1,244 research outputs found

    From shoes to ICT: a determined project, based on information technology and sustainable development, set for a long-lasting future

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    From shoes to ICT (Information and Communication Technology): how a rural area was given the chance to climb out of a crisis in traditional manufacturing industries and improve its prosperity. Local development can be built on innovation through new technologies. In the North of Alsace, France, the ADEC, a local development structure, was created with this very purpose. Can ADEC be seen as a good practice? What are the limits of such a structure? What new steps must be taken to ensure its continuation and effectiveness in the future for all its stakeholders? The ADEC experience shows how a team of deeply committed entrepreneurs and politicians can build a collective project, in coherence with EU policies, over the long-term. Through drawing out some of the key guidelines from the ADEC story, it is possible to transfer partly to other territories some of the ADEC practice.Como pode uma região rural ultrapassar a crise da indús- tria tradicional e prosperar, e como pode o desenvolvimento local assentar em inovação baseada em novas tecnologias? A resposta é procurada através do exemplo da ADEC, grupo de desenvolvimento local do Norte da Alsácia. São discutidas as suas boas práticas, os respectivos limites, os passos necessários para assegurar a sua continuidade e a participação efectiva de todos os actores. Desta experiência destaca-se a importância de se contar, a longo prazo, com uma equipa de empresários e políticos profundamente envolvidos na construção de um projecto colectivo, centrado nas políticas da União Europeia, e extraem-se ensinamentos parcialmente transfe-ríveis para outros territórios

    Multi-stage Biomarker Models for Progression Estimation in Alzheimer’s Disease

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    The estimation of disease progression in Alzheimer’s disease (AD) based on a vector of quantitative biomarkers is of high interest to clinicians, patients, and biomedical researchers alike. In this work, quantile regression is employed to learn statistical models describing the evolution of such biomarkers. Two separate models are constructed using (1) subjects that progress from a cognitively normal (CN) stage to mild cognitive impairment (MCI) and (2) subjects that progress from MCI to AD during the observation window of a longitudinal study. These models are then automatically combined to develop a multi-stage disease progression model for the whole disease course. A probabilistic approach is derived to estimate the current disease progress (DP) and the disease progression rate (DPR) of a given individual by fitting any acquired biomarkers to these models. A particular strength of this method is that it is applicable even if individual biomarker measurements are missing for the subject. Employing cognitive scores and image-based biomarkers, the presented method is used to estimate DP and DPR for subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Further, the potential use of these values as features for different classification tasks is demonstrated. For example, accuracy of 64% is reached for CN vs. MCI vs. AD classification

    Applications of Systems Engineering Methodologies to an Undergraduate Student Volunteer-Led CubeSat Constellation

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    The Northern Space Program for Innovative Research and Integrated Training (Northern SPIRIT) satellite consortium launched in March 2023 and consists of three CubeSats designed, assembled, and operated by AlbertaSat, a University of Alberta student group: Ex-Alta 2: a 3U CubeSat containing an open-source, multispectral imager designed for wildfire prediction, detection, and prevention. YukonSat and AuroraSat: 2U CubeSats developed in collaboration with Yukon University and the Aurora Research Institute, each with an educational outreach payload that can receive, display, and photograph community submitted artwork and messages. All three satellites have digital fluxgate magnetometer payloads, and nearly identical buses composed of both commercial off-the-shelf (COTS) and designed-in-house components. Common aerospace systems engineering methodologies were applied throughout all mission phases in a lean manner to mitigate technical and programmatic risk

    Natural recovery of genetic diversity by gene flow in reforested areas of the endemic Canary Island pine, Pinus canariensis

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    The endemic pine, Pinus canariensis, forms one of the main forest ecosystems in the Canary Islands. In this archipelago, pine forest is a mosaic of natural stands (remnants of past forest overexploitation) and artificial stands planted from the 1940's. The genetic makeup of the artificially regenerated forest is of some concern. The use of reproductive material with uncontrolled origin or from a reduced number of parental trees may produce stands ill adapted to local conditions or unable to adapt in response to environmental change. The genetic diversity within a transect of reforested stands connecting two natural forest fragments has been studied with nuclear and chloroplast microsatellites. Little genetic differentiation and similar levels of genetic diversity to the surrounding natural stands were found for nuclear markers. However, chloroplast microsatellites presented lower haplotype diversity in reforested stands, and this may be a consequence of the lower effective population size of the chloroplast genome, meaning chloroplast markers have a higher sensitivity to bottlenecks. Understory natural regeneration within the reforestation was also analysed to study gene flow from natural forest into artificial stands. Estimates of immigration rate into artificially regenerated forest were high (0.68-0.75), producing a significant increase of genetic diversity (both in chloroplast and nuclear microsatellites), which indicates the capacity for genetic recovery for P. canariensis reforestations surrounded by larger natural stands
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