South African Tuberculosis Vaccine Initiative
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An Architecture for Generating Questions, Answers, and Feedback from Ontologies
Full text linkAutomatically generating questions, answers, and feedback
from ontologies and conceptual models is crucial for learning activities
and knowledge validation. Existing proposals are limited to predefined
types of questions and the modelling style that they are tailored to, lack
feedback generation, and their core algorithm are dependent on those
characteristics, therewith hampering maintainability and reusability. We
designed a new architecture where the question, answer and feedback
specifications, the core algorithm for selecting the contents from the ontology,
and the verbaliser are modularised for resolving these problems.
We instantiated the architecture as a proof-of-concept, examined three
test cases, and showed that it compares favourably to related work
Evolving Behavior Allocations in Robot Swarms
Full text linkBehavioral diversity is known to benefit problem solving
in biological social systems such as insect colonies and human
societies, as well as in artificial distributed systems including
large-scale software and swarm-robotics systems. We investigate
methods of evolving robot swarms in which individuals have
heterogeneous behaviours. Two approaches are investigated to
create swarm of size n. The first encodes a repertoire of n
behaviours on a single individual, and hence evolves the swarm
directly. The second approach uses two phases. First, a large
repertoire of diverse behaviours is evolved and then another
evolutionary algorithm is used to search for an optimal allocation
of behaviours to the swarm. Results indicate that the two phase
approach of generate then allocate produces significantly more
effective collective behaviors (in terms of task accomplishment)
than the direct evolution of behaviorally heterogeneous swarms
“Must you make an app?” A qualitative exploration of socio-technical challenges and opportunities for designing digital maternal and child health solutions in Soweto, South Africa
Full text linkParticipatory and digital health approaches have the potential to create solutions to health issues and related inequalities. A project called Co-Designing Community-based ICTs Interventions for Maternal and Child Health in South Africa (CoMaCH) is exploring such solutions in four different sites across South Africa. The present study captures initial qualitative research that was carried out in one of the urban research sites in Soweto. The aim was two-fold: 1) to develop a situation analysis of existing services and the practices and preferences of intended end-users, and 2) to explore barriers and facilitators to utilising digital health for community-based solutions to maternal and child health from multiple perspectives. Semi-structured interviews were conducted with 28 participants, including mothers, other caregivers and community health workers. Four themes were developed using a framework method approach to thematic analysis: coping as a parent is a priority; existing services and initiatives lack consistency, coverage and effective communication; the promise of technology is limited by cost, accessibility and crime; and, information is key but difficult to navigate. Solutions proposed by participants included various digital-based and non-digital channels for accessing reliable health information or education; community engagement events and
social support; and, community organisations and initiatives such as saving schemes or
community gardens. This initial qualitative study informs later co-design phases, and raises ethical and practical questions about participatory intervention development, including the flexibility of researcher-driven endeavours to accommodate community views, and the limits of digital health solutions vis-à-vis material needs and structural barriers to health and wellbeing
Do People in Low Resource Environments only Need Search? Exploring Digital Archive Functionalities in South Africa
Full text linkExisting user studies on how users use digital archives as information systems seldom
focus on what influences users’ needs and expectations. Similarly, not much is known about
how the low resource context influences users’ needs. What users expect from searching
and other related functionalities is rarely addressed in the cultural heritage and historical
digital archives. These gaps unveil the mismatch between users’ needs (and expectations)
and deployed technologies in the low resource context. As a result, delivering novel services
through these digital archives is impossible because of the gap between design and reality.
Users in the low resource environment are thus constrained to use whatever functionalities
are available. This paper presents the empirical result of a user study. We determined the
study’s sample framing using the future determination analysis technique. This analysis
also guided the scoping of the study’s survey. The study foregrounds the need to adapt to
users’ ever-changing expectations by understanding their needs. This is critical for a better
system design that meets users’ expectations. A key finding is that users strongly prefer
simple search functionalities in low-resource environments. Regardless, they would prefer
to use advanced features if given the opportunity. However, the expertise (and sometimes
funding) needed to satisfy this desire is scarce. The surveyed users are only end-users
without the expertise to innovate and build digital archives to meet their needs. This
dearth of “resource(s)” was found to be characteristic of the experience of low resource (or resource-poor) settings like South Africa
Modeling of pneumococcal serogroup 10 capsular polysaccharide molecular conformations provides insight into epitopes and observed cross-reactivity.
Full text linkStreptococcus pneumoniae is an encapsulated gram-negative bacterium and a significant human pathogen. The capsular polysaccharide (CPS) is essential for virulence and a target antigen for vaccines. Although widespread introduction of pneumococcal conjugate vaccines (PCVs) has significantly reduced disease, the prevalence of non-vaccine serotypes has increased. On the basis of the CPS, S. pneumoniae serogroup 10 comprises four main serotypes 10A, 10B, 10C, and 10F; as well as the recently identified 10D. As it is the most prevalent, serotype 10A CPS has been included as a vaccine antigen in the next generation PCVs. Here we use molecular modeling to provide conformational rationales for the complex cross-reactivity reported between serotypes 10A, 10B, 10C, and 10F anti-sera. Although the highly mobile phosphodiester linkages produce very flexible CPS, shorter segments are conformationally defined, with exposed β-D-galactofuranose (β DGalf) side chains that are potential antibody binding sites. We identify four distinct conformational epitopes for the immunodominant β DGalf that assist in rationalizing the complex asymmetric cross-reactivity relationships. In particular, we find that strongly cross-reactive serotypes share common epitopes. Further, we show that human intelectin-1 has the potential to bind the exposed exocyclic 1,2-diol of the terminal β DGalf in each serotype; the relative accessibility of three- or six-linked β DGalf may play a role in the strength of the innate immune response and hence serotype disease prevalence. In conclusion, our modeling study and relevant serological studies support the inclusion of serotype 10A in a vaccine to best protect against serogroup 10 disease
Do Harsher Environments cause Selfish or Altruistic Behavior
Full text linkIn this study we develop an Agent-based Model (ABM), called Neo-
COOP, to investigate the emergence and evolution of altruistic
and selfish behaviour in Neolithic-inspired household agents under
varying degrees of environmental stress. We conduct scenario
experimentation where we track the evolution of the agents’ resource
trading preferences in scenarios with varying frequencies of
environmental stress and agent types initialized to exhibit differing
altruistic or selfish tendencies. Our results suggest that neither extreme
selfishness or extreme altruism is desirable but rather, some
middle-ground value is. Additionally, we find that the frequency of
the environmental stress plays a significant role in the emergence
of selfish behaviour amongst the social elite with higher frequency
environmental stress scenarios resulting in a greater disparity of
resource transfer beliefs between agents with equal social status
Extreme Environments Perpetuate Cooperation
Full text linkWe investigate whether environmental stress positively
impacts the emergence of cooperative behaviour in socially
stratified societies. We achieve this by utilizing NeoCOOP, an
ABM that uses artificial evolution as adaptive mechanisms to
simulate the emergence and evolution of altruistic and selfish
behaviour in Neolithic-inspired agents. We perform scenario
experimentation whereby we monitor the resource trading preferences
of these agents by varying the frequency of environmental
stress and the initial beliefs of said agents. Our results indicate
that in extreme conditions, altruism is preferred. Furthermore,
our results suggest that the degree of social stratification of a
population is positively related to its ability to maintain logisticlike
growth while remaining susceptible to environmental stress
Extreme Environments Perpetuate Cooperation
Full text linkWe investigate whether environmental stress positively
impacts the emergence of cooperative behaviour in socially
stratified societies. We achieve this by utilizing NeoCOOP, an
ABM that uses artificial evolution as adaptive mechanisms to
simulate the emergence and evolution of altruistic and selfish
behaviour in Neolithic-inspired agents. We perform scenario
experimentation whereby we monitor the resource trading preferences
of these agents by varying the frequency of environmental
stress and the initial beliefs of said agents. Our results indicate
that in extreme conditions, altruism is preferred. Furthermore,
our results suggest that the degree of social stratification of a
population is positively related to its ability to maintain logisticlike
growth while remaining susceptible to environmental stress
Extreme Environments Perpetuate Cooperation
Full text linkWe investigate whether environmental stress positively
impacts the emergence of cooperative behaviour in socially
stratified societies. We achieve this by utilizing NeoCOOP, an
ABM that uses artificial evolution as adaptive mechanisms to
simulate the emergence and evolution of altruistic and selfish
behaviour in Neolithic-inspired agents. We perform scenario
experimentation whereby we monitor the resource trading preferences
of these agents by varying the frequency of environmental
stress and the initial beliefs of said agents. Our results indicate
that in extreme conditions, altruism is preferred. Furthermore,
our results suggest that the degree of social stratification of a
population is positively related to its ability to maintain logisticlike
growth while remaining susceptible to environmental stress
Gradient Terrain Authoring
No full textDigital terrains are a foundational element in the computer-generated depiction of natural scenes. Given the variety and complexity of real-world landforms, there is a need for authoring solutions that achieve perceptually realistic outcomes without sacrificing artistic control. In this paper, we propose setting aside the elevation domain in favour of modelling in the gradient domain. Such a slope-based representation is height independent and allows a seamless blending of disparate landforms from procedural, simulation, and real-world sources. For output, an elevation model can always be recovered using Poisson reconstruction, which can include Dirichlet conditions to constrain the elevation of points and curves.
In terms of authoring our approach has numerous benefits. It provides artists with a complete toolbox, including: cut-and-paste operations that support warping as needed to fit the destination terrain, brushes to modify region characteristics, and sketching to provide point and curve constraints on both elevation and gradient. It is also a unifying representation that enables the inclusion of tools from the spectrum of existing procedural and simulation methods, such as painting localised high-frequency noise or hydraulic erosion, without breaking the formalism. Finally, our constrained reconstruction is GPU optimized and executes in real-time, which promotes productive cycles of iterative authoring