Time consistent expected mean-variance in multistage stochastic quadratic optimization: a model and a matheuristic

In this paper, we present a multistage time consistent Expected Conditional Risk Measure for minimizing a linear combination of the expected mean and the expected variance, so-called Expected Mean-Variance. The model is formulated as a multistage stochastic mixed-integer quadratic programming problem combining risk-sensitive cost and scenario analysis approaches. The proposed problem is solved by a matheuristic based on the Branch-and-Fix Coordination method. The multistage scenario cluster primal decomposition framework is extended to deal with large-scale quadratic optimization by means of stage-wise reformulation techniques. A specific case study in risk-sensitive production planning is used to illustrate that a remarkable decrease in the expected variance (risk cost) is obtained. A competitive behavior on the part of our methodology in terms of solution quality and computation time is shown when comparing with plain use of CPLEX in 150 benchmark instances, ranging up to 711,845 constraints and 193,000 binary variables.project MTM2015-65317-P (MINECO/FEDER/EU); BERC 2014-2017; IT-928-16; and by the University of the Basque Country UPV/EHU; BCAM Severo Ochoa excellence accreditation Grant SEV-2013-0323; BERC 2014-201

A parallel Branch-and-Fix Coordination based matheuristic algorithm for solving large sized multistage stochastic mixed 0-1 problems

A parallel matheuristic algorithm is presented as a spin-off from the exact Branch-and-Fix Coordination (BFC) algorithm for solving multistage stochastic mixed 0-1 problems. Some steps to guarantee the solution’s optimality are relaxed in the BFC algorithm, such that an incomplete backward branching scheme is considered for solving large sized problems. Additionally, a new branching criterion is considered, based on dynamically-guided and stage-wise ordering schemes, such that fewer Twin Node Families are expected to be visited during the execution of the so-called H-DBFC algorithm. The inner parallelization IH-DBFC of the new approach, allows to solve in parallel scenario clusters MIP submodels at different steps of the algorithm. The outer parallel version, OH-DBFC, considers independent paths and allows iterative incumbent solution values exchanges to obtain tighter bounds of the solution value of the original problem. A broad computational experience is reported for assessing the quality of the matheuristic solution for large sized instances. The instances dimensions that are considered are up to two orders of magnitude larger than in some other works that we are aware of. The optimality gap of the H-DBFC solution value versus the one obtained by a state-of-the-artMIP solver is very small, if any. The new approach frequently outperforms it in terms of solution’s quality and computing time. A comparison with our Stochastic Dynamic Programming algorithm is also reported. The use of parallel computing provides, on one hand, a perspective for solving very large sized instances and, on the other hand, an expected large reduction in elapsed time.MTM2015-65317-P, MTM2015-63710-P, IT928-16; UFI BETS 2011; IZO-SGI SGIke

Endogenous VEGF isoform expression regulates tumour cell motility

Background: Vascular endothelial growth factor-A (VEGF) is produced by most cancer cells as multiple alternatively spliced isoforms, which display distinct receptor and matrix binding characteristics. In addition to being a major inducer of tumour angiogenesis, VEGF also has complex functions in angiogenesis-independent aspects of tumour growth,but the role of individual VEGF isoforms remains poorly understood. Here we investigated the effects of endogenous VEGF isoform expression on tumour cell migration and invasion. Method: We used a panel of mouse fibrosarcoma cells we developed (fs188, fs164 and fs120) that express single VEGF isoforms (188, 164 or 120 respectively), under endogenous promoter control. We investigated adhesion to different matrices, 2D migration and invasion through 3D collagen. Results: Fs188 cells, are typically mesenchymal, form ruffles, display strong integrin-dependent adhesion and express high levels of pERK1/2 and pAKT. In contrast, fs164 and fs120 cells are not typically mesenchymal in morphology; they display weak binding to collagen, lack ruffles and align longitudinally forming long multicellular chains and abundant cell-cell contacts. On 3D collagen, fs188 cells remain mesenchymal while fs164 and fs120 cells adopt a rounded/amoeboid and a mix of rounded/mesenchymal morphologies respectively. Cell morphology and migration are dependent on the cytoskeleton and actinomyosin contractility, to provide traction force in mesenchymal movement, and cortical contraction for rounded amoeboid motility. Consistent with their mesenchymal characteristics, fs188 cells migrated faster in 2D and invaded 3D collagen more efficiently than fs164 or fs120 cells. Contractility inhibitors caused fs164/fs120 cells to switch to a mesenchymal morphology and accelerated their migration but not that of fs188 cells. Conclusion: VEGF isoforms are emerging as potential biomarkers for anti-VEGF therapies. Our results suggest that individual VEGF isoforms influence the migration and invasion strategies of tumour cells thus adding to the complexity of VEGF signaling within the tumor microenvironment. Acknowledgements This work was funded by Cancer Research UK

Insights from EEG analysis of evoked memory recalls using deep learning for emotion charting

Affect recognition in a real-world, less constrained environment is the principal prerequisite of the industrial-level usefulness of this technology. Monitoring the psychological profile using smart, wearable electroencephalogram (EEG) sensors during daily activities without external stimuli, such as memory-induced emotions, is a challenging research gap in emotion recognition. This paper proposed a deep learning framework for improved memory-induced emotion recognition leveraging a combination of 1D-CNN and LSTM as feature extractors integrated with an Extreme Learning Machine (ELM) classifier. The proposed deep learning architecture, combined with the EEG preprocessing, such as the removal of the average baseline signal from each sample and extraction of EEG rhythms (delta, theta, alpha, beta, and gamma), aims to capture repetitive and continuous patterns for memory-induced emotion recognition, underexplored with deep learning techniques. This work has analyzed EEG signals using a wearable, ultra-mobile sports cap while recalling autobiographical emotional memories evoked by affect-denoting words, with self-annotation on the scale of valence and arousal. With extensive experimentation using the same dataset, the proposed framework empirically outperforms existing techniques for the emerging area of memory-induced emotion recognition with an accuracy of 65.6%. The EEG rhythms analysis, such as delta, theta, alpha, beta, and gamma, achieved 65.5%, 52.1%, 65.1%, 64.6%, and 65.0% accuracies for classification with four quadrants of valence and arousal. These results underscore the significant advancement achieved by our proposed method for the real-world environment of memory-induced emotion recognition

Sustainable Development, Ecological Complexity, and Environmental Values

Sustainable Development, Ecological Complexity, and Environmental Values contributes to expanding the idea of sustainability by integrating different thematic issues related to sustainable development in its threefold consideration (economic, social, and environmental) with regard to the case of the Basque Country. On the global scale, changes have clearly accelerated; ecological and social sustainability are two facets of the same changing reality. First, social sustainability depends on ecological sustainability. If we continue degrading nature's capacity to produce the ecosystems' services (water filtration, climate stabilization, etc) and resources (food, materials), both individuals and nations will be affected by growing pressures and increasing conflicts, as well as by threats to public health and personal safety. Second, ecological sustainability depends on social sustainability, a socially unjust and unfair system wiht an ever-increasing population that is not able to have its needs met will necessarily lead to environmental collapse. In addition, human behavior and the social dynamic often lie at the heart of social and ecological problems. It must be, therefore, assumed that there will not be sustainable development if sustainable societies do not first exist. A sustainable society has the challenge of developing human capital. In this book, these global questions are treated as they relate to specific place and context, the Basque Country and its modern institutions.This book was published with generous financial support from the Basque Government.Introduction—Ignacio Ayestarán and Miren Onaindia ? 1. An Evaluation of Ecosystem Services as a Base for the Sustainable Management of a Region by Miren Onaindia and Gloria Rodríguez-Loinaz ? 2. An Evaluation of Millennium Ecosystems from the Basque Country by Igone Palacios, Izaskun Casada-Arzuaga, Iosu Madariaga, and Xabier Arana ? 3. Climate Change: Activities of the EOLO Group at the University of the Basque Country by Agustín Ezcurra, Jon Sáenz, and Gabriel Ibarra-Berastegi ? 4. The Environmental Value of the Karstic Landscape of the Urdaibai Biosphere Reserve: The Asnarre Promontory (Bizkaia) by Arantza Aranburu, Laura Damas-Mollá, Patxi García-Garmilla, Iñaki Yusta, M. Arriolabengoa, Peru Iridoy, and Eneko Iriarte ? 5. Recent Environmental Transformation of the Bilbao Estuary: Natural and Anthropogenic Processes by Alejandro Cearreta, Maria Jesús Irabien, and Eduardo Leorri ? 6. The Landscape of the Autonomous Community of the Basque Country: The Evolution of Forest Systems by Lorena Peña and Ibone Amezaga ? 7. Critical Theories of Sustainable Development by Eguzki Urteaga ? 8. Bases for the Transition toward a Sustainable Economy by Roberto Bermejo, David Hoyos, and Eneko Garmendia ? 9. Environmental Values, the Epistemology of Complex Problems, and Postnormal Science in the Face of Global Change by Ignacio Ayestáran ? 10. Science, Gender, and Sustainable Development by Teresa Nuño Angós ? 11. Environmental Education as Training: A Case Study at the University of the Basque Country by Araitz Uskola Ibarluzea ? 12. Social Values and Sustainable Practices among Basque Inshore Fishermen by Pío Pérez Aldasoro ? 13. Sustainable Development and the Values of Well-Being and Globalization by Eduardo Rubio Ardanaz, Juan Antonio Rubio-Ardanaz, and Xiao Fang ? Index ? List of Contributor

Tumour cells expressing single VEGF isoforms display distinct growth, survival and migration characteristics

Vascular endothelial growth factor-A (VEGF) is produced by most cancer cells as multiple isoforms, which display distinct biological activities. VEGF plays an undisputed role in tumour growth, vascularisation and metastasis; nevertheless the functions of individual isoforms in these processes remain poorly understood. We investigated the effects of three main murine isoforms (VEGF188, 164 and 120) on tumour cell behaviour, using a panel of fibrosarcoma cells we developed that express them individually under endogenous promoter control. Fibrosarcomas expressing only VEGF188 (fs188) or wild type controls (fswt) were typically mesenchymal, formed ruffles and displayed strong matrix-binding activity. VEGF164- and VEGF120-producing cells (fs164 and fs120 respectively) were less typically mesenchymal, lacked ruffles but formed abundant cell-cell contacts. On 3D collagen, fs188 cells remained mesenchymal while fs164 and fs120 cells adopted rounded/amoeboid and a mix of rounded and elongated morphologies respectively. Consistent with their mesenchymal characteristics, fs188 cells migrated significantly faster than fs164 or fs120 cells on 2D surfaces while contractility inhibitors accelerated fs164 and fs120 cell migration. VEGF164/VEGF120 expression correlated with faster proliferation rates and lower levels of spontaneous apoptosis than VEGF188 expression. Nevertheless, VEGF188 was associated with constitutively active/phosphorylated AKT, ERK1/2 and Stat3 proteins. Differences in proliferation rates and apoptosis could be explained by defective signalling downstream of pAKT to FOXO and GSK3 in fs188 and fswt cells, which also correlated with p27/p21 cyclin-dependent kinase inhibitor over-expression. All cells expressed tyrosine kinase VEGF receptors, but these were not active/activatable suggesting that inherent differences between the cell lines are governed by endogenous VEGF isoform expression through complex interactions that are independent of tyrosine kinase receptor activation. VEGF isoforms are emerging as potential biomarkers for anti-VEGF therapies. Our results reveal novel roles of individual isoforms associated with cancer growth and metastasis and highlight the importance of understanding their diverse actions

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Qualitative Research on the Impact Assessment in Health: The Experience of a reform plan in a neighborhood of Bilbao

Objective: to know the perceived effects on health of a neighborhood of Bilbao reform plan from the perspective of the neighbors and stakeholders, and identify those areas for possible improvement. Methodology: qualitative study. Obtaining information through participant observation, four discussion groups (three neighbors and another one with health professionals and social workers), and four interviews with key informants. The analysis was designed on the model of sociological analysis of the speech. Results: The findings set three areas related to socio-historical context of the neighborhood, the dynamic nature of the intervention and perceived impact on health in eight specific areas (urban accessibility, water and draining, recreation areas, power lines burial, parking place and road traffic, the small works, to feel as citizens, and social cohesion). Conclusions: Qualitative methods enabled deepen the significance of these findings in the direction of their interrelations, which enabled a better understanding of the impact on the health plan. It also points out some major methodological challenges for the development of future impact assessments on health