Ethnolinguistic data on human origin in Selkup

This paper focuses on interdisciplinary research of an important cultural phenomenon – human origin – based on Selkup language, folklore and culture. Selkups are indigenous peoples of Western Siberia belonging to the Uralic language family and sharing cultural features with their neighbors; for example, Kets, Khanty, Evenks, and Siberian Turks. This research could reveal a significant body of human culture, observe how a language reflects people's cognition, and provide ethnolinguistic data for further comparative studies

Ultrabroadband terahertz conductivity of highly doped ZnO and ITO

The broadband complex conductivities of transparent conducting oxides (TCO), namely aluminum-doped zinc oxide (AZO), gallium-doped zinc oxide (GZO) and tin-doped indium oxide (ITO), were investigated by terahertz time domain spectroscopy (THz-TDS) in the frequency range from 0.5 to 18 THz using air plasma techniques, supplemented by the photoconductive antenna (PCA) method. The complex conductivities were accurately calculated using a thin film extraction algorithm and analyzed in terms of the Drude conductivity model. All the measured TCOs have a scattering time below 15 fs. We find that a phonon response must be included in the description of the broadband properties of AZO and GZO for an accurate extraction of the scattering time in these materials, which is strongly influenced by the zinc oxide phonon resonance tail even in the low frequency part of the spectrum. The conductivity of AZO is found to be more thickness dependent than GZO and ITO, indicating high importance of the surface states for electron dynamics in AZO. Finally, we measure the transmittance of the TCO films from 10 to 200 THz with Fourier transform infrared spectroscopy (FTIR) measurements, thus closing the gap between THz-TDS measurements (0.5-18 THz) and ellipsometry measurements (200-1000 THz). (C)2015 Optical Society of Americ

Optical Properties of Gallium-Doped Zinc Oxide-A Low-Loss Plasmonic Material: First-Principles Theory and Experiment

Searching for better materials for plasmonic and metamaterial applications is an inverse design problem where theoretical studies are necessary. Using basic models of impurity doping in semiconductors, transparent conducting oxides (TCOs) are identified as low-loss plasmonic materials in the near-infrared wavelength range. A more sophisticated theoretical study would help not only to improve the properties of TCOs but also to design further lower-loss materials. In this study, optical functions of one such TCO, gallium-doped zinc oxide (GZO), are studied both experimentally and by first-principles density-functional calculations. Pulsed-laser-deposited GZO films are studied by the x-ray diffraction and generalized spectroscopic ellipsometry. Theoretical studies are performed by the total-energy-minimization method for the equilibrium atomic structure of GZO and random phase approximation with the quasiparticle gap correction. Plasma excitation effects are also included for optical functions. This study identifies mechanisms other than doping, such as alloying effects, that significantly influence the optical properties of GZO films. It also indicates that ultraheavy Ga doping of ZnO results in a new alloy material, rather than just degenerately doped ZnO. This work is the first step to achieve a fundamental understanding of the connection between material, structural, and optical properties of highly doped TCOs to tailor those materials for various plasmonic applications

At risk of being risky: The relationship between "brain age" under emotional states and risk preference.

Developmental differences regarding decision making are often reported in the absence of emotional stimuli and without context, failing to explain why some individuals are more likely to have a greater inclination toward risk. The current study (N=212; 10-25y) examined the influence of emotional context on underlying functional brain connectivity over development and its impact on risk preference. Using functional imaging data in a neutral brain-state we first identify the "brain age" of a given individual then validate it with an independent measure of cortical thickness. We then show, on average, that "brain age" across the group during the teen years has the propensity to look younger in emotional contexts. Further, we show this phenotype (i.e. a younger brain age in emotional contexts) relates to a group mean difference in risk perception - a pattern exemplified greatest in young-adults (ages 18-21). The results are suggestive of a specified functional brain phenotype that relates to being at "risk to be risky.

A comparative study of semiconductor-based plasmonic metamaterials

Recent metamaterial (MM) research faces several problems when using metal-based plasmonic components as building blocks for MMs. The use of conventional metals for MMs is limited by several factors: metals such as gold and silver have high losses in the visible and near-infrared (NIR) ranges and very large negative real permittivity values, and in addition, their optical properties cannot be tuned. These issues that put severe constraints on the device applications of MMs could be overcome if semiconductors are used as plasmonic materials instead of metals. Heavily doped, wide bandgap oxide semiconductors could exhibit both a small negative real permittivity and relatively small losses in the NIR. Heavily doped oxides of zinc and indium were already reported to be good, low loss alternatives to metals in the NIR range. Here, we consider these transparent conducting oxides (TCOs) as alternative plasmonic materials for many specific applications ranging from surface-plasmon-polariton waveguides to MMs with hyperbolic dispersion and epsilon-near-zero (ENZ) materials. We show that TCOs outperform conventional metals for ENZ and other MM-applications in the NIR.Comment: 16 pages, 7 figure

The evolution of submillimetre galaxies: two populations and a redshift cut-off

We explore the epoch dependence of number density and star-formation rate for submillimetre galaxies (SMGs) found at 850 um. The study uses a sample of 38 SMG in the GOODS-N field, for which cross-waveband identifications have been obtained for 35/38 members together with redshift measurements or estimates. A maximum-likelihood analysis is employed, along with the `single-source-survey' technique. We find a diminution in both space density and star formation rate at z > 3, closely mimicking the redshift cut-offs found for QSOs selected in different wavebands. The diminution in redshift is particularly marked, at a significance level too small to measure. The data further suggest, at a significance level of about 0.001, that two separately-evolving populations may be present, with distinct luminosity functions. These results parallel the different evolutionary behaviours of LIRGs and ULIRGs, and represent another manifestation of `cosmic down-sizing', suggesting that differential evolution extends to the most extreme star-forming galaxies.Comment: 12 pages, 11 figures, MNRAS accepted. The new version, as accepted for MNRAS, is substantially revised, with more detail on sample selection as well as extended significance tests of the result

Case Study: Predictive Fairness to Reduce Misdemeanor Recidivism Through Social Service Interventions

The criminal justice system is currently ill-equipped to improve outcomes of individuals who cycle in and out of the system with a series of misdemeanor offenses. Often due to constraints of caseload and poor record linkage, prior interactions with an individual may not be considered when an individual comes back into the system, let alone in a proactive manner through the application of diversion programs. The Los Angeles City Attorney's Office recently created a new Recidivism Reduction and Drug Diversion unit (R2D2) tasked with reducing recidivism in this population. Here we describe a collaboration with this new unit as a case study for the incorporation of predictive equity into machine learning based decision making in a resource-constrained setting. The program seeks to improve outcomes by developing individually-tailored social service interventions (i.e., diversions, conditional plea agreements, stayed sentencing, or other favorable case disposition based on appropriate social service linkage rather than traditional sentencing methods) for individuals likely to experience subsequent interactions with the criminal justice system, a time and resource-intensive undertaking that necessitates an ability to focus resources on individuals most likely to be involved in a future case. Seeking to achieve both efficiency (through predictive accuracy) and equity (improving outcomes in traditionally under-served communities and working to mitigate existing disparities in criminal justice outcomes), we discuss the equity outcomes we seek to achieve, describe the corresponding choice of a metric for measuring predictive fairness in this context, and explore a set of options for balancing equity and efficiency when building and selecting machine learning models in an operational public policy setting.Comment: 12 pages, 4 figures, 1 algorithm. The definitive Version of Record will be published in the proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* '20), January 27-30, 2020, Barcelona, Spai