A statistical study of the performance of the Hakamada-Akasofu-Fry version 2 numerical model in predicting solar shock arrival times at Earth during different phases of solar cycle 23

The performance of the Hakamada Akasofu-Fry, version 2 (HAFv.2) numerical model, which provides predictions of solar shock arrival times at Earth, was subjected to a statistical study to investigate those solar/interplanetary circumstances under which the model performed well/poorly during key phases (rise/maximum/decay) of solar cycle 23. In addition to analyzing elements of the overall data set (584 selected events) associated with particular cycle phases, subsets were formed such that those events making up a particular sub-set showed common characteristics. The statistical significance of the results obtained using the various sets/subsets was generally very low and these results were not significant as compared with the hit by chance rate (50%). This implies a low level of confidence in the predictions of the model with no compelling result encouraging its use. However, the data suggested that the success rates of HAFv.2 were higher when the background solar wind speed at the time of shock initiation was relatively fast. Thus, in scenarios where the background solar wind speed is elevated and the calculated success rate significantly exceeds the rate by chance, the forecasts could provide potential value to the customer. With the composite statistics available for solar cycle 23, the calculated success rate at high solar wind speed, although clearly above 50%, was indicative rather than conclusive. The RMS error estimated for shock arrival times for every cycle phase and for the composite sample was in each case significantly better than would be expected for a random data set. Also, the parameter "Probability of Detection, yes" (PODy) which presents the Proportion of Yes observations that were correctly forecast (i.e. the ratio between the shocks correctly predicted and all the shocks observed), yielded values for the rise/maximum/decay phases of the cycle and using the composite sample of 0.85, 0.64, 0.79 and 0.77, respectively. The statistical results obtained through detailed analysis of the available data provided insights into how changing circumstances on the Sun and in interplanetary space can affect the performance of the model. Since shock arrival predictions are widely utilized in making commercially significant decisions re. protecting space assets, the present detailed archival studies can be useful in future operational decision making during solar cycle 24. It would be of added value in this context to use Briggs-Rupert methodology to estimate the cost to an operator of acting on an incorrect forecast

One- and two-photon activated phototoxicity of conjugated porphyrin dimers with high two-photon absorption cross sections

Two-photon excited photodynamic therapy (PDT) has the potential to provide a highly targeted treatment for neoplastic diseases, as excitation can be pin-pointed to small volumes at the laser focus. In addition, two-photon PDT offers deeper penetration into mammalian tissue due to the longer wavelength of irradiation. Here we report the one-photon and two-photon excited PDT results for a collection of conjugated porphyrin dimers with high two-photon absorption cross sections. These dimers demonstrate high one-photon PDT efficacy against a human ovarian adenocarcinoma cell line (SK-OV-3) and exhibit no significant dark-toxicity at concentrations of up to 20 microM. Their one-photon excited PDT efficiencies, following irradiation at 657 nm, approach that of Visudyne, a drug used clinically for PDT. We investigated and optimised the effect of the photosensitizer concentration, incubation time and the light dose on the PDT efficacy of these dimers. These studies led to the selection of P2C2-NMeI as the most effective porphyrin dimer. We have demonstrated that P2C2-NMeI undergoes a two-photon activated process following excitation at 920 nm (3.6-6.8 mW, 300 fs, 90 MHz) and compared it to Visudyne. We conclude that the in vitro two-photon PDT efficacy of P2C2-NMeI is about twice that of Visudyne. This result highlights the potential of this series of porphyrin dimers for two-photon PDT

Bismuth Doping in Nanostructured Tetrahedrite: Scalable Synthesis and Thermoelectric Performance

In this study, we demonstrate the feasibility of Bi-doped tetrahedrite Cu12Sb4−xBixS13 (x = 0.02–0.20) synthesis in an industrial eccentric vibratory mill using Cu, Sb, Bi and S elemental precursors. High-energy milling was followed by spark plasma sintering. In all the samples, the prevailing content of tetrahedrite Cu12Sb4S13 (71–87%) and famatinite Cu3SbS4 (13–21%), together with small amounts of skinnerite Cu3SbS3, have been detected. The occurrence of the individual Cu-Sb-S phases and oxidation states of bismuth identified as Bi0 and Bi3+ are correlated. The most prominent effect of the simultaneous milling and doping on the thermoelectric properties is a decrease in the total thermal conductivity (κ) with increasing Bi content, in relation with the increasing amount of famatinite and skinnerite contents. The lowest value of κ was achieved for x = 0.2 (1.1 W m−1 K −1 at 675 K). However, this sample also manifests the lowest electrical conductivity σ, combined with relatively unchanged values for the Seebeck coefficient (S) compared with the un-doped sample. Overall, the lowered electrical performances outweigh the benefits from the decrease in thermal conductivity and the resulting figure-of-merit values illustrate a degradation effect of Bi doping on the thermoelectric properties of tetrahedrite in these synthesis conditions

A new phylodynamic model of Mycobacterium bovis transmission in a multi-host system uncovers the role of the unobserved reservoir

Multi-host pathogens are particularly difficult to control, especially when at least one of the hosts acts as a hidden reservoir. Deep sequencing of densely sampled pathogens has the potential to transform this understanding, but requires analytical approaches that jointly consider epidemiological and genetic data to best address this problem. While there has been considerable success in analyses of single species systems, the hidden reservoir problem is relatively under-studied. A well-known exemplar of this problem is bovine Tuberculosis, a disease found in British and Irish cattle caused by Mycobacterium bovis, where the Eurasian badger has long been believed to act as a reservoir but remains of poorly quantified importance except in very specific locations. As a result, the effort that should be directed at controlling disease in badgers is unclear. Here, we analyse densely collected epidemiological and genetic data from a cattle population but do not explicitly consider any data from badgers. We use a simulation modelling approach to show that, in our system, a model that exploits available cattle demographic and herd-to-herd movement data, but only considers the ability of a hidden reservoir to generate pathogen diversity, can be used to choose between different epidemiological scenarios. In our analysis, a model where the reservoir does not generate any diversity but contributes to new infections at a local farm scale are significantly preferred over models which generate diversity and/or spread disease at broader spatial scales. While we cannot directly attribute the role of the reservoir to badgers based on this analysis alone, the result supports the hypothesis that under current cattle control regimes, infected cattle alone cannot sustain M. bovis circulation. Given the observed close phylogenetic relationship for the bacteria taken from cattle and badgers sampled near to each other, the most parsimonious hypothesis is that the reservoir is the infected badger population. More broadly, our approach demonstrates that carefully constructed bespoke models can exploit the combination of genetic and epidemiological data to overcome issues of extreme data bias, and uncover important general characteristics of transmission in multi-host pathogen systems

Evidence for Multiple Polytypes of Semiconducting Boron Carbide (C\u3csub\u3e2\u3c/sub\u3eB\u3csub\u3e10\u3c/sub\u3e) from Electronic Structure

Boron carbides fabricated via plasma enhanced chemical vapor deposition from different isomeric source compounds with the same C2B10H12 closo-icosa- hedral structure result in materials with very different direct (optical) band gaps. This provides compelling evidence for the existence of multiple polytypes of C2B10 boron carbide and is consistent with electron diffraction results

Peroxisome Proliferator Activated Receptor Gamma Controls Mature Brown Adipocyte Inducibility through Glycerol Kinase.

Peroxisome proliferator-activated receptors (PPARs) have been suggested as the master regulators of adipose tissue formation. However, their role in regulating brown fat functionality has not been resolved. To address this question, we generated mice with inducible brown fat-specific deletions of PPARα, β/δ, and γ, respectively. We found that both PPARα and β/δδ are dispensable for brown fat function. In contrast, we could show that ablation of PPARγ in vitro and in vivo led to a reduced thermogenic capacity accompanied by a loss of inducibility by β-adrenergic signaling, as well as a shift from oxidative fatty acid metabolism to glucose utilization. We identified glycerol kinase (Gyk) as a partial mediator of PPARγ function and could show that Gyk expression correlates with brown fat thermogenic capacity in human brown fat biopsies. Thus, Gyk might constitute the link between PPARγ-mediated regulation of brown fat function and activation by β-adrenergic signaling