Compounding and Incorporation in the Ket Language: Implications for a More Unified Theory of Compounding

Compounding in the world’s languages is a complex word-­‐formation process that is not easily accounted for. Moreover, incorporation is equally complex and problematic. This examination of compounding and incorporation in the Ket language seeks to identify the underlying logic of these processes and to work towards a typology that captures generalizations among the numerous ways in which languages expand their lexicons through these processes. Canonical Typology provides a framework that does just this. A preliminary canonical typology of compounds is proposed here, one that subsumes a range of compounds as well as incorporation. For this reason, the Ket language, which relies heavily on compounding and incorporation, will be used as a test case. The aim is to define the canonical co

Filter Airflow prediction model development

The implementation of air filters on commercial swine farms has effectively reduced the frequency of airborne disease transmission. However, efficiently managing filter lifespan remains a challenge and an unknown operational cost for filtered swine facilities. Individual filter testing protocols are time consuming and expensive for producers. The objective of this study was to develop a predictive model for estimating airflow for an individual filter in situ by comparing multiple machine learning models to eliminate the need for manual, individual filter testing for filter resistance. The data set was generated from a custom Air Filter Environmental Testing Chamber that mimics on farm operational conditions with a low static pressure drop per filter and ground level installation. Model parameters were developed from a six-month long data set. The models were developed when the chamber was running with a new set of pre-filters and a set of five-month old v-bank filters. The developed models include a single input linear regression, multiple linear regression, and random forest models. A single input linear regression was not an effective method for predicting the chamber airflow, R2=0.08. The multiple linear regression moderately explained the variation in the data, R2=0.77. The random forest models performed the best for predicting the test chamber airflow with both models featuring R2= 0.98. The results and models from this study will be used to determine the feasibility of an on-farm application

Infrared proximity measurement system development and validation for classifying sow posture

The rapidly progressing field of precision livestock farming is becoming increasingly dependent on the utilization of camera technology. Integration of camera technology involves substantial intellectual input and computational power to acquire, process, and interpret images in real-time. Further, cameras and the necessary computational power can be cost-prohibitive and subsequently, become a constraint for application in a commercial livestock and poultry production systems. The purpose of this study is to develop an infrared proximity sensor based system to serve as a substitute a camera system to perform real-time monitoring of sow posture in farrowing stalls for a potentially lower cost and computational power. Monitoring sow posture can provide producers an indicator of farrowing and aid in evaluating sow demeanor during lactation. During the development of this system the long range infrared (IR) proximity sensors were individually calibrated, a sow posture algorithm was developed, and the IR-Sow Posture Detection System (IR-SoPoDS) system was evaluated in a commercial setting to a Kinect V2® camera for a range of sow postures. Average accuracy of the sow posture algorithm on the training data was found to be 96%. The overall accuracy of the IR-SoPoDS system across the three sow frame sizes were:87% (small), 90% (medium), and 89% (large). This IR-SoPoDS system shows a strong promise for further development for sow posture and behavior detection in the farrowing stall environment

Systematic Blueshift of Line Profiles in the Type IIn Supernova 2010jl: Evidence for Post-Shock Dust Formation?

Type IIn SNe show spectral evidence for strong interaction between their blast wave and dense circumstellar material (CSM) around the progenitor star. SN2010jl was the brightest core-collapse SN in 2010, and it was a Type IIn explosion with strong CSM interaction. Andrews et al. recently reported evidence for an IR excess in SN2010jl, indicating either new dust formation or the heating of CSM dust in an IR echo. Here we report multi-epoch spectra of SN2010jl that reveal the tell-tale signature of new dust formation: emission-line profiles becoming systematically more blueshifted as the red side of the line is blocked by increasing extinction. The effect is seen clearly in the intermediate-width (400--4000 km/s) component of H$\alpha$ beginning roughly 30d after explosion. Moreover, we present near-IR spectra demonstrating that the asymmetry in the hydrogen-line profiles is wavelength dependent, appearing more pronounced at shorter wavelengths. This evidence suggests that new dust grains had formed quickly in the post-shock shell of SN 2010jl arising from CSM interaction. Since the observed dust temperature has been attributed to an IR echo and not to new dust, either (1) IR excess emission at $\lambda < 5 \mu$m is not a particularly sensitive tracer of new dust formation in SNe, or (2) some assumptions about expected dust temperatures might require further study. Lastly, we discuss one possible mechanism other than dust that might lead to increasingly blueshifted line profiles in SNeIIn, although the wavelength dependence of the asymmetry argues against this hypothesis in the case of SN2010jl.Comment: 6 pages, 4 figures, submitted to A

Wave attenuation to clock sojourn times

The subject of time in quantum mechanics is of perennial interest especially because there is no observable for the time taken by a particle to transmit (or reflect) from a particular region. Several methods have been proposed based on scattering phase shifts and using different quantum clocks, where the time taken is clocked by some external input or indirectly from the phase of the scattering amplitudes. In this work we give a general method for calculating conditional sojourn times based on wave attenuation. In this approach clock mechanism does not couple to the Hamiltonian of the system. For simplicity, specific case of a delta dimer is considered in detail. Our analysis re-affirms recent results based on correcting quantum clocks using optical potential methods, albeit in a much simpler way.Comment: 4 pages, 5 figures. Minor corrections made and journal reference adde

Web-Based Training for an Evidence-Supported Treatment: Training Completion and Knowledge Acquisition in a Global Sample of Learners

The purpose of this investigation is to describe the characteristics of professional and preprofessional learners who registered for and completed TF-CBTWeb, a modular, web-based training program designed to promote the dissemination of Trauma-Focused Cognitive Behavioral Therapy (TF-CBT) and to demonstrate the feasibility of this method of dissemination. Between October 1, 2005, and October 1, 2012, a total of 123,848 learners registered for TF-CBTWeb, of whom 98,646 (79.7%) initiated the learning activities by beginning the first module pretest. Of those, 67,201 (68.1%) completed the full training. Registrants hailed from 130 countries worldwide, and they had varied educational backgrounds, professional identities (both professional and preprofessional), and a range of experience working with child trauma victims. Learners who were from the United States, students, those with master’s degrees, and those with fewer years of experience working with child trauma victims tended to have the highest course completion rates. Learners displayed significant increases in knowledge about each component of TF-CBT, based on module pretest and posttest scores. The advantages and limitations of this web-based training program evaluation are discussed, while important implications for the use of web-based trainings are reviewed

Food-Borne Chemical Carcinogens and the Evidence for Human Cancer Risk

Commonly consumed foods and beverages can contain chemicals with reported carcinogenic activity in rodent models. Moreover, exposures to some of these substances have been associated with increased cancer risks in humans. Food-borne carcinogens span a range of chemical classes and can arise from natural or anthropogenic sources, as well as form endogenously. Important considerations include the mechanism(s) of action (MoA), their relevance to human biology, and the level of exposure in diet. The MoAs of carcinogens have been classified as either DNA-reactive (genotoxic), involving covalent reaction with nuclear DNA, or epigenetic, involving molecular and cellular effects other than DNA reactivity. Carcinogens are generally present in food at low levels, resulting in low daily intakes, although there are some exceptions. Carcinogens of the DNA-reactive type produce effects at lower dosages than epigenetic carcinogens. Several food-related DNA-reactive carcinogens, including aflatoxins, aristolochic acid, benzene, benzo[a]pyrene and ethylene oxide, are recognized by the International Agency for Research on Cancer (IARC) as causes of human cancer. Of the epigenetic type, the only carcinogen considered to be associated with increased cancer in humans, although not from low-level food exposure, is dioxin (TCDD). Thus, DNA-reactive carcinogens in food represent a much greater risk than epigenetic carcinogens

Strong exciton-photon coupling with colloidal nanoplatelets in an open microcavity

Colloidal semiconductor nanoplatelets exhibit quantum size effects due to their thickness of only few monolayers, together with strong optical band-edge transitions facilitated by large lateral extensions. In this article we demonstrate room temperature strong coupling of the light and heavy hole exciton transitions of CdSe nanoplatelets with the photonic modes of an open planar microcavity. Vacuum Rabi splittings of $66 \pm 1$ meV and $58 \pm 1$ meV are observed for the heavy and light hole excitons respectively, together with a polariton-mediated hybridisation of both transitions. By measuring the concentration of platelets in the film we compute the transition dipole moment of a nanoplatelet exciton to be $\mu = (575 \pm 110)$ D. The large oscillator strength and fluorescence quantum yield of semiconductor nanoplatelets provide a perspective towards novel photonic devices, combining polaritonic and spinoptronic effects.Comment: 9 pages, 4 figure