Superconducting properties of ultrathin Bi2Sr2CaCu2O8+x single crystals

We use Ar-ion milling to thin Bi2212 single crystals down to a few nanometers or one-to-two (CuO2)2 layers. With decreasing the thickness, superconducting transition temperature gradually decreases to zero and the in-plane resistivity increases to large values indicating the existence of a superconductor-insulator transition in ultrathin Bi2212 single crystals.Comment: 17 pages, 6 figures, to appear in J. Appl. Phys. 98(3) 200

Cathodoluminescence-based nanoscopic thermometry in a lanthanide-doped phosphor

Crucial to analyze phenomena as varied as plasmonic hot spots and the spread of cancer in living tissue, nanoscale thermometry is challenging: probes are usually larger than the sample under study, and contact techniques may alter the sample temperature itself. Many photostable nanomaterials whose luminescence is temperature-dependent, such as lanthanide-doped phosphors, have been shown to be good non-contact thermometric sensors when optically excited. Using such nanomaterials, in this work we accomplished the key milestone of enabling far-field thermometry with a spatial resolution that is not diffraction-limited at readout. We explore thermal effects on the cathodoluminescence of lanthanide-doped NaYF$_4$ nanoparticles. Whereas cathodoluminescence from such lanthanide-doped nanomaterials has been previously observed, here we use quantitative features of such emission for the first time towards an application beyond localization. We demonstrate a thermometry scheme that is based on cathodoluminescence lifetime changes as a function of temperature that achieves $\sim$ 30 mK sensitivity in sub-$\mu$m nanoparticle patches. The scheme is robust against spurious effects related to electron beam radiation damage and optical alignment fluctuations. We foresee the potential of single nanoparticles, of sheets of nanoparticles, and also of thin films of lanthanide-doped NaYF$_4$ to yield temperature information via cathodoluminescence changes when in the vicinity of a sample of interest; the phosphor may even protect the sample from direct contact to damaging electron beam radiation. Cathodoluminescence-based thermometry is thus a valuable novel tool towards temperature monitoring at the nanoscale, with broad applications including heat dissipation in miniaturized electronics and biological diagnostics.Comment: Main text: 30 pages + 4 figures; supplementary information: 22 pages + 8 figure

Quantifying the Advantage of Looking Forward

We introduce a future orientation index to quantify the degree to which Internet users worldwide seek more information about years in the future than years in the past. We analyse Google logs and find a striking correlation between the country's GDP and the predisposition of its inhabitants to look forward

Dynamic Exponent of t-J and t-J-W Model

Drude weight of optical conductivity is calculated at zero temperature by exact diagonalization for the two-dimensional t-J model with the two-particle term, $W$. For the ordinary t-J model with $W$=0, the scaling of the Drude weight $D \propto \delta^2$ for small doping concentration $\delta$ is obtained, which indicates anomalous dynamic exponent $z$=4 of the Mott transition. When $W$ is switched on, the dynamic exponent recovers its conventional value $z$=2. This corresponds to an incoherent-to-coherent transition associated with the switching of the two-particle transfer.Comment: LaTeX, JPSJ-style, 4 pages, 5 eps files, to appear in J. Phys. Soc. Jpn. vol.67, No.6 (1998

Final-State-Interaction Simulation of T-Violation in the Top-Quark Semileptonic Decay

The standard electroweak final-state interaction induces a false T-odd correlation in the top-quark semileptonic decay. The correlation parameter is calculated in the standard model and found to be considerably larger than those that could be produced by genuine T-violation effects in a large class of theoretical models.Comment: 14 pages, 1 diagram (not included

A meta-analysis of state-of-the-art electoral prediction from Twitter data

Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightforward and the prevailing view is overly optimistic. This is problematic because while simple approaches are assumed to be good enough, core problems are not addressed. Thus, this paper aims to (1) provide a balanced and critical review of the state of the art; (2) cast light on the presume predictive power of Twitter data; and (3) depict a roadmap to push forward the field. Hence, a scheme to characterize Twitter prediction methods is proposed. It covers every aspect from data collection to performance evaluation, through data processing and vote inference. Using that scheme, prior research is analyzed and organized to explain the main approaches taken up to date but also their weaknesses. This is the first meta-analysis of the whole body of research regarding electoral prediction from Twitter data. It reveals that its presumed predictive power regarding electoral prediction has been rather exaggerated: although social media may provide a glimpse on electoral outcomes current research does not provide strong evidence to support it can replace traditional polls. Finally, future lines of research along with a set of requirements they must fulfill are provided.Comment: 19 pages, 3 table

Does \u2018bigger\u2019mean \u2018better\u2019? Pitfalls and shortcuts associated with big data for social research

\u2018Big data is here to stay.\u2019 This key statement has a double value: is an assumption as well as the reason why a theoretical reflection is needed. Furthermore, Big data is something that is gaining visibility and success in social sciences even, overcoming the division between humanities and computer sciences. In this contribution some considerations on the presence and the certain persistence of Big data as a socio-technical assemblage will be outlined. Therefore, the intriguing opportunities for social research linked to such interaction between practices and technological development will be developed. However, despite a promissory rhetoric, fostered by several scholars since the birth of Big data as a labelled concept, some risks are just around the corner. The claims for the methodological power of bigger and bigger datasets, as well as increasing speed in analysis and data collection, are creating a real hype in social research. Peculiar attention is needed in order to avoid some pitfalls. These risks will be analysed for what concerns the validity of the research results \u2018obtained through Big data. After a pars distruens, this contribution will conclude with a pars construens; assuming the previous critiques, a mixed methods research design approach will be described as a general proposal with the objective of stimulating a debate on the integration of Big data in complex research projecting