High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Personal Learning Environments – Um Ecossistema de Aprendizagem em e-Learning

Esta investigação tem como tema de estudo os ambientes pessoais de aprendizagem que se podem desenvolver em e-learning. Estes ambientes com características singulares, face ao atual estado de desenvolvimento tecnológico e social, têm sido designados na doutrina científica pela expressão anglo-saxónica Personal Learning Environments, da qual derivam os acrónimos PLE ou PLEs. Este estudo tem, como objetivo, compreender o papel dos PLEs na aprendizagem dos alunos da parte letiva do Mestrado em Gestão de Sistemas de e-Learning, da Faculdade de Ciências Sociais e Humanas da Universidade Nova de Lisboa, nos biénios que decorreram de 2010-2011 a 2012-2013. Estes alunos, ao longo da sua aprendizagem, utilizaram várias ferramentas e/ou serviços associados com as TIC e Web 2.0. Esta utilização permitiu aos alunos criarem um ecossistema de aprendizagem próprio. A metodologia de investigação utilizada teve em consideração sobretudo aspetos qualitativos. A estratégia utilizada para a recolha de informações foi o inquérito por questionário. As informações recolhidas foram sujeitas a tratamento estatístico descritivo, e posterior triangulação dos resultados de algumas das variáveis.Dos resultados obtidos, é possível concluir que os alunos do Mestrado criaram os seus próprios PLEs e que estes facilitaram as suas aprendizagens. Que a sua utilização conferiu vantagens aos alunos. Que os PLEs foram fundamentais para poderem desenvolver atividades colaborativas, e que criaram um ecossistema próprio, uma rede de troca de conhecimentos.

Peer interaction and learning opportunities in cohesive and less cohesive L2 classrooms

The present study investigates peer to peer oral interaction in two task based language teaching classrooms, one of which was a self-declared cohesive group, and the other a self- declared less cohesive group, both at B1 level. It studies how learners talk cohesion into being and considers how this talk leads to learning opportunities in these groups. The study was classroom-based and was carried out over the period of an academic year. Research was conducted in the classrooms and the tasks were part of regular class work. The research was framed within a sociocognitive perspective of second language learning and data came from a number of sources, namely questionnaires, interviews and audio recorded talk of dyads, triads and groups of four students completing a total of eight oral tasks. These audio recordings were transcribed and analysed qualitatively for interactions which encouraged a positive social dimension and behaviours which led to learning opportunities, using conversation analysis. In addition, recordings were analysed quantitatively for learning opportunities and quantity and quality of language produced. Results show that learners in both classes exhibited multiple behaviours in interaction which could promote a positive social dimension, although behaviours which could discourage positive affect amongst group members were also found. Analysis of interactions also revealed the many ways in which learners in both the cohesive and less cohesive class created learning opportunities. Further qualitative analysis of these interactions showed that a number of factors including how learners approach a task, the decisions they make at zones of interactional transition and the affective relationship between participants influence the amount of learning opportunities created, as well as the quality and quantity of language produced. The main conclusion of the study is that it is not the cohesive nature of the group as a whole but the nature of the relationship between the individual members of the small group completing the task which influences the effectiveness of oral interaction for learning.This study contributes to our understanding of the way in which learners individualise the learning space and highlights the situated nature of language learning. It shows how individuals interact with each other and the task, and how talk in interaction changes moment-by-moment as learners react to the ‘here and now’ of the classroom environment.

Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

Using students’ learning style to create effective learning groups in MCSCL environments

Students have different ways for learning and processing information. Some students prefer learning through seeing while others prefer learning through listening; some students prefer doing activities while other prefer reflecting.Some students reason logically, while others reason intuitively, etc. Identifying the learning style of each student, and providing learning content based on these styles represents a good method to enhance the learning quality. However, there are no efforts onhow to detect the students’ learning styles in mobile computer supported collaborative learning (MCSCL) environments. We present in this paper new ways for automatically detecting the learning styles of students in MCSCL environments based on the learning style model of Felder-Silverman. The identified learning styles of students could be then stored and used at anytime toassign each one of them to his/her appropriate learning group.

Literacy practices in adult learning biographies: possibilities and constraints

[Extrat] The answer to the social and economic challenges that it is assumed literacy (or its lack) puts to developed countries deeply concerns public policies of governments namely those of the OECD area. In the last decades, these concerns gave origin to several and diverse monitoring devices, initiatives and programmes for reading (mainly) development, putting a strong stress on education. UNESCO (2006, p. 6), for instance, assumes that the literacy challenge can only be met raising the quality of primary and secondary education and intensifying programmes explicitly oriented towards youth and adult literacy. (...)

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Adult Learning Services

Evidence Review 4 - Adult learning services Briefing 4 - Adult learning services This pair of documents, commissioned by Public Health England, and written by the UCL Institute of Health Equity, address the role of participation in learning as an adult in improving health. There is evidence that involvement in adult learning has both direct and indirect links with health, for example because it increases employability. There is some evidence that those who are lower down the social gradient benefit most, in health terms, from adult learning. However, there is a gradient both in participation in adult learning and skill level, whereby the more someone would benefit from adult learning, the less likely they are to participate, and the lower their literacy and numeracy skills are likely to be. This is due to a range of barriers, including prohibitively high costs, lack of personal confidence, or lack of availability and access. These papers also show that there are a number of actions local authorities can take to increase access to adult learning, improve quality of provision and increase the extent to which it is delivered and targeted proportionate to need. The full evidence review and a shorter summary briefing are available to download above. This document is part of a series. An overview document which provides an introduction to this and other documents in the series, and links to the other topic areas, is available on the ‘Local Action on health inequalities’ project page. A video of Michael Marmot introducing the work is also available on our videos page.

Learning collaboration in General Internal Medicine: a pilot project for undergraduate students in nursing, physiotherapy and medicine

Background: A form of education called Interprofessional Education (IPE) occurs when two or more professions learn with, from and about each other. The purpose of IPE is to improve collaboration and the quality of care. Today, IPE is considered as a key educational approach for students in the health professions. IPE is highly effective when delivered in active patient care, such as in clinical placements. General internal medicine (GIM) is a core discipline where hospital-based clinical placements are mandatory for students in many health professions. However, few interprofessional (IP) clinical placements in GIM have been implemented. We designed such a placement. Placement design: The placement took place in the Department of Internal Medicine at the CHUV. It involved students from nursing, physiotherapy and medicine. The students were in their last year before graduation. Students formed teams consisting of one student from each profession. Each team worked in the same unit and had to take care of the same patient. The placement lasted three weeks. It included formal IP sessions, the most important being facilitated discussions or "briefings" (3x/w) during which the students discussed patient care and management. Four teams of students eventually took part in this project. Method: We performed a type of evaluation research called formative evaluation. This aimed at (1) understanding the educational experience and (2) assessing the impact of the placement on student learning. We collected quantitative data with pre-post clerkship questionnaires. We also collected qualitative data with two Focus Groups (FG) discussions at the end of the placement. The FG were audiotaped and transcribed. A thematic analysis was then performed. Results: We focused on the qualitative data, since the quantitative data lacked of statistical power due to the small numbers of students (N = 11). Five themes emerged from the FG analysis: (1) Learning of others' roles, (2) Learning collaborative competences, (3) Striking a balance between acquiring one's own professional competences and interprofessional competences, (4) Barriers to apply learnt IP competences in the future and (5) Advantages and disadvantages of IP briefings. Conclusions: Our IP clinical placement in GIM appeared to help students learn other professionals' roles and collaborative skills. Some challenges (e.g. finding the same patient for each team) were identified and will require adjustments.

TFC e-learning estàndards : Anàlisi de la qualitat de les metadades presents als documents LOM

Aquest projecte vol estudiar la qualitat de les metadades presents en els documents que representen objectes de coneixement LOM (

Quality of Web-based information on obsessive compulsive disorder.

BACKGROUND: The Internet is increasingly used as a source of information for mental health issues. The burden of obsessive compulsive disorder (OCD) may lead persons with diagnosed or undiagnosed OCD, and their relatives, to search for good quality information on the Web. This study aimed to evaluate the quality of Web-based information on English-language sites dealing with OCD and to compare the quality of websites found through a general and a medically specialized search engine. METHODS: Keywords related to OCD were entered into Google and OmniMedicalSearch. Websites were assessed on the basis of accountability, interactivity, readability, and content quality. The "Health on the Net" (HON) quality label and the Brief DISCERN scale score were used as possible content quality indicators. Of the 235 links identified, 53 websites were analyzed. RESULTS: The content quality of the OCD websites examined was relatively good. The use of a specialized search engine did not offer an advantage in finding websites with better content quality. A score ≥16 on the Brief DISCERN scale is associated with better content quality. CONCLUSION: This study shows the acceptability of the content quality of OCD websites. There is no advantage in searching for information with a specialized search engine rather than a general one. Practical implications: The Internet offers a number of high quality OCD websites. It remains critical, however, to have a provider-patient talk about the information found on the Web.

A Method and Tool to Support the Analysis and Enhance the Understanding of Peer-to-Peer Learning Experiences

In this paper we look at how a web-based social software can be used to make qualitative data analysis of online peer-to-peer learning experiences. Specifically, we propose to use Cohere, a web-based social sense-making tool, to observe, track, annotate and visualize discussion group activities in online courses. We define a specific methodology for data observation and structuring, and present results of the analysis of peer interactions conducted in discussion forum in a real case study of a P2PU course. Finally we discuss how network visualization and analysis can be used to gather a better understanding of the peer-to-peer learning experience. To do so, we provide preliminary insights on the social, dialogical and conceptual connections that have been generated within one online discussion group.

OER as a Model for Enhanced Teaching and Learning

This article presents preliminary findings from a research study conducted by the Institute for the Study of Knowledge Management in Education on the role of open educational resources (OER) in transforming pedagogy. Based on a study of art and humanities teachers participating in an OER training network, the study reveals how exposure to OER resources and tools support collaboration among teachers, as well as new conversations about teaching practices. These findings have implications for engaging teachers in adopting new OER use practices, and for how OER can be integrated as a model for innovation in teaching and in resource development.

Open video tools to support the production of online collaborative audiovisual projects : how to promote collective creation in e-learning

This paper analyses the use of open video editing tools to support the creation and production of online collaborative audiovisual projects for higher education. It focuses on the possibilities offered by these tools to promote collective creation in virtual environments.

Open Learning Network : the evidence of OER impact

Much of the initial work on Open Educational Resources (OER) has inevitably concentrated on how to produce the resources themselves and to establish the idea in the community. It is now eight years since the term OER was first used and more than ten years since the concept of open content was described and a greater focus is now emerging on the way in which OER can influence policy and change the way in which educational systems help people learn. The Open University UK and Carnegie Mellon University are working in partnership on the OLnet (Open Learning Network), funded by The William and Flora Hewlett Foundation with the aims to search out the evidence for use and reuse of OER and to establish a network for information sharing about research in the field. This means both gathering evidence and developing approaches for how to research and understand ways to learn in a more open world, particularly linked to OER, but also looking at other influences.