Solar cycle dependence of scaling in solar wind fluctuations

In this review we collate recent results for the statistical scaling properties of fluctuations in the solar wind with a view to synthesizing two descriptions: that of evolving MHD turbulence and that of a scaling signature of coronal origin that passively propagates with the solar wind. The scenario that emerges is that of coexistent signatures which map onto the well known "two component" picture of solar wind magnetic fluctuations. This highlights the need to consider quantities which track Alfvénic fluctuations, and energy and momentum flux densities to obtain a complete description of solar wind fluctuations

Pseudo-nonstationarity in the scaling exponents of finite-interval time series

The accurate estimation of scaling exponents is central in the observational study of scale-invariant phenomena. Natural systems unavoidably provide observations over restricted intervals; consequently, a stationary stochastic process (time series) can yield anomalous time variation in the scaling exponents, suggestive of nonstationarity. The variance in the estimates of scaling exponents computed from an interval of N observations is known for finite variance processes to vary as ~1/N as N for certain statistical estimators; however, the convergence to this behavior will depend on the details of the process, and may be slow. We study the variation in the scaling of second-order moments of the time-series increments with N for a variety of synthetic and “real world” time series, and we find that in particular for heavy tailed processes, for realizable N, one is far from this ~1/N limiting behavior. We propose a semiempirical estimate for the minimum N needed to make a meaningful estimate of the scaling exponents for model stochastic processes and compare these with some “real world” time series

Multi-Spacecraft Measurement of Turbulence within a Magnetic Reconnection Jet

The relationship between magnetic reconnection and plasma turbulence is investigated using multipoint in-situ measurements from the Cluster spacecraft within a high-speed reconnection jet in the terrestrial magnetotail. We show explicitly that work done by electromagnetic fields on the particles, $\mathbf{J}\cdot\mathbf{E}$, has a non-Gaussian distribution and is concentrated in regions of high electric current density. Hence, magnetic energy is converted to kinetic energy in an intermittent manner. Furthermore, we find the higher-order statistics of magnetic field fluctuations generated by reconnection are characterized by multifractal scaling on magnetofluid scales and non-Gaussian global scale invariance on kinetic scales. These observations suggest $\mathbf{J}\cdot\mathbf{E}$ within the reconnection jet has an analogue in fluid-like turbulence theory in that it proceeds via coherent structures generated by an intermittent cascade. This supports the hypothesis that turbulent dissipation is highly nonuniform, and thus these results could have far reaching implications for space and astrophysical plasmas.Comment: 5 pages, 3 figures, submitted to Physical Review Letter

Continuous user authentication featuring keystroke dynamics based on robust recurrent confidence model and ensemble learning approach

User authentication is considered to be an important aspect of any cybersecurity program. However, one-time validation of user’s identity is not strong to provide resilient security throughout the user session. In this aspect, continuous monitoring of session is necessary to ensure that only legitimate user is accessing the system resources for entire session. In this paper, a true continuous user authentication system featuring keystroke dynamics behavioural biometric modality has been proposed and implemented. A novel method of authenticating the user on each action has been presented which decides the legitimacy of current user based on the confidence in the genuineness of each action. The 2-phase methodology, consisting of ensemble learning and robust recurrent confidence model(R-RCM), has been designed which employs a novel perception of two thresholds i.e., alert and final threshold. Proposed methodology classifies each action based on the probability score of ensemble classifier which is afterwards used along with hyperparameters of R-RCM to compute the current confidence in the genuineness of user. System decides if user can continue using the system or not based on new confidence value and final threshold. However, it tends to lock out imposter user more quickly if it reaches the alert threshold. Moreover, system has been validated with two different experimental settings and results are reported in terms of mean average number of genuine actions (ANGA) and average number of imposter actions(ANIA), whereby achieving the lowest mean ANIA with experimental setting II

Eulerian spectral closures for isotropic turbulence using a time-ordered fluctuation-dissipation relation

Procedures for time-ordering the covariance function, as given in a previous paper (K. Kiyani and W.D. McComb Phys. Rev. E 70, 066303 (2004)), are extended and used to show that the response function associated at second order with the Kraichnan-Wyld perturbation series can be determined by a local (in wavenumber) energy balance. These time-ordering procedures also allow the two-time formulation to be reduced to time-independent form by means of exponential approximations and it is verified that the response equation does not have an infra-red divergence at infinite Reynolds number. Lastly, single-time Markovianised closure equations (stated in the previous paper above) are derived and shown to be compatible with the Kolmogorov distribution without the need to introduce an ad hoc constant.Comment: 12 page

Efficient design for smart environment using Raspberry Pi with Blockchain and IoT (BRIoT)

Internet of Things (IoT) is reshaping digital world day by day by integrating several technologies to provide smart services. However, intrinsic features of IoT resulting in a number of challenges, such as decentralization, poor interoperability, privacy, confidentiality, and security vulnerabilities. Several security techniques like encryption, third-party software’s are in use currently to protect users data. Blockchain was initially established for digital crypto currencies with a Proof of Work (PoW) consensus process and the advantage of smart contracts, which enabled distributed trust without the involvement of a third party. Its distributed trust concept paved the way for many other developments, such as the development of new consensus mechanisms such as Proof of Stake (PoS) and Proof of Authority (PoA), which aided in the adoption of Blockchain with low computation machines into sectors such as smart industry and smart transportation. Blockchain implementation in IoT can address the security issue, here we proposed a design using Raspberry Pi as edge node (BRIoT)

Self-similar signature of the active solar corona within the inertial range of solar-wind turbulence

We quantify the scaling of magnetic energy density in the inertial range of solar-wind turbulence seen in situ at 1 AU with respect to solar activity. At solar maximum, when the coronal magnetic field is dynamic and topologically complex, we find self-similar scaling in the solar wind, whereas at solar minimum, when the coronal fields are more ordered, we find multifractality. This quantifies the solar-wind signature that is of direct coronal origin and distinguishes it from that of local MHD turbulence, with quantitative implications for coronal heating of the solar wind

Solar Wind Turbulence and the Role of Ion Instabilities

International audienc

Crystal Structures of Malonyl-Coenzyme A Decarboxylase Provide Insights into Its Catalytic Mechanism and Disease-Causing Mutations

Malonyl-coenzyme A decarboxylase (MCD) is found from bacteria to humans, has important roles in regulating fatty acid metabolism and food intake, and is an attractive target for drug discovery. We report here four crystal structures of MCD from human, Rhodopseudomonas palustris, Agrobacterium vitis, and Cupriavidus metallidurans at up to 2.3 Å resolution. The MCD monomer contains an N-terminal helical domain involved in oligomerization and a C-terminal catalytic domain. The four structures exhibit substantial differences in the organization of the helical domains and, consequently, the oligomeric states and intersubunit interfaces. Unexpectedly, the MCD catalytic domain is structurally homologous to those of the GCN5-related N-acetyltransferase superfamily, especially the curacin A polyketide synthase catalytic module, with a conserved His-Ser/Thr dyad important for catalysis. Our structures, along with mutagenesis and kinetic studies, provide a molecular basis for understanding pathogenic mutations and catalysis, as well as a template for structure-based drug design