Evaluating free flux flow in low-pinning molybdenum-germanium superconducting films

Vortex dynamics in molybdenum-germanium superconducting films were found to well approximate the unpinned free limit even at low driving forces. This provided an opportunity to empirically establish the intrinsic character of free flux flow and to test in detail the validity of theories for this regime beyond the Bardeen-Stephen approximation. Our observations are in good agreement with the mean-field result of time dependent Ginzburg-Landau theory. PACS: 74.25.Sv,74.25.Wx,74.25.Uv,74.25.Op,74.25.F- Keywords: vortices, fluxon, Larkin, Ovchinnikov, upper critical magnetic fieldComment: This is the final revised version of a paper that is currently in press. It is expected to appear in Phys. Rev. B in 201

3D-QSAR studies of checkpoint kinase 1 inhibitors based on molecular docking and CoMFA

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q 2 value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r 2 value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r 2 value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis

Improved cuckoo search based neural network learning algorithms for data classification

Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. These networks can be trained with gradient descent back propagation. The algorithm is not definite in finding the global minimum of the error function since gradient descent may get stuck in local minima, where it may stay indefinitely. Among the conventional methods, some researchers prefer Levenberg-Marquardt (LM) because of its convergence speed and performance. On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. Recently, a novel meta-heuristic search technique called cuckoo search (CS) has gained a great deal of attention from researchers due to its efficient convergence towards optimal solution. But Cuckoo search is prone to less optimal solution during exploration and exploitation process due to large step lengths taken by CS due to Levy flight. It can also be used to improve the balance between exploration and exploitation of CS algorithm, and to increase the chances of the egg’s survival. This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. This exploration and exploitation method followed in the proposed HACPSO algorithm makes it to converge to global optima with more efficiency than the original Cuckoo Search (CS) algorithm. Finally, the proposed CS hybrid variants such as; HACPSO, HACPSO-BP, HACPSO-LM, CSBP, CSLM, CSERN, and CSLMERN are evaluated and compared with conventional Back propagation Neural Network (BPNN), Artificial Bee Colony Neural Network (ABCNN), Artificial Bee Colony Back propagation algorithm (ABC-BP), and Artificial Bee Colony Levenberg-Marquardt algorithm (ABC-LM). Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. Overall from the simulation results, it is realized that the proposed CS based NN algorithms performs better than all other proposed and conventional models in terms of CPU Time, MSE, SD and accuracy

Functional responses of methanogenic archaea to syntrophic growth.

Methanococcus maripaludis grown syntrophically with Desulfovibrio vulgaris was compared with M. maripaludis monocultures grown under hydrogen limitation using transcriptional, proteomic and metabolite analyses. These measurements indicate a decrease in transcript abundance for energy-consuming biosynthetic functions in syntrophically grown M. maripaludis, with an increase in transcript abundance for genes involved in the energy-generating central pathway for methanogenesis. Compared with growth in monoculture under hydrogen limitation, the response of paralogous genes, such as those coding for hydrogenases, often diverged, with transcripts of one variant increasing in relative abundance, whereas the other was little changed or significantly decreased in abundance. A common theme was an apparent increase in transcripts for functions using H(2) directly as reductant, versus those using the reduced deazaflavin (coenzyme F(420)). The greater importance of direct reduction by H(2) was supported by improved syntrophic growth of a deletion mutant in an F(420)-dependent dehydrogenase of M. maripaludis. These data suggest that paralogous genes enable the methanogen to adapt to changing substrate availability, sustaining it under environmental conditions that are often near the thermodynamic threshold for growth. Additionally, the discovery of interspecies alanine transfer adds another metabolic dimension to this environmentally relevant mutualism

Templated Growth of Covalently Bonded Three-Dimensional Carbon Nanotube Networks Originated from Graphene

A template-assisted method that enables the growth of covalently bonded three-dimensional carbon nanotubes (CNTs) originating from graphene at a large scale is demonstrated. Atomic force microscopy-based mechanical tests show that the covalently bonded CNT structure can effectively distribute external loading throughout the network to improve the mechanical strength of the material

Therapeutic effects of CD133 + Exosomes on liver function after stroke in type 2 diabetic mice

BACKGROUND AND PURPOSE: Non-alcoholic fatty liver disease (NAFLD) is known to adversely affect stroke recovery. However, few studies investigate how stroke elicits liver dysfunction, particularly, how stroke in type 2 diabetes mellitus (T2DM) exacerbates progression of NAFLD. In this study, we test whether exosomes harvested from human umbilical cord blood (HUCBC) derived CD133 + cells (CD133 + Exo) improves neuro-cognitive outcome as well as reduces liver dysfunction in T2DM female mice. METHODS: Female, adult non-DM and T2DM mice subjected to stroke presence or absence were considered. T2DM-stroke mice were randomly assigned to receive PBS or Exosome treatment group. CD133 + Exo (20 μg/200 μl PBS, i.v.) was administered once at 3 days after stroke. Evaluation of neurological (mNSS, adhesive removal test) and cognitive function [novel object recognition (NOR) test, odor test] was performed. Mice were sacrificed at 28 days after stroke and brain, liver, and serum were harvested. RESULTS: Stroke induces severe and significant short-term and long-term neurological and cognitive deficits which were worse in T2DM mice compared to non-DM mice. CD133 + Exo treatment of T2DM-stroke mice significantly improved neurological function and cognitive outcome indicated by improved discrimination index in the NOR and odor tests compared to control T2DM-stroke mice. CD133 + Exo treatment of T2DM stroke significantly increased vascular and white matter/axon remodeling in the ischemic brain compared to T2DM-stroke mice. However, there were no differences in the lesion volume between non-DM stroke, T2DM-stroke and CD133 + Exo treated T2DM-stroke mice. In T2DM mice, stroke induced earlier and higher TLR4, NLRP3, and cytokine expression (SAA, IL1β, IL6, TNFα) in the liver compared to heart and kidney, as measured by Western blot. T2DM-stroke mice exhibited worse NAFLD progression with increased liver steatosis, hepatocellular ballooning, fibrosis, serum ALT activity, and higher NAFLD Activity Score compared to T2DM mice and non-DM-stroke mice, while CD133 + Exo treatment significantly attenuated the progression of NAFLD in T2DM stroke mice. CONCLUSION: Treatment of female T2DM-stroke mice with CD133 + Exo significantly reduces the progression of NAFLD/NASH and improves neurological and cognitive function compared to control T2DM-stroke mice

Small and mighty: adaptation of superphylum Patescibacteria to groundwater environment drives their genome simplicity.

BackgroundThe newly defined superphylum Patescibacteria such as Parcubacteria (OD1) and Microgenomates (OP11) has been found to be prevalent in groundwater, sediment, lake, and other aquifer environments. Recently increasing attention has been paid to this diverse superphylum including > 20 candidate phyla (a large part of the candidate phylum radiation, CPR) because it refreshed our view of the tree of life. However, adaptive traits contributing to its prevalence are still not well known.ResultsHere, we investigated the genomic features and metabolic pathways of Patescibacteria in groundwater through genome-resolved metagenomics analysis of > 600 Gbp sequence data. We observed that, while the members of Patescibacteria have reduced genomes (~ 1 Mbp) exclusively, functions essential to growth and reproduction such as genetic information processing were retained. Surprisingly, they have sharply reduced redundant and nonessential functions, including specific metabolic activities and stress response systems. The Patescibacteria have ultra-small cells and simplified membrane structures, including flagellar assembly, transporters, and two-component systems. Despite the lack of CRISPR viral defense, the bacteria may evade predation through deletion of common membrane phage receptors and other alternative strategies, which may explain the low representation of prophage proteins in their genomes and lack of CRISPR. By establishing the linkages between bacterial features and the groundwater environmental conditions, our results provide important insights into the functions and evolution of this CPR group.ConclusionsWe found that Patescibacteria has streamlined many functions while acquiring advantages such as avoiding phage invasion, to adapt to the groundwater environment. The unique features of small genome size, ultra-small cell size, and lacking CRISPR of this large lineage are bringing new understandings on life of Bacteria. Our results provide important insights into the mechanisms for adaptation of the superphylum in the groundwater environments, and demonstrate a case where less is more, and small is mighty

Integration of TESLA and FLUTE over satellite networks

Multicast research has explored the security challenges faced in group communications. Multicast transport and multicast security need to work in close collaboration to realise a multicast service. However, there has been comparatively little work to combine the two technologies. In this paper the authors is presenting an example of partially integrating Timed Efficient Stream Loss-Tolerant Authentication (TESLA) protocol and the File Delivery over Unidirectional Transport (FLUTE) protocol. The security concern raised by the proposed algorithm is analysed for satellite network. The proposed algorithm was implemented on a testbed with multicast tunnel between University of Surrey and University of Aberdeen and the results are presented in this paper