California Consortium of Addiction Programs and Professionals

Artificial intelligence (AI) is one of the most important, ground-breaking, and debated technologies of our age that has gained in popularity thanks to the availability of huge amount of data (Big Data), the advances made in algorithmics, and the improvement witnessed in both computing power and storage capability of machines. Although there is a consensus on the disruptive nature of AI, some firms have already adopted this technology while others are still lagging. Conventional wisdom in innovation management posits that perceived barriers prevent organizations from adopting an innovation such as AI-based technologies. However, previous research has yielded mixed results with respect to the relationship between perceived barriers to the adoption of an innovation and its actual adoption. Analyzing data obtained from the European Commission on 7549 firms with a configurational approach based on a combination of hierarchical and non-hierarchical cluster analysis followed by post-hoc analysis, this exploratory study seeks to expand our understanding of AI-based technologies perceived barriers-adoption link. Using 15 variables to measure perceived barriers to the adoption of AI-based technologies, we highlight the complex nature of this relationship that echoes the inconsistent findings of previous studies. We identify three clusters of firms that face different configurations of perceived barriers while exhibiting orthogonality on all 15 perceived barriers to AI-based technologies adoption (cluster I – High Level perceived barriers, n=2249, 32.4%; Cluster II- Low Level perceived barriers, n=1879, 24.9%; Cluster III -Moderate Level barriers, n=3221, 42.7%). Among the three configurational solutions, two exhibit asymmetrical relationships between the causal conditions (configuration of perceived barriers) and the outcome (AI-based technologies adoption intensity).

A quadruply lensed source, J125856.3-031944, has been discovered using the DELVE survey and WISE W1 - W2 colors. Followup direct imaging carried out with the Magellan Baade 6.5 m telescope is analyzed, as is spectroscopy from the 2.5 m Nordic Optical Telescope. The lensed image configuration is kite-like, with the major axis of the lensing galaxy along the symmetry axis of the kite, and with the faintest image at its tail. Redward of 6000 AA the tail image is strongly blended with the lensing galaxy. The Sloan g direct imaging carried out with Magellan permits deblending. As the lensed image configuration is nearly circular, simple models give high predicted magnifications for all four images. The source's narrow emission lines at redshift z=2.225 and low intrinsic luminosity qualify it as a Type 2 AGN. The Magellan image shows a substantial residual that suggests a second lensing galaxy.

The next Milky Way supernova will be an epochal event in multi-messenger astronomy, critical to tests of supernovae, neutrinos, and new physics. Realizing this potential depends on having realistic simulations of core collapse. We investigate the neutrino predictions of nearly all modern models (1-, 2-, and 3-d) over the first $\simeq$1 s, making the first detailed comparisons of these models to each other and to the SN 1987A neutrino data. Even with different methods and inputs, the models generally agree with each other. However, even considering the low neutrino counts, the models generally disagree with data. What can cause this? We show that neither neutrino oscillations nor different progenitor masses appear to be a sufficient solution. We outline urgently needed work.

(Abridged) The origin of dSphs in the Local Group (LG) remains an enigma. The tidal stirring model posits that late-type, rotationally-supported dwarfs resembling present-day dwarf irregular (dIrr) galaxies can transform into dSphs via interactions with Milky Way-sized hosts. Using collisionless N-body simulations, we investigate for the first time how tidal stirring depends on the dark matter (DM) density distribution in the central stellar region of the progenitor disky dwarf. Specifically, we explore various asymptotic inner slopes gamma of the dwarf DM density profiles (rho \propto r^{-gamma} as r -> 0). For a given orbit inside the primary, rotationally-supported dwarfs embedded in DM halos with core-like density distributions (gamma = 0.2) and mild density cusps (gamma = 0.6) demonstrate a substantially enhanced likelihood and efficiency of transformation into dSphs compared to their counterparts with steeper DM density profiles (gamma = 1). Such shallow DM distributions are akin to those of observed dIrrs, highlighting tidal stirring as a plausible model for the LG morphology-density relation. When gamma <1, a single pericentric passage can induce dSph formation and disky dwarfs on low-eccentricity or large-pericenter orbits are able to transform into dSphs; these new results allow the tidal stirring model to explain the existence of virtually all known dSphs across a wide range of distances from their hosts. A subset of rotationally-supported dwarfs with gamma <1 are eventually disrupted by the primary; those that survive as dSphs are generally on orbits that are biased towards lower eccentricities and/or larger pericenters relative to those of typical CDM satellites. The latter could explain the rather peculiar orbits of several classic LG dSphs such as Fornax, Leo I, Tucana, and Cetus.

We identify a "supernova rate problem": the measured cosmic core-collapse supernova rate is a factor of ~ 2 smaller (with significance ~ 2 sigma) than that predicted from the measured cosmic massive-star formation rate. The comparison is critical for topics from galaxy evolution and enrichment to the abundance of neutron stars and black holes. We systematically explore possible resolutions. The accuracy and precision of the star formation rate data and conversion to the supernova rate are well supported, and proposed changes would have far-reaching consequences. The dominant effect is likely that many supernovae are missed because they are either optically dim (low-luminosity) or dark, whether intrinsically or due to obscuration. We investigate supernovae too dim to have been discovered in cosmic surveys by a detailed study of all supernova discoveries in the local volume. If possible supernova impostors are included, then dim supernovae are common enough by fraction to solve the supernova rate problem. If they are not included, then the rate of dark core collapses is likely substantial. Other alternatives are that there are surprising changes in our understanding of star formation or supernova rates, including that supernovae form differently in small galaxies than in normal galaxies. These possibilities can be distinguished by upcoming supernova surveys, star formation measurements, searches for disappearing massive stars, and measurements of supernova neutrinos.

Most proposed dark matter candidates are stable and are produced thermally in the early Universe. However, there is also the possibility of unstable (but long-lived) dark matter, produced thermally or otherwise. We propose a strategy to distinguish between dark matter annihilation and/or decay in the case that a clear signal is detected in gamma-ray observations of Milky Way dwarf spheroidal galaxies with gamma-ray experiments. The sole measurement of the energy spectrum of an indirect signal would render the discrimination between these cases impossible. We show that by examining the dependence of the intensity and energy spectrum on the angular distribution of the emission, the origin could be identified as decay, annihilation, or both. In addition, once the type of signal is established, we show how these measurements could help to extract information about the dark matter properties, including mass, annihilation cross section, lifetime, dominant annihilation and decay channels, and the presence of substructure. Although an application of the approach presented here would likely be feasible with current experiments only for very optimistic dark matter scenarios, the improved sensitivity of upcoming experiments could enable this technique to be used to study a wider range of dark matter models.

The recent detection of secondary CMB anisotropy by the South Pole Telescope places a conservative bound on temperature fluctuations from the optical depth-modulated Doppler effect of T_{3000} < sqrt{13} microK at multipoles l~3000. This bound is the first empirical constraint on reionization optical depth fluctuations at arcminute scales, tau_{3000} = 0.001 T_{3000}/microK, implying that these fluctuations are no more than a few percent of the mean. Optical depth modulation of the quadrupole source to polarization generates B-modes that are correspondingly bounded as B_{3000} = 0.003 T_{3000}. The maximal extrapolation to the l~100 gravitational wave regime yields B_{100} = 0.1 T_{3000} and remains in excess of gravitational lensing if the effective comoving size of the ionizing regions is R > 80 Mpc. If patchy reionization is responsible for much of the observed arcminute scale temperature fluctuations, current bounds on B_{100} already require R < 200 Mpc and can be expected to improve rapidly. Frequency separation of thermal Sunyaev-Zel'dovich contributions to the measured secondary anisotropy would also substantially improve the limits on optical depth fluctuations and B-modes from reionization.

Given a class of dark energy models, constraints from one set of cosmic acceleration observables make predictions for other observables. Here we present the allowed ranges for the expansion rate H(z), distances D(z), and the linear growth function G(z) (as well as other, derived growth observables) from the current combination of cosmological measurements of supernovae, the cosmic microwave background, baryon acoustic oscillations, and the Hubble constant. With a cosmological constant as the dark energy and assuming near-minimal neutrino masses, the growth function is already predicted to better than 2% precision at any redshift, with or without spatial curvature. Direct measurements of growth that match this precision offer the opportunity to stringently test and potentially rule out a cosmological constant. While predictions in the broader class of quintessence models are weaker, it is remarkable that they are typically within a factor of 2-3 of forecasts for future space-based supernovae and Planck CMB measurements. In particular, measurements of growth at any redshift, or the Hubble constant H_0, that exceed LambdaCDM predictions by substantially more than 2% would rule out not only a cosmological constant but also the whole quintessence class, with or without curvature and early dark energy. Barring additional systematic errors hiding in the data, such a discovery would require more exotic explanations of cosmic acceleration such as phantom dark energy, dark energy clustering, or modifications of gravity.

This cross-sectional study examines predictors of heavy smoking among 256 male and female methadone maintenance therapy (MMT) clients from five MMT clinics in the Los Angeles area. The authors find that women report lower rates of heavy smoking than men (47% vs. 54%, respectively), in concordance with current literature pointing to gender differences in smoking behaviors. In particular, men who report heavy drinking, fair or poor health, and recent heroin use are more likely to report heavy smoking compared with men not reporting these factors. Women who report recent heroin use, a lifetime history of sex trade, and who have been ill enough to require a blood transfusion also have greater odds of reporting heavy cigarette smoking. Findings from this study may aid not only in designing gender-based smoking cessation programs for MMT clients but also in addressing the gender-based issues related to smoking in such a population.

Mixed-species associations are temporary associations between individuals of different species that are often observed in birds, primates and cetaceans. They have been interpreted as a strategy to reduce predation risk, enhance foraging success and/or provide a social advantage. In the archipelago of the Azores, four species of dolphins are commonly involved in mixed-species associations: the common dolphin, Delphinus delphis, the bottlenose dolphin, Tursiops truncatus, the striped dolphin, Stenella coeruleoalba, and the spotted dolphin, Stenella frontalis. In order to understand the reasons why dolphins associate, we analysed field data collected since 1999 by research scientists and trained observers placed onboard fishing vessels. In total, 113 mixed-species groups were observed out of 5720 sightings. The temporal distribution, habitat (water depth, distance to the coast), behaviour (i.e. feeding, travelling, socializing), size and composition of mixed-species groups were compared with those of single-species groups. Results did not support the predation avoidance hypothesis and gave little support to the social advantage hypothesis. The foraging advantage hypothesis was the most convincing. However, the benefits of mixed-species associations appeared to depend on the species. Associations were likely to be opportunistic in the larger bottlenose dolphin, while there seemed to be some evolutionary constraints favouring associations in the rarer striped dolphin. Comparison with previous studies suggests that the formation of mixed-species groups depends on several environmental factors, and therefore may constitute an adaptive response.