Assignment methods for incidence calculus

Incidence calculus is a mechanism for probabilistic reasoning in which sets of possible worlds, called incidences, are associated with axioms, and probabilities are then associated with these sets. Inference rules are used to deduce bounds on the incidence of formulae which are not axioms, and bounds for the probability of such a formula can then be obtained. In practice an assignment of probabilities directly to axioms may be given, and it is then necessary to find an assignment of incidence which will reproduce these probabilities. We show that this task of assigning incidences can be viewed as a tree searching problem, and two techniques for performing this research are discussed. One of these is a new proposal involving a depth first search, while the other incorporates a random element. A Prolog implementation of these methods has been developed. The two approaches are compared for efficiency and the significance of their results are discussed. Finally we discuss a new proposal for applying techniques from linear programming to incidence calculus.

A comprehensive comparison between generalized incidence calculus and Dempster-Shafer theory of evidence.

Dealing with uncertainty problems in intelligent systems has attracted a lot of attention in the AI community. Quite a few techniques have been proposed. Among them, the Dempster-Shafer theory of evidence (DS theory) has been widely appreciated. In DS theory, Dempster's combination rule plays a major role. However, it has been pointed out that the application domains of the rule are rather limited and the application of the theory sometimes gives unexpected results. We have previously explored the problem with Dempster's combination rule and proposed an alternative combination mechanism in generalized incidence calculus. In this paper we give a comprehensive comparison between generalized incidence calculus and the Dempster-Shafer theory of evidence. We first prove that these two theories have the same ability in representing evidence and combining DS-independent evidence. We then show that the new approach can deal with some dependent situations while Dempster's combination rule cannot. Various examples in the paper show the ways of using generalized incidence calculus in expert systems.

Constructing probabilistic ATMS using extended incidence calculus

This paper discusses the relations between extended incidence calculus and assumption-based truth maintenance systems (ATMSs). We first prove that managing labels for statements (nodes) in an ATMS is equivalent to producing incidence sets of these statements in extended incidence calculus. We then demonstrate that the justification set for a node is functionally equivalent to the implication relation set for the same node in extended incidence calculus. As a consequence, extended incidence calculus can provide justifications for an ATMS, because implication relation sets are discovered by the system automatically. We also show that extended incidence calculus provides a theoretical basis for constructing a probabilistic ATMS by associating proper probability distributions on assumptions. In this way, we can not only produce labels for all nodes in the system, but also calculate the probability of any of such nodes in it. The nogood environments can also be obtained automatically. Therefore, extended incidence calculus and the ATMS are equivalent in carrying out inferences at both the symbolic level and the numerical level. This extends a result due to Laskey and Lehner.

Comparative repeatability of two handheld fractional exhaled nitric oxide monitors.

Background The use of portable fractional exhaled nitric oxide (FENO) devices is increasingly common in the diagnosis and management of allergic airways inflammation. Methods We tested two handheld FENO devices, to determine (a) if there was adequate intradevice repeatability to allow the use of single breath testing, and (b) if the devices could be used interchangeably. In a mixed pediatric population, including normal, asthmatic, and children with peanut allergies, 858 paired values were collected from the NIOX-MINO® and/or the NObreath® devices. Results The NIOX-MINO® showed excellent repeatability (mean difference of 0.1 with 95% limits of agreement between -7.93 to 7.72?ppb), while the NObreath® showed good repeatability (mean difference of -1.61 with 95% limits of agreement between -14.1 and 10.8?ppb). Intradevice repeatability was good but not adequate and the NIOX-MINO® systematically produced higher results than the NObreath® [mean difference of 7.8?ppb with 95% limits of agreement from -11.55 to 27.52?ppb (-33% to 290%)]. Conclusions Our results support the manufacturer's advice that single breath testing is appropriate for the NIOX-MINO®. NObreath® results indicate that the mean of more than one breath should be utilized. The devices cannot be used interchangeably. Pediatr Pulmonol. © 2011 Wiley Periodicals, Inc.

White matter fractional anisotrophy predicts balance performance in older adults

Aging is characterized by brain structural changes that may compromise motor functions. In the context of postural control, white matter integrity is crucial for the efficient transfer of visual, proprioceptive and vestibular feedback in the brain. To determine the role of age-related white matter decline as a function of the sensory feedback necessary to correct posture, we acquired diffusion weighted images in young and old subjects. A force platform was used to measure changes in body posture under conditions of compromised proprioceptive and/or visual feedback. In the young group, no significant brain structure-balance relations were found. In the elderly however, the integrity of a cluster in the frontal forceps explained 21% of the variance in postural control when proprioceptive information was compromised. Additionally, when only the vestibular system supplied reliable information, the occipital forceps was the best predictor of balance performance (42%). Age-related white matter decline may thus be predictive of balance performance in the elderly when sensory systems start to degrade.

The Utility of Fractional Exhaled Nitric Oxide Suppression in the Identification of Nonadherence in Difficult Asthma

Rationale: Nonadherence to inhaled corticosteroid therapy (ICS) is a major contributor to poor control in difficult asthma, yet it is challenging to ascertain. Objectives: Identify a test for nonadherence using fractional exhaled nitric oxide (FENO) suppression after directly observed inhaled corticosteroid (DOICS) treatment. Methods: Difficult asthma patients with an elevated FENO (>45 ppb) were recruited as adherent (ICS prescription filling >80%) or nonadherent (filling <50%). They received 7 days of DOICS (budesonide 1,600 µg) and a test for nonadherence based on changes in FENO was developed. Using this test, clinic patients were prospectively classified as adherent or nonadherent and this was then validated against prescription filling records, prednisolone assay, and concordance interview. Measurements and Main Results: After 7 days of DOICS nonadherent (n = 9) compared with adherent subjects (n = 13) had a greater reduction in FENO to 47 ± 21% versus 79 ± 26% of baseline measurement (P = 0.003), which was also evident after 5 days (P = 0.02) and a FENO test for nonadherence (area under the curve = 0.86; 95% confidence interval, 0.68-1.00) was defined. Prospective validation in 40 subjects found the test identified 13 as nonadherent; eight confirmed nonadherence during interview (three of whom had excellent prescription filling but did not take medication), five denied nonadherence, two had poor inhaler technique (unintentional nonadherence), and one also denied nonadherence to prednisolone despite nonadherent blood level. Twenty-seven participants were adherent on testing, which was confirmed in 21. Five admitted poor ICS adherence but of these, four were adherent with oral steroids and one with omalizumab. Conclusions: FENO suppression after DOICS provides an objective test to distinguish adherent from nonadherent patients with difficult asthma. Clinical trial registered with www.clinicaltrials.gov (NCT 01219036). Copyright © 2012 by the American Thoracic Society.

Model categories for orthogonal calculus

We restate the notion of orthogonal calculus in terms of model categories. This provides a cleaner set of results and makes the role of O(n)-equivariance clearer. Thus we develop model structures for the category of n-polynomial and n-homogeneous functors, along with Quillen pairs relating them. We then classify n-homogeneous functors, via a zig-zag of Quillen equivalences, in terms of spectra with an O(n)-action. This improves upon the classification theorem of Weiss. As an application, we develop a variant of orthogonal calculus by replacing topological spaces with orthogonal spectra.

Belief change with noisy sensing in the situation calculus

Situation calculus has been applied widely in arti?cial intelligence to model and reason about actions and changes in dynamic systems. Since actions carried out by agents will cause constant changes of the agents’ beliefs, how to manage
these changes is a very important issue. Shapiro et al. [22] is one of the studies that considered this issue. However, in this framework, the problem of noisy sensing, which often presents in real-world applications, is not considered. As a
consequence, noisy sensing actions in this framework will lead to an agent facing inconsistent situation and subsequently the agent cannot proceed further. In this paper, we investigate how noisy sensing actions can be handled in iterated
belief change within the situation calculus formalism. We extend the framework proposed in [22] with the capability of managing noisy sensings. We demonstrate that an agent can still detect the actual situation when the ratio of noisy sensing actions vs. accurate sensing actions is limited. We prove that our framework subsumes the iterated belief change strategy in [22] when all sensing actions are accurate. Furthermore, we prove that our framework can adequately handle belief introspection, mistaken beliefs, belief revision and belief update even with noisy sensing, as done in [22] with accurate sensing actions only.