Speech act theory and Gricean pragmatics: A review

This paper entitled “Speech Act Theory and Gricean Pragmatics: A Review” appreciates the language of action words since pragmatic strategies are applied in order to bring out features of speeches. Pragmatic strategies such as entailment, presupposition, implicatures, context of situation, speech acts among others were used in this paper. The paper is also anchored on the pragmatic theory which is a speech act theory. This theory deals with utterances and how they are used to express actions. The examples used in this study were utterances used by some scholars in their research work and some extemporaneous examples given by the authors of this paper. These utterances served as our data in this paper. The study concludes that speech act captures an action performed by someone through his words. Also the central aspect of the Speech Act Theory is that an utterance is part of an action within the framework of social institution and conventions. J. L. Austin proposed three levels of speech acts: locutionary act, illocutionary act and perlocutionary act which were dissected in this paper

Opportunities and Challenges in a Changing Beef Industry: Results of a Statewide Needs Assessment in Iowa

The U.S. beef industry is poised for growth following increased contraction over the past decade that has resulted in the lowest cattle inventory in over 60 years. However, sustainable, long term growth of the industry is dependent upon early identification of issues that may inhibit profitability. A series of seven listening sessions conducted across Iowa in November and December of 2013 by the Iowa Beef Center identified land access, farm transition, production efficiency, marketing, genetics, data management, feedstuffs, and animal health as “mega-issues” facing producers. Specific issues under each of these overarching categories will guide future extension programming efforts within the Iowa Beef Center

GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

One of the biggest issues facing the use of machine learning in medical imaging is the lack of availability of large, labelled datasets. The annotation of medical images is not only expensive and time consuming but also highly dependent on the availability of expert observers. The limited amount of training data can inhibit the performance of supervised machine learning algorithms which often need very large quantities of data on which to train to avoid overfitting. So far, much effort has been directed at extracting as much information as possible from what data is available. Generative Adversarial Networks (GANs) offer a novel way to unlock additional information from a dataset by generating synthetic samples with the appearance of real images. This paper demonstrates the feasibility of introducing GAN derived synthetic data to the training datasets in two brain segmentation tasks, leading to improvements in Dice Similarity Coefficient (DSC) of between 1 and 5 percentage points under different conditions, with the strongest effects seen fewer than ten training image stacks are available

Cosmic homogeneity demonstrated with luminous red galaxies

We test the homogeneity of the Universe at $z\sim 0.3$ with the Luminous Red Galaxy (LRG) spectroscopic sample of the Sloan Digital Sky Survey. First, the mean number $N(R)$ of LRGs within completely surveyed LRG-centered spheres of comoving radius $R$ is shown to be proportional to $R^3$ at radii greater than $R\sim 70 h^{-1} \mathrm{Mpc}$. The test has the virtue that it does not rely on the assumption that the LRG sample has a finite mean density; its results show, however, that there \emph{is} such a mean density. Secondly, the survey sky area is divided into 10 disjoint solid angular regions and the fractional rms density variations of the LRG sample in the redshift range $0.2<z<0.35$ among these ($\sim 2\times10^7 h^{-3} \mathrm{Mpc^3}$) regions is found to be 7 percent of the mean density. This variance is consistent with typical biased \lcdm models and puts very strong constraints on the quality of SDSS photometric calibration.Comment: submitted to Ap

Average Infrared Galaxy Spectra From Spitzer Flux Limited Samples

The mid-infrared spectroscopic analysis of a flux-limited sample of galaxies with fv(24um) > 10 mJy is presented. Sources observed are taken from the Spitzer First Look Survey (FLS) catalog and from the NOAO Deep Wide-Field Survey region in Bootes (NDWFS). The spectroscopic sample includes 60 of the 100 sources in these combined catalogs having fv(24um) > 10 mJy. New spectra from the Spitzer Infrared Spectrograph are presented for 25 FLS sources and for 11 Bootes AGN; these are combined with 24 Bootes starburst galaxies previously published to determine the distribution of mid-infrared spectral characteristics for the total 10 mJy sample. Sources have 0.01 < z < 2.4 and 41.8 < log vLv(15um) < 46.2 (ergs/s). Average spectra are determined as a function of luminosity; lower luminosity sources (log vLv(15um) < 44.0) are dominated by PAH features and higher luminosity sources (log vLv(15um) > 44.0) are dominated by silicate absorption or emission. We find that a rest frame equivalent width of 0.4um for the 6.2um PAH emission feature provides a well defined division between lower luminosity, "pure" starbursts and higher luminosity AGN or composite sources. Using the average spectra, fluxes fv(24um) which would be observed with the Spitzer MIPS are predicted as a function of redshift for sources with luminosities that correspond to the average spectra. AGN identical to those in this 10 mJy sample could be seen to z = 3 with fv(24um) > 1 mJy, but starbursts fall to fv(24um) < 1 mJy by z ~ 0.5. This indicates that substantial luminosity evolution of starbursts is required to explain the numerous starbursts found in other IRS results having fv(24um) > 1 mJy and z ~ 2.Comment: Accepted for publication in The Astrophysical Journa

2006 SQ372: A Likely Long-Period Comet from the Inner Oort Cloud

We report the discovery of a minor planet (2006 SQ372) on an orbit with a perihelion of 24 AU and a semimajor axis of 796 AU. Dynamical simulations show that this is a transient orbit and is unstable on a timescale of 200 Myrs. Falling near the upper semimajor axis range of the scattered disk and the lower semimajor axis range of the Oort Cloud, previous membership in either class is possible. By modeling the production of similar orbits from the Oort Cloud as well as from the scattered disk, we find that the Oort Cloud produces 16 times as many objects on SQ372-like orbits as the scattered disk. Given this result, we believe this to be the most distant long-period comet ever discovered. Furthermore, our simulation results also indicate that 2000 OO67 has had a similar dynamical history. Unaffected by the "Jupiter-Saturn Barrier," these two objects are most likely long-period comets from the inner Oort Cloud