Regulating Robo Advice Across the Financial Services Industry

Automated financial product advisors – “robo advisors” – are emerging across the financial services industry, helping consumers choose investments, banking products, and insurance policies. Robo advisors have the potential to lower the cost and increase the quality and transparency of financial advice for consumers. But they also pose significant new challenges for regulators who are accustomed to assessing human intermediaries. A well-designed robo advisor will be honest and competent, and it will recommend only suitable products. Because humans design and implement robo advisors, however, honesty, competence, and suitability cannot simply be assumed. Moreover, robo advisors pose new scale risks that are different in kind from that involved in assessing the conduct of thousands of individual actors. This essay identifies the core components of robo advisors, key questions that regulators need to be able to answer about them, and the capacities that regulators need to develop in order to answer those questions. The benefits to developing these capacities almost certainly exceed the costs, because the same returns to scale that make an automated advisor so cost-effective lead to similar returns to scale in assessing the quality of automated advisors

Passage-time statistics of superradiant light pulses from Bose-Einstein condensates

We discuss the passage-time statistics of superradiant light pulses generated during the scattering of laser light from an elongated atomic Bose-Einstein condensate. Focusing on the early-stage of the phenomenon, we analyze the corresponding probability distributions and their scaling behaviour with respect to the threshold photon number and the coupling strength. With respect to these parameters, we find quantities which only vary significantly during the transition between the Kapitza Dirac and the Bragg regimes. A possible connection of the present observations to Brownian motion is also discussed.Comment: Close to the version published in J. Phys.

Dirac Quantization of Two-Dimensional Dilaton Gravity Minimally Coupled to N Massless Scalar Fields

It is shown that the Callan-Giddings-Harvey-Strominger theory on the cylinder can be consistently quantized (using Dirac's approach) without imposing any constraints on the sign of the gravitational coupling constant or the sign (or value) of the cosmological constant. The quantum constraints in terms of the original geometrical variables are also derived

Canonical Equivalence of a Generic 2D Dilaton Gravity Model and a Bosonic String Theory

We show that a canonical tranformation converts, up to a boundary term, a generic 2d dilaton gravity model into a bosonic string theory with a Minkowskian target space.Comment: LaTeX file, 9 pages, no figure

Metallicities of M Dwarf Planet Hosts from Spectral Synthesis

We present the first spectroscopic metallicities of three M dwarfs with known or candidate planetary mass companions. We have analyzed high resolution, high signal-to-noise spectra of these stars which we obtained at McDonald Observatory. Our analysis technique is based on spectral synthesis of atomic and molecular features using recently revised cool-star model atmospheres and spectrum synthesis code. The technique has been shown to yield results consistent with the analyses of solar-type stars and allows measurements of M dwarf [M/H] values to 0.12 dex precision. From our analysis, we find [M/H] = -0.12, -0.32, and -0.33 for GJ 876, GJ 436, and GJ 581 respectively. These three M dwarf planet hosts have sub-solar metallicities, a surprising departure from the trend observed in FGK-type stars. This study is the first part of our ongoing work to determine the metallicities of the M dwarfs included in the McDonald Observatory planet search program.Comment: 13 pages, 2 figures, accepted for publication in ApJ

Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies

Contrast, contours and the confusion effect in dazzle camouflage

‘Motion dazzle camouflage’ is the name for the putative effects of highly conspicuous, often repetitive or complex, patterns on parameters important in prey capture, such as the perception of speed, direction and identity. Research into motion dazzle camouflage is increasing our understanding of the interactions between visual tracking, the confusion effect and defensive coloration. However, there is a paucity of research into the effects of contrast on motion dazzle camouflage: is maximal contrast a prerequisite for effectiveness? If not, this has important implications for our recognition of the phenotype and understanding of the function and mechanisms of potential motion dazzle camouflage patterns. Here we tested human participants' ability to track one moving target among many identical distractors with surface patterns designed to test the influence of these factors. In line with previous evidence, we found that targets with stripes parallel to the object direction of motion were hardest to track. However, reduction in contrast did not significantly influence this result. This finding may bring into question the utility of current definitions of motion dazzle camouflage, and means that some animal patterns, such as aposematic or mimetic stripes, may have previously unrecognized multiple functions

DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity.

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple ([Formula: see text]40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples