Leaf epidermal profiling as a phenotyping tool for DNA methylation mutants

Phenotypic evaluation of epigenetic mutants is mainly based on the analysis of plant growth and morphological features. However, there are cellular level changes that are not visible to the naked eye and require analysis with higher resolution techniques. In this study, we carried out a phenotypic characterisation of several Arabidopsis thaliana hypomethylation mutants by quantitative image analysis combined with flow cytometry. This phenotyping approach permitted identification of abnormalities at the cellular level in mutants with wild-type morphology at the organ level. Morphometry of adaxial leaf epidermis revealed variations in the size and number of pavement cells, and the density and distribution of stomata in the analysed second rosette leaves from the mutants studied. A direct correlation between DNA ploidy status and leaf pavement cell size in wild type and mutant leaves was observed. Recognition of hidden phenotypic variations could facilitate the identification of key genetic loci underlying the phenotypes caused by modifications of DNA methylation. Thus, this study outlines an easy and fast phenotyping strategy that can be used as a reliable tool for characterisation of epigenetic mutants at the cellular level

Motivational Social Visualizations for Personalized E-Learning

A large number of educational resources is now available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produces at least two problems: how to help students find the most appropriate resources, and how to engage them into using these resources and benefiting from them. Personalized and social learning have been suggested as potential methods for addressing these problems. Our work presented in this paper attempts to combine the ideas of personalized and social learning. We introduce Progressor + , an innovative Web-based interface that helps students find the most relevant resources in a large collection of self-assessment questions and programming examples. We also present the results of a classroom study of the Progressor +  in an undergraduate class. The data revealed the motivational impact of the personalized social guidance provided by the system in the target context. The interface encouraged students to explore more educational resources and motivated them to do some work ahead of the course schedule. The increase in diversity of explored content resulted in improving students’ problem solving success. A deeper analysis of the social guidance mechanism revealed that it is based on the leading behavior of the strong students, who discovered the most relevant resources and created trails for weaker students to follow. The study results also demonstrate that students were more engaged with the system: they spent more time in working with self-assessment questions and annotated examples, attempted more questions, and achieved higher success rates in answering them

QuizMap: Open social student modeling and adaptive navigation support with TreeMaps

In this paper, we present a novel approach to integrate social adaptive navigation support for self-assessment questions with an open student model using QuizMap, a TreeMap-based interface. By exposing student model in contrast to student peers and the whole class, QuizMap attempts to provide social guidance and increase student performance. The paper explains the nature of the QuizMap approach and its implementation in the context of self-assessment questions for Java programming. It also presents the design of a semester-long classroom study that we ran to evaluate QuizMap and reports the evaluation results. © 2011 Springer-Verlag Berlin Heidelberg

Mediated behavioural change in human-machine networks: exploring network characteristics, trust and motivation

Human-machine networks pervade much of contemporary life. Network change is the product of structural modifications along with differences in participant be-havior. If we assume that behavioural change in a human-machine network is the result of changing the attitudes of participants in the network, then the question arises whether network structure can affect participant attitude. Taking citizen par-ticipation as an example, engagement with relevant stakeholders reveals trust and motivation to be the major objectives for the network. Using a typology to de-scribe network state based on multiple characteristic or dimensions, we can pre-dict possible behavioural outcomes in the network. However, this has to be medi-ated via attitude change. Motivation for the citizen participation network can only increase in line with enhanced trust. The focus for changing network dynamics, therefore, shifts to the dimensional changes needed to encourage increased trust. It turns out that the coordinated manipulation of multiple dimensions is needed to bring about the desired shift in attitude.Comment: Paper submitted to SocInfo, organised by the Oxford Internet Institute, September 201

Multifaceted open social learner modelling

Open social learner modelling (OSLM) approaches are promoted in order to assist learners in self-directed and self-determined learning in a social context. Still, most approaches only focus on visualising learners’ performance, or providing complex tools for social navigation. Our proposal, additionally, emphasises the importance of visualising both learners’ performance and their contribution to a learning community. We seek also to seamlessly integrate OSLM with learning contents, in order for the multifaceted OSLM’s prospect for ubiquity and context-awareness to enrich the adaptive potential of social e-learning systems. This paper thus presents the design of multifaceted OSLM by introducing novel, personalised social interaction features into Topolor, a social personalised adaptive e-learning environment. The umbrella target is to create and study aspects of open social learner models. An experimental study is conducted to analyse the impact of the newly introduced features. The results are finally concluded to suggest future research and further improvements

Direct measurements of the effects of salt and surfactant on interaction forces between colloidal particles at water-oil interfaces

The forces between colloidal particles at a decane-water interface, in the presence of low concentrations of a monovalent salt (NaCl) and of the surfactant sodium dodecylsulfate (SDS) in the aqueous subphase, have been studied using laser tweezers. In the absence of electrolyte and surfactant, particle interactions exhibit a long-range repulsion, yet the variation of the interaction for different particle pairs is found to be considerable. Averaging over several particle pairs was hence found to be necessary to obtain reliable assessment of the effects of salt and surfactant. It has previously been suggested that the repulsion is consistent with electrostatic interactions between a small number of dissociated charges in the oil phase, leading to a decay with distance to the power -4 and an absence of any effect of electrolyte concentration. However, the present work demonstrates that increasing the electrolyte concentration does yield, on average, a reduction of the magnitude of the interaction force with electrolyte concentration. This implies that charges on the water side also contribute significantly to the electrostatic interactions. An increase in the concentration of SDS leads to a similar decrease of the interaction force. Moreover the repulsion at fixed SDS concentrations decreases over longer times. Finally, measurements of three-body interactions provide insight into the anisotropic nature of the interactions. The unique time-dependent and anisotropic interactions between particles at the oil-water interface allow tailoring of the aggregation kinetics and structure of the suspension structure.Comment: Submitted to Langmui

Constructive and Destructive Processes During the 2018–2019 Eruption Episode at Shiveluch Volcano, Kamchatka, Studied From Satellite and Aerial Data

Dome-building volcanoes often develop by intrusion and extrusion, recurrent destabilization and sector collapses, and renewed volcanic growth inside the collapse embayment. However, details of the structural architecture affiliated with renewed volcanic activity and the influences of regional structures remain poorly understood. Here, we analyze the recent activity of Shiveluch volcano, Kamchatka Peninsula, characterized by repeated episodes of lava dome growth and destruction due to large explosions and gravity-driven collapses. We collect and process a multisensor dataset comprising high-resolution optical (aerial and tri-stereo Pleiades satellite), radar (TerraSAR-X and TanDEM-X satellites), and thermal (aerial and MODIS, Sentinel-2, and Landsat 8 satellites) data. We investigate the evolution of the 2018–2019 eruption episode and evaluate the morphological and structural changes that led to the August 29, 2019 explosive eruption and partial dome collapse. Our results show that a new massive lava lobe gradually extruded onto the SW flank of the dome, concurrent with magmatic intrusion into the eastern dome sector, adding 0.15 km3 to the lava dome complex. As the amphitheater infilled, new eruption craters emerged along a SW-NE alignment close to the amphitheater rim. Then, the large August 29, 2019 explosive eruption occurred, followed by partial dome collapse, which was initially directed away from this SW-NE trend. The eruption and collapse removed 0.11 km3 of the dome edifice and led to the formation of a new central SW-NE-elongated crater with dimensions of 430 m × 490 m, a collapse scar at the eastern part of the dome, and pyroclastic density currents that traveled ∼12 km downslope. This work sheds light on the structural architecture dominated by a SW-NE lineament and the complex interplay of volcano constructive and destructive processes. We develop a conceptual model emphasizing the relevance of structural trends, namely, 1) a SW-NE-oriented (possibly regional) structure and 2) the infilled amphitheater and its decollement surface, both of which are vital for understanding the directions of growth and collapse and for assessing the potential hazards at both Shiveluch and dome-building volcanoes elsewhere

Efficacy assessment of sustained intraperitoneal paclitaxel therapy in a murine model of ovarian cancer using bioluminescent imaging

We evaluated the pre-clinical efficacy of a novel intraperitoneal (i.p.) sustained-release paclitaxel formulation (PTXePC) using bioluminescent imaging (BLI) in the treatment of ovarian cancer. Human ovarian carcinoma cells stably expressing the firefly luciferase gene (SKOV3Luc) were injected i.p. into SCID mice. Tumour growth was evaluated during sustained or intermittent courses of i.p. treatment with paclitaxel (PTX). In vitro bioluminescence strongly correlated with cell survival and cytotoxicity. Bioluminescent imaging detected tumours before their macroscopic appearance and strongly correlated with tumour weight and survival. As compared with intermittent therapy with Taxol®, sustained PTXePC therapy resulted in significant reduction of tumour proliferation, weight and BLI signal intensity, enhanced apoptosis and increased survival times. Our results demonstrate that BLI is a useful tool in the pre-clinical evaluation of therapeutic interventions for ovarian cancer. Moreover, these results provide evidence of enhanced therapeutic efficacy with the sustained PTXePC implant system, which could potentially translate into successful clinical outcomes