Learning about knowledge: A complex network approach

This article describes an approach to modeling knowledge acquisition in terms of walks along complex networks. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks, i.e. networks composed of successive interconnected layers, arise naturally as a consequence of compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks, i.e. unreachable nodes, the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barab\'asi-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaux of knowledge stagnation in the case of the preferential movements strategy in presence of conditional edges.Comment: 18 pages, 19 figure

Access to shops: The views of low-income shoppers

Concern is mounting as the retail stranglehold upon access to food grows. Research on the implications of restructuring retailing and health inequality has failed to involve low-income consumers in this debate. This paper reports on an exercise conducted for the UK Government's, Social Exclusion Unit's Policy Action Team on Access to Shops. The survey provides a useful baseline of the views of low-income groups in England. The choices that people on low income can make were found to be dominated by certain factors such as income and, most importantly, transport. Consumers reported varying levels of satisfaction with retail provision. The findings suggest gaps between what people have, what they want and what the planning process does and does not offer them. Better policy and processes are needed to include and represent the interests of low-income groups

Service orchestration with priority constraints

Business process management is an operational management approach that focuses on improving business processes. Business processes, i.e., collections of important activities in an organization, are represented in the form of a workflow, an orchestrated and repeatable pattern of activities amenable to automated analysis and control. Priority is an important concept in modeling workflows. We need priority to model cancelable and compensable tasks within transactional business processes. We use the Reo coordination language to model and formally analyze workflows. In this paper, we propose a constraint-based approach to formalize priority in Reo. We introduce special channels to propagate and block priority flows, define their semantics as constraints, and model priority propagation as a constraint satisfaction problem

Neonicotinoid seed treatments of soybean provide negligible benefits to US farmers

Neonicotinoids are the most widely used insecticides worldwide and are typically deployed as seed treatments (hereafter NST) in many grain and oilseed crops, including soybeans. However, there is a surprising dearth of information regarding NST effectiveness in increasing soybean seed yield, and most published data suggest weak, or inconsistent yield benefit. The US is the key soybean-producing nation worldwide and this work includes soybean yield data from 194 randomized and replicated field studies conducted specifically to evaluate the effect of NSTs on soybean seed yield at sites within 14 states from 2006 through 2017. Here we show that across the principal soybean-growing region of the country, there are negligible and management-specific yield benefits attributed to NSTs. Across the entire region, the maximum observed yield benefits due to fungicide (FST = fungicide seed treatment) + neonicotinoid use (FST + NST) reached 0.13 Mg/ha. Across the entire region, combinations of management practices affected the effectiveness of FST + N ST to increase yield but benefits were minimal ranging between 0.01 to 0.22 Mg/ha. Despite widespread use, this practice appears to have little benefit for most of soybean producers; across the entire region, a partial economic analysis further showed inconsistent evidence of a break-even cost of FST or FST + N ST. These results demonstrate that the current widespread prophylactic use of NST in the key soybean-producing areas of the US should be re-evaluated by producers and regulators alike

Neonicotinoid seed treatments of soybean provide negligible benefits to US farmers

Neonicotinoids are the most widely used insecticides worldwide and are typically deployed as seed treatments (hereafter NST) in many grain and oilseed crops, including soybeans. However, there is a surprising dearth of information regarding NST effectiveness in increasing soybean seed yield, and most published data suggest weak, or inconsistent yield benefit. The US is the key soybean-producing nation worldwide and this work includes soybean yield data from 194 randomized and replicated field studies conducted specifically to evaluate the effect of NSTs on soybean seed yield at sites within 14 states from 2006 through 2017. Here we show that across the principal soybean-growing region of the country, there are negligible and management-specific yield benefits attributed to NSTs. Across the entire region, the maximum observed yield benefits due to fungicide (FST = fungicide seed treatment) + neonicotinoid use (FST + NST) reached 0.13 Mg/ha. Across the entire region, combinations of management practices affected the effectiveness of FST + N ST to increase yield but benefits were minimal ranging between 0.01 to 0.22 Mg/ha. Despite widespread use, this practice appears to have little benefit for most of soybean producers; across the entire region, a partial economic analysis further showed inconsistent evidence of a break-even cost of FST or FST + N ST. These results demonstrate that the current widespread prophylactic use of NST in the key soybean-producing areas of the US should be re-evaluated by producers and regulators alike

Comparing Petri Net and Activity Diagram Variants for Workflow Modelling:A Quest for Reactive Petri Nets

Petri net variants are widely used as a workflow modelling technique. Recently, UMLa ctivity diagrams have been used for the same purpose, even though the syntax and semantics of activity diagrams has not been yet fully worked out. Nevertheless, activity diagrams seem very similar to Petri nets and on the surface, one may think that they are variants of each other. To substantiate or deny this claim, we need to formalise the intended semantics of activity diagrams and then compare this with various Petri net semantics. In previous papers we have defined two formal semantics for UMLact ivity diagrams that are intended for workflow modelling. In this paper, we discuss the design choices that underlie these two semantics and investigate whether these design choices can be met in low-level and high-level Petri net semantics. We argue that the main difference between the Petri net semantics and our semantics of UML act ivity diagrams is that the Petri net semantics models resource usage of closed, active systems that are non-reactive, whereas our semantics of UMLact ivity diagrams models open, reactive systems. Since workflow systems are open, reactive systems, we conclude that Petri nets cannot model workflows accurately, unless they are extended with a syntax and semantics for reactivity

Is the Public willing to help the Nigerian Police during the Boko Haram crisis? A look at moderating factors.

This paper sought the opinion of 200 Nigerians on their willingness to cooperate with the Police during the Boko Haram crisis. Public perceptions of Police effectiveness during the crisis, residence location, gender and religious affiliation were used as moderators. Data was analysed using an explanatory factor analysis and structural equation modelling. Results indicated a strong association between perceived effectiveness and willingness to report to the Police with respondents who question the effectiveness of the Police being less likely to be willing to report criminal activity about Boko Haram. Further to this, the impact of religion on willingness to report was at least partially mediated by perceived effectiveness of the Police with the results showing that Christian respondents perceived the Police as less effective. Females and those living in the North were significantly less willing to report criminal activity to the Police The findings are then discussed in relation to the BH crises and directions for future research are given