Classifying Ellipsis in Dialogue: A Machine Learning Approach

Articl

Using Deep Neural Networks to Learn Syntactic Agreement

We consider the extent to which different deep neural network (DNN) configurations can learn syntactic relations, by taking up Linzen et al.’s (2016) work on subject-verb agreement with LSTM RNNs. We test their methods on a much larger corpus than they used (a ⇠24 million example part of the WaCky corpus, instead of their ⇠1.35 million example corpus, both drawn from Wikipedia). We experiment with several different DNN architectures (LSTM RNNs, GRUs, and CNNs), and alternative parameter settings for these systems (vocabulary size, training to test ratio, number of layers, memory size, drop out rate, and lexical embedding dimension size). We also try out our own unsupervised DNN language model. Our results are broadly compatible with those that Linzen et al. report. However, we discovered some interesting, and in some cases, surprising features of DNNs and language models in their performance of the agreement learning task. In particular, we found that DNNs require large vocabularies to form substantive lexical embeddings in order to learn structural patterns. This finding has interesting consequences for our understanding of the way in which DNNs represent syntactic information. It suggests that DNNs learn syntactic patterns more efficiently through rich lexical embeddings, with semantic as well as syntactic cues, than from training on lexically impoverished strings that highlight structural patterns

Prevalence of Enteropathogens in Dogs Attending 3 Regional Dog Parks in Northern California.

BackgroundThe prevalence and risk factors for infection with enteropathogens in dogs frequenting dog parks have been poorly documented, and infected dogs can pose a potential zoonotic risk for owners.Hypothesis/objectivesTo determine the prevalence and risk factors of infection with enteropathogens and zoonotic Giardia strains in dogs attending dog parks in Northern California and to compare results of fecal flotation procedures performed at a commercial and university parasitology laboratory.AnimalsThree-hundred dogs attending 3 regional dog parks in Northern California.MethodsProspective study. Fresh fecal specimens were collected from all dogs, scored for consistency, and owners completed a questionnaire. Specimens were analyzed by fecal centrifugation flotation, DFA, and PCR for detection of 11 enteropathogens. Giardia genotyping was performed for assemblage determination.ResultsEnteropathogens were detected in 114/300 dogs (38%), of which 62 (54%) did not have diarrhea. Frequency of dog park attendance correlated significantly with fecal consistency (P = .0039), but did not correlate with enteropathogen detection. Twenty-seven dogs (9%) were infected with Giardia, and genotyping revealed nonzoonotic assemblages C and D. The frequency of Giardia detection on fecal flotation was significantly lower at the commercial laboratory versus the university laboratory (P = .013), and PCR for Giardia was negative in 11/27 dogs (41%) that were positive on fecal flotation or DFA.Conclusions and clinical importanceEnteropathogens were commonly detected in dogs frequenting dog parks, and infection with Giardia correlated with fecal consistency. PCR detection of Giardia had limited diagnostic utility, and detection of Giardia cysts by microscopic technique can vary among laboratories

‘Synthetic cannabis’: A dangerous misnomer

The term 'synthetic cannabis' has been widely used in public discourse to refer to a group of cannabinoid receptor agonists. In this paper we detail the characteristics of these drugs, and present the case that the term is a misnomer. We describe the pharmacodynamics of these drugs, their epidemiology, mechanisms of action, physiological effects and how these differ substantially from delta-9-tetrahydrocannabinol (THC). We argue that not only is the term a misnomer, but it is one with negative clinical and public health implications. Rather, the substances referred to as 'synthetic cannabis' in public discourse should instead be referred to consistently as synthetic cannabinoid receptor agonists (SCRAs), a drug class distinct from plant-derived cannabinoids. SCRAs have greater potency and efficacy, and psychostimulant-like properties. While such terminology may be used in the scientific community, it is not widely used amongst the media, general public, people who use these drugs or may potentially do so. A new terminology has the potential to reduce the confusion and harms that result from the misnomer ‘synthetic cannabis’. The constant evolution of this distinct drug class necessitates a range of distinct policy responses relating to terminology, harm reduction, epidemiology, treatment, and legal status

The anti-adhesive effect of curcumin on Candida albicans biofilms on denture materials

The use of natural compounds as an alternative source of antimicrobials has become a necessity given the growing concern over global antimicrobial resistance. Polyphenols, found in various edible plants, offers one potential solution to this. We aimed to investigate the possibility of using curcumin within the context of oral health as a way of inhibiting and preventing the harmful development of Candida albicans biofilms. We undertook a series of adsorption experiments with varying concentrations of curcumin, showing that 50 ug/ml could prevent adhesion. This effect could be further synergised by the curcumin pretreatment of yeast cells to obtain significantly greater inhibition (>90, p<0.001). Investigation of the biological impact of curcumin showed that it preferentially affected immature morphological forms (yeast and germlings), and actively promoted aggregation of the cells. Transcriptional analyses showed that key adhesins were down-regulated (ALS1 and ALS3), whereas aggregation related genes (ALS5 and AAF1) were up-regulated. Collectively, these data demonstrated that curcumin elicits anti-adhesive effects and that induces transcription of genes integrally involved in the processes related to biofilm formation. Curcumin and associated polyphenols therefore have the capacity to be developed for use in oral healthcare to augment existing preventative strategies for candidal biofilms on the denture surface

Visual coherence of moving and stationary image changes

AbstractDetection thresholds were compared for moving and stationary oscillations with equivalent contrast changes. Motion was more detectable than stationary oscillation, and the difference increased with size of the feature (a Gaussian blob). Phase discriminations between a center and two flanking features were much better for motion than for stationary oscillation. Motion phase discriminations were similar to motion detection and were robust over increases in spatial separation and temporal frequency, but not so for stationary oscillations. Separate visual motion signals were positively correlated, but visual signals for stationary oscillation were negatively correlated. Evidently, motion produces visually coherent changes in image structure, but stationary contrast oscillation does not

Bayesian Inference Semantics: A Modelling System and A Test Suite

We present BIS, a Bayesian Inference Seman- tics, for probabilistic reasoning in natural lan- guage. The current system is based on the framework of Bernardy et al. (2018), but de- parts from it in important respects. BIS makes use of Bayesian learning for inferring a hy- pothesis from premises. This involves estimat- ing the probability of the hypothesis, given the data supplied by the premises of an argument. It uses a syntactic parser to generate typed syn- tactic structures that serve as input to a model generation system. Sentences are interpreted compositionally to probabilistic programs, and the corresponding truth values are estimated using sampling methods. BIS successfully deals with various probabilistic semantic phe- nomena, including frequency adverbs, gener- alised quantifiers, generics, and vague predi- cates. It performs well on a number of interest- ing probabilistic reasoning tasks. It also sus- tains most classically valid inferences (instan- tiation, de Morgan’s laws, etc.). To test BIS we have built an experimental test suite with examples of a range of probabilistic and clas- sical inference patterns

Prevalence and correlates of food insecurity in community-based individuals with severe mental illness receiving long-acting injectable antipsychotic treatment

People with severe mental illness (SMI) have numerous risk factors that may predispose them to food insecurity (FI); however, the prevalence of FI and its effects on health are under-researched in this population. The present study aimed to describe the prevalence of FI and its relationship to lifestyle factors in people with SMI. This cross-sectional study recruited people with SMI receiving long-acting injectable (LAI) antipsychotic medication from community services at three sites in Sydney, Australia. Assessments were completed on physical health and lifestyle factors. χ2 Tests, independent-samples t tests and binary logistic regression analyses were calculated to examine relationships between lifestyle factors and FI. In total, 233 people completed the assessments: 154 were males (66 %), mean age 44·8 (sd 12·7) years, and the majority (70 %) had a diagnosis of schizophrenia. FI was present in 104 participants (45 %). People with FI were less likely to consume fruits (OR 0·42, 95 % CI 0·24, 0·74, P = 0·003), vegetables (OR 0·39, 95 % CI 0·22, 0·69, P = 0·001) and protein-based foods (OR 0·45, 95 % CI 0·25, 0·83, P = 0·011) at least once daily, engaged in less moderate to vigorous physical activity (min) (OR 0·997, 95 % CI 0·993, 1·000, P = 0·044), and were more likely to smoke (OR 1·89, 95 % CI 1·08, 3·32, P = 0·026). FI is highly prevalent among people with SMI receiving LAI antipsychotic medications. Food-insecure people with SMI engage in less healthy lifestyle behaviours, increasing the risk of future non-communicable disease

Risk Factors for Development of Chronic Kidney Disease in Cats

BACKGROUND: Identification of risk factors for development of chronic kidney disease (CKD) in cats may aid in its earlier detection. HYPOTHESIS/OBJECTIVES: Evaluation of clinical and questionnaire data will identify risk factors for development of azotemic CKD in cats. ANIMALS: One hundred and forty‐eight client‐owned geriatric (>9 years) cats. METHODS: Cats were recruited into the study and followed longitudinally for a variable time. Owners were asked to complete a questionnaire regarding their pet at enrollment. Additional data regarding dental disease were obtained when available by development of a dental categorization system. Variables were explored in univariable and multivariable Cox regression models. RESULTS: In the final multivariable Cox regression model, annual/frequent vaccination (P value, .003; hazard ratio, 5.68; 95% confidence interval, 1.83–17.64), moderate dental disease (P value, .008; hazard ratio, 13.83; 95% confidence interval, 2.01–94.99), and severe dental disease (P value, .001; hazard ratio, 35.35; 95% confidence interval, 4.31–289.73) predicted development of azotemic CKD. CONCLUSION: Our study suggests independent associations between both vaccination frequency and severity of dental disease and development of CKD. Further studies to explore the pathophysiological mechanism of renal injury for these risk factors are warranted