Direct numerical simulations of optimal thermal convection in rotating plane layer dynamos

The heat transfer behavior of convection-driven dynamos in a rotating plane layer between two parallel plates, heated from below and cooled from the top, is investigated. At a fixed rotation rate (Ekman Number, $E=10^{-6}$) and fluid properties (thermal and magnetic Prandtl numbers, $Pr=Pr_m=1$), both dynamo convection (DC) and non-magnetic rotating convection (RC) simulations are performed to demarcate the effect of magnetic field on heat transport at different thermal forcings (Rayleigh Number, $Ra=3.83\times10^{9}-3.83\times10^{10}$). In this range, our turbulence resolving simulations demonstrate the existence of an optimum thermal forcing, at which heat transfer between the plates in DC exhibits maximum enhancement, as compared to the heat transport in the RC simulations. Unlike any global force balance reported in the literature, the present simulations reveal an increase in the Lorentz force in the \textit{thermal boundary layer}, due to stretching of magnetic field line by the vortices near the walls with no-slip boundary condition. This increase in Lorentz force mitigates turbulence suppression owing to the Coriolis force, resulting in enhanced turbulence and heat transfe

Effects of kinematic and magnetic boundary conditions on the dynamics of convection-driven plane layer dynamos

Rapidly rotating convection-driven dynamos are investigated under different kinematic and magnetic boundary conditions using DNS. At a fixed rotation rate, represented by the Ekman number $E=5\times10^{-7}$, the thermal forcing is varied from 2 to 20 times its value at the onset of convection ($\mathcal{R}=Ra/Ra_c=2-20$), keeping the fluid properties constant ($Pr=Pr_m=1$). The statistical behavior, force balance and heat transport characteristics of the dynamos depend on boundary conditions that dictate both boundary layer and the interior dynamics. At a fixed thermal forcing ($\mathcal{R}=3$), the Ekman plumes in the presence of viscous boundary layers lead to energetic vortices that result in higher enstrophy and kinetic helicity with no-slip boundaries compared to free-slip boundaries. The structure and strength of the magnetic field are also dictated by the boundary conditions. Though the leading order force balance remains geostrophic, Lorentz force dominates inside the thermal boundary layer with no-slip, electrically conducting walls. Here, the Lorentz work term in the turbulent kinetic energy budget is found to have components that exchange energy from the velocity field to the magnetic field, and vice-versa. However, with no-slip, insulated walls, all Lorentz work components perform unidirectional energy transfer to produce magnetic energy from the kinetic energy of the fluid. The heat transfer enhancement in dynamos, compared to non-magnetic rotating convection, exhibits a peak in the range $\mathcal{R}=3-5$. For free-slip conditions, dynamo action may alter the heat transport by suppressing the formation of large-scale vortices. However, the highest heat transfer enhancement occurs when the boundaries are no-slip, electrically conducting walls

Delayed intrinsic activation of an NMDA-independent CaM-kinase II in a critical time window is necessary for late consolidation of an associative memory

Calcium/calmodulin-dependent kinases (CaM-kinases) are central to various forms of long-term memory (LTM) in a number of evolutionarily diverse organisms. However, it is still largely unknown what contributions specific CaM-kinases make to different phases of the same specific type of memory, such as acquisition, or early, intermediate, and late consolidation of associative LTM after classical conditioning. Here, we investigated the involvement of CaM-kinase II (CaMKII) in different phases of associative LTM induced by single-trial reward classical conditioning in Lymnaea, a well established invertebrate experimental system for studying molecular mechanisms of learning and memory. First, by using a general CaM-kinase inhibitor, KN-62, we found that CaM-kinase activation was necessary for acquisition and late consolidation, but not early or intermediate consolidation or retrieval of LTM. Then, we used Western blot-based phosphorylation assays and treatment with CaMKIINtide to identify CaMKII as the main CaM-kinase, the intrinsic activation of which, in a critical time window ( approximately 24 h after learning), is central to late consolidation of LTM. Additionally, using MK-801 and CaMKIINtide we found that acquisition was dependent on both NMDA receptor and CaMKII activation. However, unlike acquisition, CaMKII-dependent late memory consolidation does not require the activation of NMDA receptors. Our new findings support the notion that even apparently stable memory traces may undergo further molecular changes and identify NMDA-independent intrinsic activation of CaMKII as a mechanism underlying this "lingering consolidation." This process may facilitate the preservation of LTM in the face of protein turnover or active molecular processes that underlie forgetting

Heterologous expression and in-vitro analysis of Streptococcus pneumoniae FtsEX divisome complex with peptidoglycan (PG) hydrolase PcsB and actin homologue FtsA, required for PG remodelling and cell separation

Bacterial cell division is orchestrated by the divisome complex of proteins necessary for new peptidoglycan (PG) synthesis and PG remodeling during septum formation and cell separation. These proteins have homologues in both Grampositive and Gram-negative species highlighting their fundamental biological role. The complex between FtsE and FtsX is recruited to the divisome at an early stage in mid-cell division and is required in assembling further downstream divisome proteins as well as in regulating divisome activity. Specifically, it provides a membrane anchor for an extracellular hydrolase that is required for hydrolysis of PG of old cell wall material and to enable separation of daughter cells during division. In our heterologous expression study, we observed aberrant cell division defects in Escherichia coli (Ec) cell when subject to expression of the Streptococcus pneumoniae (Sp) FtsEX mimicking the phenotype of existing antibiotics. This phenotype can be rescued co-overexpressing SpFtsEX with its cognate peptidoglycan hydrolase; PcsB that hydrolyses Escherichia coli PG required for PG remodeling during cell separation. In this study, we have demonstrated Streptococcus pneumoniae FtsEX-FtsA and FtsEX-PcsB complexes can be isolated in-vitro using nanodiscs styrene-maleic-acid-lipid-particles (SMALP), preserving their membrane lipid environment. The protein-protein interaction studies indicate SpFtsX but not SpFtsE, interacts with the essential divisome protein SpFtsA, and PcsB successfully docks with FtsEX in the SMALP disk. Negative stain electron microscopy images and initial high resolution cryo-EM trials with these complexes indicates these tools could be prerequisite for investigating mechanistic insight about their structural-functional relationship and for further inhibitor screens for these complexes

A Simple Flood Forecasting Scheme Using Wireless Sensor Networks

This paper presents a forecasting model designed using WSNs (Wireless Sensor Networks) to predict flood in rivers using simple and fast calculations to provide real-time results and save the lives of people who may be affected by the flood. Our prediction model uses multiple variable robust linear regression which is easy to understand and simple and cost effective in implementation, is speed efficient, but has low resource utilization and yet provides real time predictions with reliable accuracy, thus having features which are desirable in any real world algorithm. Our prediction model is independent of the number of parameters, i.e. any number of parameters may be added or removed based on the on-site requirements. When the water level rises, we represent it using a polynomial whose nature is used to determine if the water level may exceed the flood line in the near future. We compare our work with a contemporary algorithm to demonstrate our improvements over it. Then we present our simulation results for the predicted water level compared to the actual water level.Comment: 16 pages, 4 figures, published in International Journal Of Ad-Hoc, Sensor And Ubiquitous Computing, February 2012; V. seal et al, 'A Simple Flood Forecasting Scheme Using Wireless Sensor Networks', IJASUC, Feb.201

Minimization of Handoff Failure Probability for Next-Generation Wireless Systems

During the past few years, advances in mobile communication theory have enabled the development and deployment of different wireless technologies, complementary to each other. Hence, their integration can realize a unified wireless system that has the best features of the individual networks. Next-Generation Wireless Systems (NGWS) integrate different wireless systems, each of which is optimized for some specific services and coverage area to provide ubiquitous communications to the mobile users. In this paper, we propose to enhance the handoff performance of mobile IP in wireless IP networks by reducing the false handoff probability in the NGWS handoff management protocol. Based on the information of false handoff probability, we analyze its effect on mobile speed and handoff signaling delay.Comment: 16 Page

A generalized curvilinear solver for spherical shell Rayleigh-B\'enard convection

A three-dimensional finite-difference solver has been developed and implemented for Boussinesq convection in a spherical shell. The solver transforms any complex curvilinear domain into an equivalent Cartesian domain using Jacobi transformation and solves the governing equations in the latter. This feature enables the solver to account for the effects of the non-spherical shape of the convective regions of planets and stars. Apart from parallelization using MPI, implicit treatment of the viscous terms using a pipeline alternating direction implicit scheme and HYPRE multigrid accelerator for pressure correction makes the solver efficient for high-fidelity direct numerical simulations. We have performed simulations of Rayleigh-B\'enard convection at three Rayleigh numbers $Ra=10^{5}, 10^{7}$ and $10^{8}$ while keeping the Prandtl number fixed at unity ($Pr=1$). The average radial temperature profile and the Nusselt number match very well, both qualitatively and quantitatively, with the existing literature. Closure of the turbulent kinetic energy budget, apart from the relative magnitude of the grid spacing compared to the local Kolmogorov scales, assures sufficient spatial resolution

A CREB2-targeting microRNA is required for long-term memory after single-trial learning

Although single-trial induced long-term memories (LTM) have been of major interest in neuroscience, how LTM can form after a single episode of learning remains largely unknown. We hypothesized that the removal of molecular inhibitory constraints by microRNAs (miRNAs) plays an important role in this process. To test this hypothesis, first we constructed small non-coding RNA (sncRNA) cDNA libraries from the CNS of Lymnaea stagnalis subjected to a single conditioning trial. Then, by next generation sequencing of these libraries, we identified a specific pool of miRNAs regulated by training. Of these miRNAs, we focussed on Lym-miR-137 whose seed region shows perfect complementarity to a target sequence in the 3’ UTR of the mRNA for CREB2, a well-known memory repressor. We found that Lym-miR-137 was transiently up-regulated 1 h after single-trial conditioning, preceding a down-regulation of Lym-CREB2 mRNA. Furthermore, we discovered that Lym-miR-137 is co-expressed with Lym-CREB2 mRNA in an identified neuron with an established role in LTM. Finally, using an in vivo loss-of-function approach we demonstrated that Lym-miR-137 is required for single-trial induced LTM

Non-Intrusive Uncertainty Quantification for U3Si2 and UO2 Fuels with SiC/SiC Cladding using BISON for Digital Twin-Enabling Technology

U.S. Nuclear Regulatory Committee (NRC) and U.S. Department of Energy (DOE) initiated a future-focused research project to assess the regulatory viability of machine learning (ML) and artificial intelligence (AI)-driven Digital Twins (DTs) for nuclear applications. Advanced accident tolerant fuel (ATF) is one of the priority focus areas of the DOE/ NRC. DTs have the potential to transform the nuclear energy sector in the coming years by incorporating risk-informed decision-making into the Accelerated Fuel Qualification (AFQ) process for ATF. A DT framework can offer game-changing yet practical and informed solutions to the complex problem of qualifying advanced ATFs. However, novel ATF technology suffers from a couple of challenges, such as (i) Data unavailability; (ii) Lack of data, missing data; and (iii) Model uncertainty. These challenges must be resolved to gain the trust in DT framework development. In addition, DT-enabling technologies consist of three major areas: (i) modeling and simulation (M&S), covering uncertainty quantification (UQ), sensitivity analysis (SA), data analytics through ML/AI, physics-based models, and data-informed modeling, (ii) Advanced sensors/instrumentation, and (iii) Data management. UQ and SA are important segments of DT-enabling technologies to ensure trustworthiness, which need to be implemented to meet the DT requirement. Considering the regulatory standpoint of the modeling and simulation (M&S) aspect of DT, UQ and SA are paramount to the success of DT framework in terms of multi-criteria and risk-informed decision-making. In this study, the adaptability of polynomial chaos expansion (PCE) based UQ/SA in a non-intrusive method in BISON was investigated to ensure M&S aspects of the AFQ for ATF. This study introduces the ML-based UQ and SA methods while exhibiting actual applications to the finite element-based nuclear fuel performance code