Perseverers, recencies and deferrers : new experimental evidence for multiple inference strategies in understanding

In the course of understanding a text, a succession of decision points arise at which readers are faced with the task of choosing among alternative possible interpretations ofthattext. We present new experimental evidence that different readers use different inference strategies to guide their inference behavior during understanding. The choices available to an understander range from various alternative inferential paths to the option of making no inference at a particular point, leaving a 'loose end'. Different inference strategies result in observably different behaviors during understanding, including consistent differences in reading times, and different interpretations of a text. The preliminary experimental results given here so far consistently support a previously published set of hypotheses about the inference process that we have called Judgmental Inference theory

Parsing with parallelism : a spreading-activation model of inference processing during text understanding

The past decade of reseatch in Natural Language Processing has universally recognized that, since natural language input is almost always ambiguous with respect to its pragmatic implications, its syntactic parse, and even its lexical analysis (i.e., choice of correct word-sense for an ambiguous word), processing natural language input requires decisions about word meanings, syntactic structure, and pragmatic inferences. The lexical, syntactic, and pragmatic levels of inferencing are not as disparate as they have often been treated in both psychological and artificial intelligence research. In fact, these three levels of analysis interact to form a joint interpretation of text.ATLAST (A Three-level Language Analysis SysTem) is an implemented integration of human language understanding at the lexical, the syntactic, and the pragmatic levels. For psychological validity, ATLAST is based on results of experiments with human subjects. The ATLAST model uses a new architecture which was developed to incorporate three features: spreading activation memory, two-stage syntax, and parallel processing of syntax and semantics. It is also a new framework within which to interpret and tackle unsolved problems through implementation and experimentation

STRATEGIST : a program that models strategy-driven and content-driven inference behavior

In the course of understanding a text, different readers use different inference strategies to guide their choice of interpretations of the events in the text. This is in contrast to previous computer models of understanding, which all use the content-driven inference. The separate strategies are theorized to be composed of the same component inference processes, but of different rules for application of the processes. The use of different strategies occasionally results in different results of new experimental data and a working computer program, called STRATEGIST, that models both strategy-drive and content-driven inference behavior. The rules which make up two of these strategies are presented

Maximal multihomogeneity of algebraic hypersurface singularities

From the degree zero part of logarithmic vector fields along an algebraic hypersurface singularity we indentify the maximal multihomogeneity of a defining equation in form of a maximal algebraic torus in the embedded automorphism group. We show that all such maximal tori are conjugate and in one-to-one correspondence to maxmimal tori in the degree zero jet of the embedded automorphism group. The result is motivated by Kyoji Saito's characterization of quasihomogeneity for isolated hypersurface singularities and extends its formal version and a result of Hauser and Mueller.Comment: 5 page

Multi-comparisons of rape and rape myth endorsement through analysis of existing modified rape myth items

Traditionally, rape has been viewed as a crime perpetrated by men against women. However, it is now recognised that males can also be victims of rape. The current research had several interrelated aims to; (i) provide a profile of both male and female rape victims, (ii) compare the characteristics of rape perpetrated against male and female victims, (iii) estimate the incidence of male and female rape within the general community, (iv) describe the reporting practices of rape victims, and (v) determine the relationship between rape and depression, suicide ideation, and suicide attempts. The community's level of rape myth endorsement was also explored. Rape myths were defined as attitudes and beliefs about rape, rape victims, and rapists that are generally false but are widely and persistently held, and serve to deny and justify sexual aggression against women and men. The present study compared rape myth endorsement levels concerning both male and female victims. However, it was first necessary to construct a rape myth questionnaire, the Rape Attitudinal Scale (RAQ), which minimised the methodological limitations of pre-existing scales. The current research utilised online methodology and, in total, 560 individuals participated in the research. It was found that almost two out of every five participants had been a victim of rape during their lifetime, with males accounting for 8.60% of the raped sample. Rape victims emanated from a variety of demographic backgrounds and the gender differences between the characteristics of the rape were discussed. Approximately one in seven rape victims stated that they had reported the rape to police, with half of those rape victims regretting informing the police of their experience. Almost twice as many female rape victims than male rape victims failed to report their rape to anyone. It was also found that victims of rape are more likely to report rape to authorities when the rape fits the "real rape" stereotype. It was evident that the trauma of rape and its overall negative sequelae can persist long after the rape has occurred. It was found that rape victims were significantly more likely than non-victims to be classified as depressed, experience suicidal thoughts and had attempted suicide. It was concluded that the RAQ was a reliable and valid measure of individual's rape myth endorsement levels. The underlying nature of rape myths did not differ between male and female victims of rape, although certain rape myths seem to be more applicable to each gender. The majority of the current sample did not endorse rape myths, however participants from particular demographic backgrounds were more likely than others to endorse rape myths. A small, yet alarming, proportion of the current sample reported that they would be likely to rape someone if they could get away with it. Implications of the current findings were discussed in terms of future rape education campaigns that could increase public awareness, increase reporting rates and hopefully reduce the incidence of rape within our society

Computation of a 30750-Bit Binary Field Discrete Logarithm

This paper reports on the computation of a discrete logarithm in the finite field $\mathbb F_{2^{30750}}$, breaking by a large margin the previous record, which was set in January 2014 by a computation in $\mathbb F_{2^{9234}}$. The present computation made essential use of the elimination step of the quasi-polynomial algorithm due to Granger, Kleinjung and Zumbr\"agel, and is the first large-scale experiment to truly test and successfully demonstrate its potential when applied recursively, which is when it leads to the stated complexity. It required the equivalent of about 2900 core years on a single core of an Intel Xeon Ivy Bridge processor running at 2.6 GHz, which is comparable to the approximately 3100 core years expended for the discrete logarithm record for prime fields, set in a field of bit-length 795, and demonstrates just how much easier the problem is for this level of computational effort. In order to make the computation feasible we introduced several innovative techniques for the elimination of small degree irreducible elements, which meant that we avoided performing any costly Gr\"obner basis computations, in contrast to all previous records since early 2013. While such computations are crucial to the $L(\frac 1 4 + o(1))$ complexity algorithms, they were simply too slow for our purposes. Finally, this computation should serve as a serious deterrent to cryptographers who are still proposing to rely on the discrete logarithm security of such finite fields in applications, despite the existence of two quasi-polynomial algorithms and the prospect of even faster algorithms being developed.Comment: 22 page

Quasihomogeneity of isolated singularities and logarithmic cohomology

We characterize quasihomogeneity of isolated singularities by the injectivity of the map induced by the first differential of the logarithmic differential complex in the top local cohomology supported in the singular point.Comment: 5 page

Standing and travelling waves in the shallow-water circular hydraulic jump

A wave equation for a time-dependent perturbation about the steady shallow-water solution emulates the metric an acoustic white hole, even upon the incorporation of nonlinearity in the lowest order. A standing wave in the sub-critical region of the flow is stabilised by viscosity, and the resulting time scale for the amplitude decay helps in providing a scaling argument for the formation of the hydraulic jump. A standing wave in the super-critical region, on the other hand, displays an unstable character, which, although somewhat mitigated by viscosity, needs nonlinear effects to be saturated. A travelling wave moving upstream from the sub-critical region, destabilises the flow in the vicinity of the jump, for which experimental support has been given.Comment: 9 pages, REVTeX, Additional treatment on travelling waves. Extensively revised in the publised version. Contains a full new section on the role of nonlinearit

DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.Comment: Accepted at JBI under the new name: "Predicting healthcare trajectories from medical records: A deep learning approach