“Believe me”:an analysis of Donald Trump’s use of refrains

Abstract. The purpose of this master’s thesis is to examine U.S. president Donald Trump’s use of refrains during unscripted talk with political discourse analysis as my method. The research material for the study consists of publicly available recordings and transcripts of Trump talking at various events, including the three 2016 presidential debates with Hillary Clinton, several campaign rallies, one-on-one interviews, and improvised remarks given to reporters, mostly at the White House. The refrains that were identified in the study are “Believe me,” “We’ll see what happens,” “They say,” “Take a look at,” “Like they’ve never seen before,” and “Nobody’s ever seen anything like it.” The analysis showed that Trump’s refrains share common features, which are vagueness, repetition, vernacular folksiness, exaggeration, and appeals to authority. The surrounding sentence elements of the refrains were presented in refrain pattern tables that highlight the systematic manner in which the refrains are used. Trump typically relied on the refrains when making various claims and providing proof for his arguments. They were most often used in contexts were Trump was criticizing some entity and asserting his authority.Tiivistelmä. Tämän pro gradu -tutkielman tarkoitus on tarkastella Yhdysvaltain presidentin Donald Trumpin käyttämiä hokemia hänen puhuessaan omin sanoin erilaisissa tilaisuuksissa. Menetelmäni tähän tarkoitukseen on poliittinen diskurssianalyysi. Tutkimusaineistoni koostuu Trumpin esiintymisten julkisista tallenteista, mukaan lukien kolme vaaliväittelyä Hillary Clintonin kanssa vuodelta 2016, useita vaalikampanjan aikaisia puhetilaisuuksia, haastatteluita ja lähinnä Valkoisessa talossa toimittajille esitettyjä improvisoituja kommentteja. Tutkimuksessa havaittuja hokemia olivat ”Believe me” (”Uskokaa minua”), ”We’ll see what happens” (”Katsotaan mitä tapahtuu”), ”They say” (”Monet sanovat”), ”Take a look at” (”Katso”), ”Like they’ve never seen before” (”Kuin he eivät ole koskaan nähneet”) ja ”Nobody’s ever seen anything like it” (”Kukaan ei ole koskaan nähnyt moista”). Tutkimuksesta kävi ilmi, että hokemia yhdistäviä tekijöitä ovat epämääräisyys, toisto, puhekielisyys, liioittelu ja auktoriteetteihin vetoaminen. Hokemia käytettiin systemaattisesti siten, että ympäröivät lauseet noudattivat yleensä samaa mallia. Trump vaikuttaa käyttävän hokemia erilaisten väittämien esittämiseen, ja tarjoaa niiden avulla perusteluita argumenteilleen. Ne esiintyivät useimmin konteksteissa, joissa Trump kritisoi jotakin ja pyrki vahvistamaan omaa auktoriteettiaan

Enhancement of marine cloud albedo via controlled sea spray injections: a global model study of the influence of emission rates, microphysics and transport

Modification of cloud albedo by controlled emission of sea spray particles into the atmosphere has been suggested as a possible geoengineering option to slow global warming. Previous global studies have imposed changes in cloud drop concentration in low level clouds to explore the radiative and climatic effects. Here, we use a global aerosol transport model to quantify how an imposed flux of sea spray particles affects the natural aerosol processes, the particle size distribution, and concentrations of cloud drops. We assume that the proposed fleet of vessels emits sea spray particles with a wind speed-dependent flux into four regions of persistent stratocumulus cloud off the western coasts of continents. The model results show that fractional changes in cloud drop number concentration (CDNC) vary substantially between the four regions because of differences in wind speed (which affects the spray efficiency of the vessels), transport and particle deposition rates, and because of variations in aerosols from natural and anthropogenic sources. Using spray emission rates comparable to those implied by previous studies we find that the predicted CDNC changes are very small (maximum 20%) and in one of the four regions even negative. The weak or negative effect is because the added particles suppress the in-cloud supersaturation and prevent existing aerosol particles from forming cloud drops. A scenario with five times higher emissions (considerably higher than previously assumed) increases CDNC on average by 45–163%, but median concentrations are still below the 375 cm<sup>−3</sup> assumed in previous studies. An inadvertent effect of the spray emissions is that sulphur dioxide concentrations are suppressed by 1–2% in the seeded regions and sulphuric acid vapour by 64–68% due to chemical reactions on the additional salt particles. The impact of this suppression on existing aerosol is negligible in the model, but should be investigated further in the real environment so that inadvertent impacts can be excluded

Stellar activity as noise in exoplanet detection I. Methods and application to solar-like stars and activity cycles

The detection of exoplanets using any method is prone to confusion due to the intrinsic variability of the host star. We investigate the effect of cool starspots on the detectability of the exoplanets around solar-like stars using the radial velocity method. For investigating this activity-caused "jitter" we calculate synthetic spectra using radiative transfer, known stellar atomic and molecular lines, different surface spot configurations, and an added planetary signal. Here, the methods are described in detail, tested and compared to previously published studies. The methods are also applied to investigate the activity jitter in old and young solar-like stars, and over a solar-like activity cycles. We find that the mean full jitter amplitude obtained from the spot surfaces mimicking the solar activity varies during the cycle approximately between 1 m/s and 9 m/s. With a realistic observing frequency a Neptune mass planet on a one year orbit can be reliably recovered. On the other hand, the recovery of an Earth mass planet on a similar orbit is not feasible with high significance. The methods developed in this study have a great potential for doing statistical studies of planet detectability, and also for investigating the effect of stellar activity on recovered planetary parameters.Comment: Accepted to MNRA

CERCLA Defendants: The Problem of Expanding Liability and Diminishing Defenses

The Article will first explore the various actions that expose a party to CERCLA liability. Second, this paper will examine the extent of the potential liability. Third, the statutory affirmative defenses that a defendant may assert will be investigated. Finally, the ability of a defendant to decrease any damage awards against him, through apportionment, will be explored

Magnetic field geometry and chemical abundance distribution of the He-strong star CPD -57 3509

The magnetic field of CPD -57 3509 was recently detected in the framework of the BOB (B fields in OB stars) collaboration. We acquired low-resolution spectropolarimetric observations of CPD -57 3509 with FORS2 and high-resolution UVES observations randomly distributed over a few months to search for periodicity, to study the magnetic field geometry, and to determine the surface distribution of silicon and helium. We also obtained supplementary photometric observations at a timeline similar to the spectroscopic and spectropolarimetric observations. A period of 6.36d was detected in the measurements of the mean longitudinal magnetic field. A sinusoidal fit to our measurements allowed us to constrain the magnetic field geometry and estimate the dipole strength in the range of 3.9-4.5kG. Our application of the Doppler imaging technique revealed the presence of He I spots located around the magnetic poles, with a strong concentration at the positive pole and a weaker one around the negative pole. In contrast, high concentration Si III spots are located close to the magnetic equator. Further, our analysis of the spectral variability of CPD -57 3509 on short time scales indicates distinct changes in shape and position of line profiles possibly caused by the presence of beta Cep-like pulsations. A small periodic variability in line with the changes of the magnetic field strength is clearly seen in the photometric data.Comment: 11 pages, 5 tables, 7 figures, accepted for publication in MNRA

Aerosol climate feedback due to decadal increases in Southern Hemisphere wind speeds

Observations indicate that the westerly jet in the Southern Hemisphere troposphere is accelerating. Using a global aerosol model we estimate that the increase in wind speed of 0.45 + /- 0.2 m s(-1) decade(-1) at 50-65 degrees S since the early 1980s caused a higher sea spray flux, resulting in an increase of cloud condensation nucleus concentrations of more than 85% in some regions, and of 22% on average between 50 and 65 degrees S. These fractional increases are similar in magnitude to the decreases over many northern hemisphere land areas due to changes in air pollution over the same period. The change in cloud drop concentrations causes an increase in cloud reflectivity and a summertime radiative forcing between at 50 and 65 degrees S comparable in magnitude but acting against that from greenhouse gas forcing over the same time period, and thus represents a substantial negative climate feedback. However, recovery of Antarctic ozone depletion in the next two decades will likely cause a fall in wind speeds, a decrease in cloud drop concentration and a correspondingly weaker cloud feedback

Enhancing biomedical word embeddings by retrofitting to verb clusters

Verbs play a fundamental role in many biomedical tasks and applications such as relation and event extraction. We hypothesize that performance on many downstream tasks can be improved by aligning the input pretrained embeddings according to semantic verb classes. In this work, we show that by using semantic clusters for verbs, a large lexicon of verb classes derived from biomedical literature, we are able to improve the performance of common pretrained embeddings in downstream tasks by retrofitting them to verb classes. We present a simple and computationally efficient approach using a widely available “off-theshelf” retrofitting algorithm to align pretrained embeddings according to semantic verb clusters. We achieve state-of-the-art results on text classification and relation extraction tasks

Cell deformation behavior in mechanically loaded rabbit articular cartilage 4 weeks after anterior cruciate ligament transection

SummaryObjectiveChondrocyte stresses and strains in articular cartilage are known to modulate tissue mechanobiology. Cell deformation behavior in cartilage under mechanical loading is not known at the earliest stages of osteoarthritis. Thus, the aim of this study was to investigate the effect of mechanical loading on volume and morphology of chondrocytes in the superficial tissue of osteoarthritic cartilage obtained from anterior cruciate ligament transected (ACLT) rabbit knee joints, 4 weeks after intervention.MethodsA unique custom-made microscopy indentation system with dual-photon microscope was used to apply controlled 2 MPa force-relaxation loading on patellar cartilage surfaces. Volume and morphology of chondrocytes were analyzed before and after loading. Also global and local tissue strains were calculated. Collagen content, collagen orientation and proteoglycan content were quantified with Fourier transform infrared microspectroscopy, polarized light microscopy and digital densitometry, respectively.ResultsFollowing the mechanical loading, the volume of chondrocytes in the superficial tissue increased significantly in ACLT cartilage by 24% (95% confidence interval (CI) 17.2–31.5, P < 0.001), while it reduced significantly in contralateral group tissue by −5.3% (95% CI −8.1 to −2.5, P = 0.003). Collagen content in ACLT and contralateral cartilage were similar. PG content was reduced and collagen orientation angle was increased in the superficial tissue of ACLT cartilage compared to the contralateral cartilage.ConclusionsWe found the novel result that chondrocyte deformation behavior in the superficial tissue of rabbit articular cartilage is altered already at 4 weeks after ACLT, likely because of changes in collagen fibril orientation and a reduction in PG content

A neural network multi-task learning approach to biomedical named entity recognition

$\textbf{Background}$ Named Entity Recognition (NER) is a key task in biomedical text mining. Accurate NER systems require task-specific, manually-annotated datasets, which are expensive to develop and thus limited in size. Since such datasets contain related but different information, an interesting question is whether it might be possible to use them together to improve NER performance. To investigate this, we develop supervised, multi-task, convolutional neural network models and apply them to a large number of varied existing biomedical named entity datasets. Additionally, we investigated the effect of dataset size on performance in both single- and multi-task settings. $\textbf{Results}$ We present a single-task model for NER, a Multi-output multi-task model and a Dependent multi-task model. We apply the three models to 15 biomedical datasets containing multiple named entities including Anatomy, Chemical, Disease, Gene/Protein and Species. Each dataset represent a task. The results from the single-task model and the multi-task models are then compared for evidence of benefits from Multi-task Learning. With the Multi-output multi-task model we observed an average F-score improvement of 0.8% when compared to the single-task model from an average baseline of 78.4%. Although there was a significant drop in performance on one dataset, performance improves significantly for five datasets by up to 6.3%. For the Dependent multi-task model we observed an average improvement of 0.4% when compared to the single-task model. There were no significant drops in performance on any dataset, and performance improves significantly for six datasets by up to 1.1%. The dataset size experiments found that as dataset size decreased, the multi-output model’s performance increased compared to the single-task model’s. Using 50, 25 and 10% of the training data resulted in an average drop of approximately 3.4, 8 and 16.7% respectively for the single-task model but approximately 0.2, 3.0 and 9.8% for the multi-task model. $\textbf{Conclusions}$ Our results show that, on average, the multi-task models produced better NER results than the single-task models trained on a single NER dataset. We also found that Multi-task Learning is beneficial for small datasets. Across the various settings the improvements are significant, demonstrating the benefit of Multi-task Learning for this task.This work was supported by Medical Research Council [grant number MR/M013049/1] and the Cambridge Commonwealth, European and International Trust

Effects of gnawing material, group size and cage level in rack on Wistar rats

Han: Wist rats were housed after weaning in groups of one, two, three or four in stainless steel cages with aspen chip bedding, with or without wooden gnawing blocks. The use of the blocks was assessed by Video recording and by measuringweight loss of the blocks. Behaviour of the males&nbsp; was tested in a five minute open field test. At the age of 14 weeks the males were transferred into cages with wire mesh bottom without contact bedding. After four weeks, the males were&nbsp; euthanized and weights of the adrenal glands, thymus and spleen were measured. The physiological and behavioural effects of blocks, group size and cage level in rack were tested. In solid bottom cages with direct bedding, the use of the blocks was minimal. It was not affected by the sex or age of the animals. Neither was it affected by the group size or the cage level in a rack. The gnawing of the blocks increased afier the rats were transferred on to grid floor without bedding. The food intake or weight gain were not affected by any of the factors studied. The presence of blocks decreased the adrenal weights in rats transferred into wire mesh cages. In open field, the animals living alone were less active and they moved slower from the peripheral to central area than the animals living in groups. The animals living on the highest shelf of the rack differed from the others in their latency times of rearing and grooming. None of the environmental variables tested affected the behavioural factor scores derived from factor analysis. In conclusion. the wooden blocks may reduce the stress of rats adapted to bedding, if they have to be removed to grid floor. The group size or cage level in rack influenced some behaviours of rats in the open field