Bighorn Sheep Movements and Mineral Lick Use in Waterton-Glacier International Peace Park (Poster)

This study used bighorn sheep telemetry data collected in Glacier National Park, Waterton Lakes National Park, and the Blackfeet Reservation to examine bighorn sheep movements and use of known mineral licks.  Over 168,400 GPS locations were collected between 2002 and 2011 on 97 bighorn sheep individuals from 17 different social groups.  We examined the proximity of bighorn sheep telemetry data to 32 known mineral lick locations to describe timing and frequency of mineral lick use.  Fifty individuals had locations near known mineral licks, and most mineral lick visits took place between May and August.  We compared movements towards known mineral lick locations with general bighorn sheep movements.  After estimating bighorn sheep kernel home ranges, we evaluated how movement towards the lick, timing, and frequency of use varied depending on location of the lick relative to sheep home ranges.  We conducted a k-means cluster analysis of movement characteristics to identify potential locations of unknown mineral licks and movement pinch points.  We will discuss options for using these locations to monitor bighorn sheep health and population size

Ab initio study of transport properties in defected carbon nanotubes: an O(N) approach

A combination of ab initio simulations and linear-scaling Green's functions techniques is used to analyze the transport properties of long (up to one micron) carbon nanotubes with realistic disorder. The energetics and the influence of single defects (mono- and di-vacancies) on the electronic and transport properties of single-walled armchair carbon nanotubes are analyzed as a function of the tube diameter by means of the local orbital first-principles Fireball code. Efficient O(N) Green's functions techniques framed within the Landauer-Buttiker formalism allow a statistical study of the nanotube conductance averaged over a large sample of defected tubes and thus extraction of the nanotubes localization length. Both the cases of zero and room temperature are addressed.Comment: 15 pages, 12 figures (submitted to J. Phys: Condens. Matter

Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition

Here, we develop an audiovisual deep residual network for multimodal apparent personality trait recognition. The network is trained end-to-end for predicting the Big Five personality traits of people from their videos. That is, the network does not require any feature engineering or visual analysis such as face detection, face landmark alignment or facial expression recognition. Recently, the network won the third place in the ChaLearn First Impressions Challenge with a test accuracy of 0.9109

Social Preferences, Skill Segregation and Wage Dynamics

We study the earning structure and the equilibrium asignment of workers to firms in a model in which workers have social preferences, and skills are perfectly substitutable in production. Firms offer long-term contracts, and we allow for frictions in the labour market in the form of mobility costs. The model delivers specific predictions about the nature of worker flows, about the characteristic of workplace skill segregation, and about wage dispersion both within and cross firms. We shows that long-term contracts in the resence of social preferences associate within-firm wage dispersion with novel "internal labour market" features such as gradual promotions, productivity-unrelated wage increases, and downward wage flexibility. These three dynamic features lead to productivity-unrelated wage volatily within firms.Publicad

Extending the viability of human precision-cut intestinal slice model for drug metabolism studies

Human Precision-cut intestinal slices (hPCIS) are used to study intestinal physiology, pathophysiology, drug efficacy, toxicology, kinetics, and metabolism. However, the use of this ex vivo model is restricted to approximately a 24 h timeframe because of declining viability of the hPCIS during traditional culture. We hypothesized that we could extend the hPCIS viability by using organoid medium. Therefore, we cultured hPCIS for up to 72 h in organoid media [expansion medium (Emed) and differentiation medium (Dmed)]. After incubation, we assessed culture-induced changes on viability markers, specific cell type markers and we assessed the metabolic activity of enterocytes by measuring midazolam metabolite formation. We show that the adenosine triphosphate (ATP)/protein ratio of Emed-cultured hPCIS and morphology of both Emed- and Dmed-cultured hPCIS was improved compared to WME-cultured hPCIS. Emed-cultured hPCIS showed an increased expression of proliferation and stem cell markers, whereas Dmed-cultured hPCIS showed an increased expression of proliferation and enterocyte markers, along with increased midazolam metabolism. Using the Emed, the viability of hPCIS could be extended for up to 72 h, and proliferating stem cells remained preserved. Using Dmed, hPCS also remained viable for up to 72 h, and specifically rescued the metabolizing enterocytes during culture. In conclusion, by using two different organoid culture media, we could extend the hPCIS viability for up to 72 h of incubation and specifically steer stem cells or enterocytes towards their original function, metabolism, and proliferation, potentially allowing pharmacokinetic and toxicology studies beyond the 24 h timeframe

Applications and Benefits of Catalytic Converter Thermal Management

A catalytic converter thermal management system (TMS) using variable-conductance vacuum insulation and phase-change thermal storage can maintain the converter temperature above its operating temperature for many hours, allowing most trips to begin with minimal ``cold-start`` emissions. The latest converter TMS prototype was tested on a Ford Taurus (3.0 liter flex-fuel engine) at Southwest Research Institute. Following a 24-hour soak, the FTP-75 emissions were 0.031, 0.13, and 0.066 g/mile for NMHC, CO, and NOx, respectively. Tests were also run using 85% ethanol (E85), resulting in values of 0.005, 0.124, and 0.044 g/mile, and 0.005 g/mile NMOG. Compared to the baseline FTP levels, these values represent reductions of 84% to 96% for NMHC, NMOG, and CO

Genuine Personality Recognition from Highly Constrained Face Images

People are able to accurately estimate personality traits, merely on the basis of \u201cpassport\u201d-style neutral faces and, thus, cues must exist that allow for such estimation. However, up to date, there has been little progress in identifying the form and location of these cues. In this paper we address the problem of inferring true personality traits in highly constrained images using state of art machine learning techniques, in particular, deep networks and class activation maps analysis. The novelty of our work consists in that, differently from the vast majority of the current and past approaches (that refer to the problem of consensus personality rating prediction) we predict the genuine personality based on highly constrained images: the target\u2019s are self ratings on a validated personality inventory and we restrict to passport-like photos, in which so-called controllable cues are minimized. Our results show that self-reported personality traits can be accurately evaluated from facial features. A preliminar analysis on the features activation maps shows promising results for a deeper understanding on relevant facial cues for traits estimation