Belief Revision in Structured Probabilistic Argumentation

In real-world applications, knowledge bases consisting of all the information at hand for a specific domain, along with the current state of affairs, are bound to contain contradictory data coming from different sources, as well as data with varying degrees of uncertainty attached. Likewise, an important aspect of the effort associated with maintaining knowledge bases is deciding what information is no longer useful; pieces of information (such as intelligence reports) may be outdated, may come from sources that have recently been discovered to be of low quality, or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing the basic issues of handling contradictory and uncertain data. Then, to address the last issue, we focus on the study of non-prioritized belief revision operations over probabilistic PreDeLP programs. We propose a set of rationality postulates -- based on well-known ones developed for classical knowledge bases -- that characterize how such operations should behave, and study a class of operators along with theoretical relationships with the proposed postulates, including a representation theorem stating the equivalence between this class and the class of operators characterized by the postulates

A Case-Control Study of Factors Associated with Non-Adherent to Antiretroviral Therapy Among HIV Infected People in Pwani Region, Eastern Tanzania

Non-adherence is one of the major causes of treatment failure which leads to increased morbidity and mortality caused by opportunistic infections. Optimal anti-retroviral therapy (ART) adherence is essential for maximal suppression of viral replication and long term survival of patients. In order to develop effective public health interventions in the context of scaling ART services to peripheral areas, it is important to evaluate factors associated with non-adherence among HIV-infected individuals in Pwani Region. The purpose of this study was to identify factors related to non-adherence to ART among HIV infected people in Pwani Region eastern of Tanzania. A case-control study was carried out at Tumbi Hospital and Chalinze Health Centre in Pwani Region in eastern Tanzania. A structured questionnaire was used to assess non-adherence and adherence to doses instruction and time schedule. Patients with less than 95% adherence were defined as cases while those with more than 95% adherence became controls. A structured questionnaire containing factors known to be associated with non-adherence to ART in similar settings was administered. Univariate and multivariate conditional logistic regression was performed to identify factors associated with non-adherence. A total of 79 cases and 237 controls matched by age and sex were studied. A high proportion of cases and controls (77.2% and 84.8%) had good knowledge of ART benefits, adherence and eligibility. Majority of cases (73.3%) and controls (69.2%) used public transport to access ART services. More than half of cases (53.2%) missed clinic appointments due to lack of bus fare or other reasons and was associated with ART non adherence (mOR 4.2, 95%CI, 2.2-8.1 and 2.1,95%CI 1.2-4.2). Disclosure to confidants only and failure to disclose HIV-test positive status were associated with non adherence (mOR 3.3, 95%CI 1.3-8.5 and 2.3, 95%CI 1.2-7.1). Alcohol use was associated with non adherence to ART (mOR 1.9, 95%CI 1.4-3.7). Patients who were not satisfied with providers were more likely to be non adherence to ART (mOR 2.0, 95%CI 1.2-3.8). In conclusion, these findings show that adherence is a process which is depended on local specific adherence factors. Adherence improvement strategies need to consider site specific adherence determinants, patient experiences and concern

Rich environments for active learning in action: Problem‐based learning

Rich Environments for Active Learning (REALs) are comprehensive instructional systems that are consistent with constructivist theories. They promote study and investigation within authentic contexts; encourage the growth of student responsibility, initiative, decision making and intentional learning; cultivate collaboration among students and teachers; utilize dynamic, interdisciplinary, generative learning activities that promote higher‐order thinking processes to help students develop rich and complex knowledge structures; and assess student progress in content and learning‐to‐learn within authentic contexts using realistic tasks and performances. Problem‐Based Learning (PBL) is an instructional methodology that can be used to create REALs. PBL's student‐centred approach engages students in a continuous collaborative process of building and reshaping understanding as a natural consequence of their experiences and interactions within learning environments that authentically reflect the world around them. In this way, PBL and REALs are a response to teacher‐centred educational practices that promote the development of inert knowledge, such as conventional teacher‐to‐student knowledge dissemination activities. In this article, we compare existing assumptions underlying teacher‐directed educational practice with new assumptions that promote problem solving and higher‐level thinking by putting students at the centre of learning activities. We also examine the theoretical foundation that supports these new assumptions and the need for REALs. Finally, we describe each REAL characteristic and provide supporting examples of REALs in action using PB