solutions were analysed using relationship between excess volume and entropy. Alloys of iron with Ni, Cr and Mn are close to the ideal solutions. Calculated volumes are in agreement with experimental data. Alloys of Fe with C, B, Si and P are considered as interstitial solutions using P. Gaskell's model developed for amorphous alloys of transition metals with metalloids. Calculated partial molar volumes of C, B, Si and P in dilute binary solutions at 1823 K are (cm3/mol): 1.59, 3.37, 7.06 and 6.26 respectively. The model correctly describes the liquid alloys of iron with metalloids as interstitial solutions. [ABSTRACT FROM AUTHOR]

We introduce the minimal maximally predictive models (ϵ-machines) of processes generated by certain hidden semi-Markov models. Their causal states are either discrete, mixed, or continuous random variables and causal-state transitions are described by partial differential equations. As an application, we present a complete analysis of the ϵ-machines of continuous-time renewal processes. This leads to closed-form expressions for their entropy rate, statistical complexity, excess entropy, and differential information anatomy rates.

Identifying and quantifying memory are often critical steps in developing a mechanistic understanding of stochastic processes. These are particularly challenging and necessary when exploring processes that exhibit long-range correlations. The most common signatures employed rely on second-order temporal statistics and lead, for example, to identifying long memory in processes with power-law autocorrelation function and Hurst exponent greater than 1/2. However, most stochastic processes hide their memory in higher-order temporal correlations. Information measures - specifically, divergences in the mutual information between a process' past and future (excess entropy) and minimal predictive memory stored in a process' causal states (statistical complexity) - provide a different way to identify long memory in processes with higher-order temporal correlations. However, there are no ergodic stationary processes with infinite excess entropy for which information measures have been compared to autocorrelation functions and Hurst exponents. Here, we show that fractal renewal processes - those with interevent distribution tails ∝t-α - exhibit long memory via a phase transition at α=1. Excess entropy diverges only there and statistical complexity diverges there and for all α

We give exact formulae for a wide family of complexity measures that capture the organization of hidden nonlinear processes. The spectral decomposition of operator-valued functions leads to closed-form expressions involving the full eigenvalue spectrum of the mixed-state presentation of a process's ε-machine causal-state dynamic. Measures include correlation functions, power spectra, past-future mutual information, transient and synchronization informations, and many others. As a result, a direct and complete analysis of intrinsic computation is now available for the temporal organization of finitary hidden Markov models and nonlinear dynamical systems with generating partitions and for the spatial organization in one-dimensional systems, including spin systems, cellular automata, and complex materials via chaotic crystallography.

In the present investigation, an attempt has been made to evaluate internal pressure (Pi), energy (ΔEvap), and enthalpy of vaporization (ΔHvap) along with excess entropy (SE) and excess isothermal compressibility (βTE) for binary solutions of alkanones (2-propanone, 2-butanone, and 2-heptanone) and aromatic amines (aniline, N-methylaniline, and pyridine) at 293.15, 298.15, and 303.15 K, respectively. The cohesive energy density (CED) and solubility parameter (δ) are studied to understand the strength of molecular interactions. The coefficient of thermal expansion (α) and isothermal compressibility (βT) have also been investigated using empirical equations and have been employed to understand the molecular interactions. All the evaluated properties have been used to understand the nature and extent of intermolecular interactions taking place. The observed trends in the properties and their variations have been discussed in terms of varying chain lengths of the alkyl group and the hydrogen bonding capability of the components. The findings show that the extent of interactions follows an order: aniline > NMA > pyridine, keeping the alkanone constant at all the temperatures under study.

The heat capacity, Cp, of synthetic hydroxyapatite [Ca5(PO4)3OH–OH-Ap], as well as of ten compositions along the OH-Ap-chlorapatite (Cl-Ap) join and 12 compositions along the OH-Ap-fluorapatite (F-Ap) join have been measured using relaxation calorimetry (heat capacity option of the Physical Properties Measurement System—PPMS) and differential scanning calorimetry (DSC) in the temperature range of 5–764 K. Apatites along the Cl-OH and F-OH joins were synthesized at 1100 °C and 300 MPa in an internally heated gas pressure vessel via an exchange process between synthetic fluorapatite or chlorapatite crystals (200–500 μm size) and a series of Ca(OH)2-H2O solutions with specific compositions and amounts relative to the starting apatite. The standard third-law entropy of OH-Ap, derived from the low-temperature heat capacity measurements, is S° = 386.3 ± 2.5 J mol−1 K−1, which is ~ 1% lower than that resulting from low-temperature adiabatic calorimetry data on OH-Ap from the 1950's. The heat capacity of OH-Ap above 298.15 K shows a hump-shaped anomaly centred around 442 K. Based on published structural and calorimetric work, this feature is interpreted to result from a monoclinic to hexagonal phase transition. Super ambient Cp up to this transition can be represented by the polynomial: C p OH - Ap 298 K - 442 K J mol - 1 K - 1 = 1013.7 - 13735.5 T - 0.5 + 2.616718 10 7 T - 2 - 3.551381 10 9 T - 3. . The DSC data above this transition were combined with heat capacities computed using density functional theory and can be given by the Cp polynomial: C p OH - Ap > 442 K J mol - 1 K - 1 = 877.2 - 11393.7 T - 0.5 + 5.452030 10 7 T - 2 - 1.394125 10 10 T - 3 . Positive excess heat capacities of mixing, ∆Cpex, in the order of 1–2 J mol−1 K−1, occur in both solid solutions at around 70 K. They are significant at these conditions exceeding the 2σ-uncertainty of the data. This positive ∆Cpex is compensated by a negative ∆Cpex of the same order at around 250 K in both binaries. At higher temperatures (up to 1200 K), ∆Cpex is zero within error for all solid solution members. As a consequence, the calorimetric entropies, Scal, show no deviation from ideal mixing behaviour within a 2σ-uncertainty for both joins. Excess entropies of mixing, ∆Sex, are thus zero for the OH-Ap–F-Ap, as well as for the OH-Ap–Cl-Ap join. The Cp–T behaviour of the OH-Ap endmember is discussed in relation to that of the F- and Cl-endmembers. [ABSTRACT FROM AUTHOR]

The mutual information between stimulus and spike-train response is commonly used to monitor neural coding efficiency, but neuronal computation broadly conceived requires more refined and targeted information measures of input-output joint processes. A first step toward that larger goal is to develop information measures for individual output processes, including information generation (entropy rate), stored information (statistical complexity), predictable information (excess entropy), and active information accumulation (bound information rate). We calculate these for spike trains generated by a variety of noise-driven integrate-and-fire neurons as a function of time resolution and for alternating renewal processes. We show that their time-resolution dependence reveals coarse-grained structural properties of interspike interval statistics; e.g., τ-entropy rates that diverge less quickly than the firing rate indicated by interspike interval correlations. We also find evidence that the excess entropy and regularized statistical complexity of different types of integrate-and-fire neurons are universal in the continuous-time limit in the sense that they do not depend on mechanism details. This suggests a surprising simplicity in the spike trains generated by these model neurons. Interestingly, neurons with gamma-distributed ISIs and neurons whose spike trains are alternating renewal processes do not fall into the same universality class. These results lead to two conclusions. First, the dependence of information measures on time resolution reveals mechanistic details about spike train generation. Second, information measures can be used as model selection tools for analyzing spike train processes.

We present two examples of finite-alphabet, infinite excess entropy processes generated by stationary hidden Markov models (HMMs) with countable state sets. The first, simpler example is not ergodic, but the second is. These are the first explicit constructions of processes of this type. © 2014 by the authors.

When stressed sufficiently, solid materials yield and deform plastically via reorganization of microscopic constituents. Indeed, it is possible to alter the microstructure of materials by judicious application of stress, an empirical process utilized in practice to enhance the mechanical properties of metals. Understanding the interdependence of plastic flow and microscopic structure in these nonequilibrium states, however, remains a major challenge. Here, we experimentally investigate this relationship, between the relaxation dynamics and microscopic structure of disordered colloidal solids during plastic deformation. We apply oscillatory shear to solid colloidal monolayers and study their particle trajectories as a function of shear rate in the plastic regime. Under these circumstances, the strain rate, the relaxation rate associated with plastic flow, and the sample microscopic structure oscillate together, but with different phases. Interestingly, the experiments reveal that the relaxation rate associated with plastic flow at time t is correlated with the strain rate and sample microscopic structure measured at earlier and later times, respectively. The relaxation rate, in this nonstationary condition, exhibits power-law, shear-thinning behavior and scales exponentially with sample excess entropy. Thus, measurement of sample static structure (excess entropy) provides insight about both strain rate and constituent rearrangement dynamics in the sample at earlier times. [ABSTRACT FROM AUTHOR]

The transport properties of soft particle glasses, such as dynamic viscosity, normal stress coefficients, and shear-induced diffusivity of its particles, are determined by the microstructure of the suspension under flow. A thermodynamic measure of the microstructure is the excess entropy, which we show here accurately correlates the transport properties of soft particle glasses onto master curves across a wide range of volume fractions, suspending fluid viscosities, particle moduli, and shear rates. The excess entropy for soft particle glasses is approximated with the two-body excess entropy computed from the pair distribution function extracted from dynamic simulations. The shear viscosity and normal stress functions diverge and the diffusivity vanishes at a critical excess entropy, corresponding to the yield stress of the suspension. An effective temperature is computed and is found to vary linearly with the shear stress and the elastic energy of the sheared soft particle glass. From this, an equation of state is derived relating the excess entropy to the shear stress. Consequently, three of the four transport properties are determined from the measurement of just one. Finally, a single master curve of particle diffusivity versus excess entropy is presented that unifies observations for both equilibrium and nonequilibrium suspensions. [ABSTRACT FROM AUTHOR]

We introduce an ambidextrous view of stochastic dynamical systems, comparing their forward-time and reverse-time representations and then integrating them into a single time-symmetric representation. The perspective is useful theoretically, computationally, and conceptually. Mathematically, we prove that the excess entropy—a familiar measure of organization in complex systems—is the mutual information not only between the past and future, but also between the predictive and retrodictive causal states. Practically, we exploit the connection between prediction and retrodiction to directly calculate the excess entropy. Conceptually, these lead one to discover new system measures for stochastic dynamical systems: crypticity (information accessibility) and causal irreversibility. Ultimately, we introduce a time-symmetric representation that unifies all of these quantities, compressing the two directional representations into one. The resulting compression offers a new conception of the amount of information stored in the present.

60 years ago, Grant Wilson proposed the first successful activity coefficient model based on the local composition concept he introduced. The model has received wide acceptance and extensive applicability as it could represent accurately the vapor-liquid equilibria of complex mixtures. It could be readily extended to multicomponent systems without additional parameters and with good results. It has not dominated the chemical engineering practice compared to models proposed a few years after (NRTL and UNIQUAC) possibly due to one important shortcoming. The Wilson equation could never represent liquid-liquid equilibria no matter the values of the model's parameters. While this is well-established, the "physical" reasons behind this deficiency had not been fully explored. This work presents and explores the secret of the Wilson equation related to its ability to predict partial miscibility. It will be established that the capabilities of the Wilson model are possibly broader compared to what was originally thought. The presentation is also inspired by several discussions with professor Michael L. Michelsen over the years which are also cited in the manuscript. [ABSTRACT FROM AUTHOR]

It is possible to obtain (excess) interfacial entropies from the temperature dependence of some characteristic surface parameter. Such excess entropies contain much valuable information. Their studies lead to deeper insight into the interfacial properties. In some cases, quite unexpected results are obtained. In the present paper, we shall consider three illustrations: (1) the surface excess entropy of the electrical double layer on silver iodide, (2) the surface excess entropy of the interface between air and electrolyte solutions and (3) the surface excess entropy of Langmuir polymeric monolayers. Their analysis starts with defining this characteristic parameter and measuring its temperature dependence, followed by a brief thermodynamic analysis to obtain the sought entropy. Given the generality of this methodology, its applicability is likely to be extended to a variety of other interfacial properties, in particular when competition between electric and non-electric forces plays a role as in self-assembly, hydrophobic bonding and polyelectrolytes. [ABSTRACT FROM AUTHOR]

The increased excess entropy in face-centered-cubic high entropy alloys is confirmed by quantitatively measuring heat capacities of pure Ni together with equiatomic NiCo, NiCoCr, and NiCoFeCr alloys with increasing configurational entropy. Surprisingly, the incredible excess entropy in the NiCoFeCr alloy can be even up to 0.9R, much larger than that in traditional alloys. The temperature-dependent measurement of the excess entropy indicates the major contribution of lattice vibrations. The excess magnetic entropy dominates in the temperature of 300 to 1000 K. The abnormal excess entropy reveals extraordinary lattice dynamic effects in high entropy alloys, which is a new feature in these alloys. The significant excess entropy at lower temperatures and their subtle shifts at high temperatures. Unlabelled Image [ABSTRACT FROM AUTHOR]

The complexity of a turbulent wake flow is studied using the excess entropy method. Turbulent complexity originates from the deterministic but unpredictable nature of the governing equation, and the excess entropy method is useful in providing a systematic way to quantify the random and coherent patterns in a flow field using information-per-letter and degree-of-complexity, respectively. In this study, the excess entropy calculated using the transverse velocity component decreases considerably along the stream-wise direction, which is consistent with the fact that large-scale structures dissociate and disappear in the far wake. The flow gradually becomes more random and unpredictable. On the other hand, the excess entropy obtained from the streamwise velocity sequence reveals that the pattern of small-scale structures remains largely unchanged during the flow evolution, even though their intensity becomes weaker. Quantifying the coherence and randomness of turbulence provides a more complete description of a complex flow field. The parameter selection in the complexity evaluation is also discussed in the paper. • Excess entropy provides a new perspective to understand the pattern of turbulence. • This method quantifies both the coherence and randomness of a complex flow. • In the studied flow, the pattern of small-scale structures remains unchanged. • The pattern of large structures change significantly in the streamwise direction. [ABSTRACT FROM AUTHOR]

Using a notion on the excess entropy of glass with respect to the counterpart crystal, we introduce a simple dimensionless order parameter ξ , which changes from ξ → 0 to ξ → 1. The former case corresponds to a strongly disordered liquid-like structure while the latter instance describes a highly ordered crystal-like glass. This approach is applied to 13 metallic and 2 tellurite glasses. We found that ξ is strongly sensitive to structural state and/or chemical composition. This parameter can be also used for a comparison of the order in glasses belonging to different classes and appears to represent a new way of structural order estimate. It is important that the ordering parameter ξ has a strong correlation with the glass-forming ability. [ABSTRACT FROM AUTHOR]

Quantifying behaviors of robots which were generated autonomously from task-independent objective functions is an important prerequisite for objective comparisons of algorithms and movements of animals. The temporal sequence of such a behavior can be considered as a time series and hence complexity measures developed for time series are natural candidates for its quantification. The predictive information and the excess entropy are such complexity measures. They measure the amount of information the past contains about the future and thus quantify the nonrandom structure in the temporal sequence. However, when using these measures for systems with continuous states one has to deal with the fact that their values will depend on the resolution with which the systems states are observed. For deterministic systems both measures will diverge with increasing resolution. We therefore propose a new decomposition of the excess entropy in resolution dependent and resolution independent parts and discuss how they depend on the dimensionality of the dynamics, correlations and the noise level. For the practical estimation we propose to use estimates based on the correlation integral instead of the direct estimation of the mutual information based on next neighbor statistics because the latter allows less control of the scale dependencies. Using our algorithm we are able to show how autonomous learning generates behavior of increasing complexity with increasing learning duration.

Highlights • Zinc induces a decrease of melting temperature. • Addition of zinc in the glass matrix induces a decrease in excess entropy. • Strontium induces an increase of crystallisation temperature. • Addition of strontium in the glass matrix induces an increase in excess entropy. Abstract This research is based on the study of thermal behaviour of bioactive glass in the quaternary system SiO 2 -CaO-Na 2 O-P 2 O 5 doped with metallic elements such as Zn and Sr destined for use as bone biomaterial. It encompasses glass transition temperature, crystallization temperature and melting temperature. This work is based on both determination and comparison of the effects of Zn and Sr on thermal characteristics after their introduction in the glass matrix. Thermal stability and excess entropy of all studied glasses have been calculated. Obtained results highlight the different effects of doping on the glasses thermal behaviour. Most notable effects are the sharp decrease of melting temperature of 10 wt% Zn-doped glass and the increase of crystallization temperature of 10 wt% Sr-doped glass. Furthermore, excess entropy of pure glass increases with addition of Sr and decreases with addition of Zn. [ABSTRACT FROM AUTHOR]

We present two examples of finite-alphabet, infinite excess entropy processes generated by stationary hidden Markov models (HMMs) with countable state sets. The first, simpler example is not ergodic, but the second is. These are the first explicit constructions of processes of this type.

We study the approach towards equilibrium in a dynamic Ising model, the Q2R cellular automaton, with microscopic reversibility and conserved energy for an infinite one-dimensional system. Starting from a low-entropy state with positive magnetisation, we investigate how the system approaches equilibrium characteristics given by statistical mechanics. We show that the magnetisation converges to zero exponentially. The reversibility of the dynamics implies that the entropy density of the microstates is conserved in the time evolution. Still, it appears as if equilibrium, with a higher entropy density is approached. In order to understand this process, we solve the dynamics by formally proving how the information-theoretic characteristics of the microstates develop over time. With this approach we can show that an estimate of the entropy density based on finite length statistics within microstates converges to the equilibrium entropy density. The process behind this apparent entropy increase is a dissipation of correlation information over increasing distances. It is shown that the average information-theoretic correlation length increases linearly in time, being equivalent to a corresponding increase in excess entropy. [ABSTRACT FROM AUTHOR]

In this paper we explore the validity of the Rosenfeld and the Dzugutov relation for the Lennard-Jones (LJ) system, its repulsive counterpart, the WCA system and a network forming liquid, the NTW model. We find that for all the systems both the relations are valid at high temperature regime with an universal exponent close to 0.8. Similar to that observed for the simple liquids, the LJ and the WCA systems show a breakdown of the scaling laws at the low temperature regime. However for the NTW model, which is a simple liquid, these scaling laws are valid even at lower temperature regime similar to that found for ionic melts. Thus we find that the NTW model has mixed characteristics of simple liquids and ionic melts. Our study further reveals a quantitative relationship between the Rosenfeld and the Arrhenius relations. For strong liquids, the validity of the Rosenfeld relation in the low temperature regime is connected to it following the Arrhenius behaviour in that regime. Finally we explore the role of pair entropy and residual multiparticle entropy in the dynamics as a function of fragility of the systems. [ABSTRACT FROM AUTHOR]