We address the spectral problem of the formally normal quantum mechanical operator associated with the quantised mirror curve of the toric (almost) del Pezzo Calabi-Yau threefold called local P 2 in the case of complex values of Planck’s constant. We show that the problem can be approached in terms of the Bethe ansatz-type highly transcendental equations.Broadband mid-infrared (B-MIR) thermography using fibre optic waveguides can be critical in real-time imaging in harsh environments such as additive manufacturing, personalised medical diagnosis and therapy. We investigate the polarisation effect on thermal measurements through poly-crystalline fibre bundle employing a simple broadband cross-polarisation configuration experimental set-up. Silver halide poly-crystalline fibres AgCl1-xBrx (0 ≤ x≤1) (AgClBr-PolyC) have very wide transmission bandwidth spanning over the spectral range from 1 µm up to 31 µm FWHM. Moreover, they are non-toxic, non-hygroscopic, with relatively good flexibility, which make them very adequate for spectroscopic and thermal measurements in medical and clinical fields. In this study, we used a fibre bundle composed of seven single AgClBr-PolyC fibres, each with a core diameter of about 300 µm, inserted between two broadband MIR polarisers. A silicon carbide filament source was placed at the entrance of the fibre bundle, while a FLIR thermal camera with a close-up lens was employed to measure the spatial temperature distribution over the fibre-bundle end. Indeed, polarisation dependence of temperature measurements has been clearly observed in which the orientation of temperature extrema (minima and maxima) vary from one fibre to another within the bundle. Moreover, these observations have enabled the classification of AgClBr-PolyC fibres following their polarisation sensitivities by which some fibres are relatively highly sensitive to polarisation with polarisation temperature difference (PTD) that can reach 22.1 ± 2.8 °C, whereas some others show very low PTD values down to 3.1 ± 2.8 °C. Many applications can readily be found based on the advantages of both extreme cases.Synthetic biology, as an engineering approach to biological systems, has the potential to disruptively innovate the development of vaccines, therapeutics, and diagnostics. Data accessibility and differences in data-usage capabilities are important factors in shaping this innovation landscape. In this paper, the data that underpin synthetic biology responses to the COVID-19 pandemic are analyzed as positional information goods-goods whose value depends on exclusivity. The positionality of biological data impacts the ability to guide innovations toward societally preferred goals. From both an ethical and economic point of view, positionality can lead to suboptimal as well as beneficial situations. When aiming for responsible innovation (i.e. embedding societal deliberation in the innovation process), it is important to consider hurdles and facilitators in data access and use. Central governance and knowledge commons provide routes to mitigate the negative effects of data positionality.Silver nanoparticles have a great potential in a broad range of applications such as drug-delivery carriers because of their antiviral and antibacterial properties. In this study, the coating properties of silver nanoparticle (size range of 1.6 nm) with three common anti-malarial drugs, Artemisinin, Artemether, and Artesunate have been studied by using the quantum mechanical and classical atomistic molecular dynamics simulation in order to use as the drug delivery to treat malaria and COVID-19 diseases. The optimized structure, frequencies, charge distribution, and the electrostatic potential maps of the three drug molecules were simulated by using the density functional theory (DFT) at the B3LYP/6-311++g(d,p) level of theory. Then, molecular dynamics simulation was used to study the coating of AgNP with each of these drugs. The affinity of interaction was obtained as Artesunate > Artemether > Artemisinin which is in agreement with the DFT results on the adsorption of drugs on the Ag(111) slab.Mesoporous bioactive glasses (MBGs) are gaining increasing interest in the design of new biomaterials for bone defects treatment. An important research trend to enhance their biological behavior is the inclusion of moderate amounts of oxides with therapeutical action such as CuO. MBGs with composition (85-x)SiO2-10-CaO-5P2O5-xCuO (x = 0, 2.5 or 5 mol-%) were synthesized, investigating the influence of the CuO content and some synthesis parameters in their properties. Two series were developed; first one used HCl as catalyst and chlorides as CaO and CuO precursors, second one, used HNO3 and nitrates. MBGs of chlorides family exhibited calcium/copper phosphate nanoparticles between 10 and 20 nm in size. Selleck BLU-222 Nevertheless, CuO-containing MBGs of nitrates family showed metallic copper nanoparticles larger than 50 nm as well as quicker in vitro bioactive responses. Thus, MBGs of the nitrate series were coated by an apatite-like layer after 24 h soaked in simulated body fluid (SBF) a remarkably short period for a MBG containing 5% of CuO. A model, focused in the location of copper in the glass network, was proposed to relate nanostructure and in vitro behaviour. Moreover, after 24 h soaked in MEM or THB culture media, all the MBGs released therapeutic amounts of Ca2+ and Cu2+ ions. Because the quick bioactive response in SBF, the capacity to host biomolecules in their pores and to release therapeutic concentrations of Ca2+ and Cu2+ ions, MBGs of the nitrate families are proposed as excellent biomaterials for bone regeneration.When the information of many individuals is pooled, the resulting aggregate often is a good predictor of unknown quantities or facts. This aggregate predictor frequently outperforms the forecasts of experts or even the best individual forecast included in the aggregation process (“wisdom of crowds”). However, an appropriate aggregation mechanism is considered crucial to reaping the benefits of a “wise crowd”. Of the many possible ways to aggregate individual forecasts, we compare (uncensored and censored) arithmetic and geometric mean and median, continuous double auction market prices and sealed bid-offer call market prices in a controlled experiment. We use an asymmetric information structure, where participants know different sub-sets of the total information needed to exactly calculate the asset value to be estimated. We find that prices from continuous double auction markets clearly outperform all alternative approaches for aggregating dispersed information and that information lets only the best-informed participants generate excess returns.