pinecone/core-2020-05-10-deduplication huggingface dataset:
Global Insights and Support

This book uses the example of a partnership journey between universities, schools, the local health industry as well as a number of government organisations which worked to ensure the growth of physical education in primary education. The initiative employed the United Nations (UN) ideals as a model and contextualised them within local schools and communities. What began as a pathway seed quickly grew to involve multi-stakeholder partnerships and therefore explores how the UN Sustainable Development Goals (SDG) may be implemented at a grass roots level.This chapter shares a deeper analysis of insights from the UK case study research, which indicated that partnership complexities were minimised when the relationships were developed over a sustained period of time, where genuine trust is built between stakeholders and not forced. Furthermore, when learning created through partnerships were perceived as relevant by all stakeholders, there was some form of funding, and teacher educators were confident and competent with the children aged 5–11 years. These insights were supported by recent shifts in teacher education. Hence, the global insights offered timely support and direction for the ‘Best Start’ programme
Developing Local Partnerships in HPE (Win, Win, Win)

This book uses the example of a partnership journey between universities, schools, the local health industry as well as a number of government organisations which worked to ensure the growth of physical education in primary education. The initiative employed the United Nations (UN) ideals as a model and contextualised them within local schools and communities. What began as a pathway seed quickly grew to involve multi-stakeholder partnerships and therefore explores how the UN Sustainable Development Goals (SDG) may be implemented at a grass roots level.The community collaborative partnership was extended in semester one 2012 as part of unit EDF3619 ‘Sport and physical activity education’. The purpose of this chapter is to share insights of this programme. A key goal for the ‘Friday Sports’ programme was to be a worthwhile and valued experience for the children, and especially, for the four new partnering schools. The partnership enabled accessing new assets for each of the stakeholders and subsequently, enhancing the quality of the learning experience, which they otherwise would not have had. Feedback from the various stakeholders evidenced that the ‘Friday Sports’ programme was successful and very popular
Partnerships Work: Continuing the Success in Swimming and Water Safety

This book uses the example of a partnership journey between universities, schools, the local health industry as well as a number of government organisations which worked to ensure the growth of physical education in primary education. The initiative employed the United Nations (UN) ideals as a model and contextualised them within local schools and communities. What began as a pathway seed quickly grew to involve multi-stakeholder partnerships and therefore explores how the UN Sustainable Development Goals (SDG) may be implemented at a grass roots level.The purpose of this chapter is to share the continued swimming education community partnership programme success. Pathways were investigated and initiated in 2011 which began a journey of collaboration between Australian Registered Training Organisations (RTO), the local health industry (local leisure and sports centre) and external swimming instructors employed at the venue, local primary schools, and the university sector; Monash University (Gippsland). The programme accentuated the vital role pre-service teacher education can play in the development of children’s swimming and water safety knowledge, skills, and understanding within all communities, especially the socio-economically disadvantaged
A Graph Traversal Based Approach to Answer Non-Aggregation Questions
  Over DBpedia

We present a question answering system over DBpedia, filling the gap between
user information needs expressed in natural language and a structured query
interface expressed in SPARQL over the underlying knowledge base (KB). Given
the KB, our goal is to comprehend a natural language query and provide
corresponding accurate answers. Focusing on solving the non-aggregation
questions, in this paper, we construct a subgraph of the knowledge base from
the detected entities and propose a graph traversal method to solve both the
semantic item mapping problem and the disambiguation problem in a joint way.
Compared with existing work, we simplify the process of query intention
understanding and pay more attention to the answer path ranking. We evaluate
our method on a non-aggregation question dataset and further on a complete
dataset. Experimental results show that our method achieves best performance
compared with several state-of-the-art systems.Comment: In the proceedings of the 5th Joint International Semantic Technology
  (JIST2015): https://link.springer.com/chapter/10.1007/978-3-319-31676-5_1
Using Nets-Within-Nets for Modeling Differentiating Cells in the Epigenetic Landscape

In this work the authors propose the use of a high-level Petri net formalism for modeling developmental processes at the cell level, taking explicitly into account the role of epigenetic regulation. The term "epigenetics" can refer to all possible mechanisms "acting on the genomic information between genotype and phenotype", changing the actual condition of a system without changing the underlying DNA sequence. "For example, even though the vast majority of cells in a multicellular organism share an identical genotype, organismal development generates a diversity of cell types with disparate, yet stable, profiles of gene expression and distinct cellular functions. Thus, cellular differentiation may be considered an epigenetic phenomenon, largely governed by changes in what is described as the "epigenetic landscape" . The epigenetic landscape was initially proposed as a visual metaphor for describing the scenario where developmental processes take place. Cell type differentiation is represented as increasingly irreversible, as ridges rise between the valleys where the different cells are traveling. These two metaphoric terms refer to a quasi-potential scenario. In computational terms, an epigenetic landscape can be interpreted as the ensemble of all possible regulation configurations a complex system can be in. Unfortunately, the huge number of variables involved in epigenetic regulation make this task extremely challenging. The proposed model, based on Petri Nets, is designed to simulate and conceptually characterize the contributions of the epigenetic regulation from those of other mechanisms within the cells, including transcriptional and post-transcriptional regulation, and metabolism. In this work we present the idea and the main properties of the model. Experimental results are not yet available but will be presented at the conferenc
Reactive interstitial and reparative fibrosis as substrates for cardiac ectopic pacemakers and reentries

This book constitutes the refereed proceedings of the 4th International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2016, held in Granada, Spain, in April 2016.\ud
The 69 papers presented were carefully reviewed and selected from 286 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; biomedical image analysis; biomedical signal analysis; computational systems for modeling biological processes; eHealth; tools for next generation sequencing data analysis; assistive technology for people with neuromotor disorders; fundamentals of biological dynamics and maximization of the information extraction from the experiments in the biological systems; high performance computing in bioinformatics, computational biology and computational chemistry; human behavior monitoring, analysis and understanding; pattern recognition and machine learning in the -omics sciences; and resources for bioinformatics.Dangerous cardiac arrhythmias have been frequently associated\ud
with focal sources of fast pulses, i.e. ectopic pacemakers. However,\ud
there is a lack of experimental evidences that could explain how ectopic\ud
pacemakers could be formed in cardiac tissue. In recent studies, we have\ud
proposed a new theory for the genesis of ectopic pacemakers in pathological\ud
cardiac tissues: reentry inside microfbrosis, i.e., a small region where\ud
excitable myocytes and non-conductive material coexist. In this work,\ud
we continue this investigation by comparing different types of fibrosis,\ud
reparative and reactive interstitial fibrosis. We use detailed and modern\ud
models of cardiac electrophysiology that account for the micro-structure\ud
of cardiac tissue. In addition, for the solution of our models we use, for\ud
the first time, a new numerical algorithm based on the Uniformization\ud
method. Our simulation results suggest that both types of fibrosis can\ud
support reentries, and therefore can generate in-silico ectopic pacemakers.\ud
However, the probability of reentries differs quantitatively for the\ud
different types of fibrosis. In addition, the new Uniformization method\ud
yields 20-fold increase in cardiac tissue simulation speed and, therefore,\ud
was an essential technique that allowed the execution of over a thousand\ud
of simulations.Peer ReviewedPostprint (updated version
Automated quality control for proton magnetic resonance spectroscopy data using convex non-negative matrix factorization

Proton Magnetic Resonance Spectroscopy (1H MRS) has proven its diagnostic potential in a variety of conditions. However, MRS is not yet widely used in clinical routine because of the lack of experts on its diagnostic interpretation. Although data-based decision support systems exist to aid diagnosis, they often take for granted that the\ud
data is of good quality, which is not always the case in a real  application context. Systems based on models built with bad quality data are likely to underperform in their decision support tasks. In this study, we propose a system to filter out such bad quality data. It is based on convex Non-Negative Matrix Factorization models, used as a dimensionality reduction procedure, and on the use of several classifiers to discriminate between good and bad quality data.Peer ReviewedPostprint (author's final draft
Adaptive Seeding for Gaussian Mixture Models

We present new initialization methods for the expectation-maximization
algorithm for multivariate Gaussian mixture models. Our methods are adaptions
of the well-known $K$-means++ initialization and the Gonzalez algorithm.
Thereby we aim to close the gap between simple random, e.g. uniform, and
complex methods, that crucially depend on the right choice of hyperparameters.
Our extensive experiments indicate the usefulness of our methods compared to
common techniques and methods, which e.g. apply the original $K$-means++ and
Gonzalez directly, with respect to artificial as well as real-world data sets.Comment: This is a preprint of a paper that has been accepted for publication
  in the Proceedings of the 20th Pacific Asia Conference on Knowledge Discovery
  and Data Mining (PAKDD) 2016. The final publication is available at
  link.springer.com (http://link.springer.com/chapter/10.1007/978-3-319-31750-2
  24
Addressing Privacy and Trust Issues in Cultural Heritage Modelling

The management of cultural heritage information is an important aspect of human society since it enables us to document and understand our past and learn from it. Recent developments in ICT have significantly boosted research and development activities aimed at the creation and management of cultural heritage resources. As a result, information systems play an increasingly important role on storing and managing cultural heritage information and allowing preservation of the information in a digital way. To support such effort, a number of cultural heritage conceptual models have been developed and presented in the literature. However, such models they focus on the heritage entities and information, but fail to include issues such as privacy and trust. Our research has shown that these are important issues to consider in order to have a complete cultural heritage model. This paper presents the first work in the literature to include privacy and trust as part of a cultural heritage conceptual model. We demonstrate the applicability of our work using a real world case study from the Iron Age settlement of Castrolandin in Spain
Quantum communication with photons

The secure communication of information plays an ever increasing role in our
society today. Classical methods of encryption inherently rely on the
difficulty of solving a problem such as finding prime factors of large numbers
and can, in principle, be cracked by a fast enough machine. The burgeoning
field of quantum communication relies on the fundamental laws of physics to
offer unconditional information security. Here we introduce the key concepts of
quantum superposition and entanglement as well as the no-cloning theorem that
form the basis of this field. Then, we review basic quantum communication
schemes with single and entangled photons and discuss recent experimental
progress in ground and space-based quantum communication. Finally, we discuss
the emerging field of high-dimensional quantum communication, which promises
increased data rates and higher levels of security than ever before. We discuss
recent experiments that use the orbital angular momentum of photons for sharing
large amounts of information in a secure fashion.Comment: (37 pages, 19 figures
Asymptotic Analysis of a Viscous Fluid in a Curved Pipe with Elastic
  Walls

This communication is devoted to the presentation of our recent results
regarding the asymptotic analysis of a viscous flow in a tube with elastic
walls. This study can be applied, for example, to the blood flow in an artery.
With this aim, we consider the dynamic problem of the incompressible flow of a
viscous fluid through a curved pipe with a smooth central curve. Our analysis
leads to obtain an one dimensional model via singular perturbation of the
Navier-Stokes system as $\varepsilon$, a non dimensional parameter related to
the radius of cross-section of the tube, tends to zero. We allow the radius
depend on tangential direction and time, so a coupling with an elastic or
viscoelastic law on the wall of the pipe is possible.
  To perform the asymptotic analysis, we do a change of variable to a reference
domain where we assume the existence of asymptotic expansions on $\varepsilon$
for both velocity and pressure which, upon substitution on Navier-Stokes
equations, leads to the characterization of various terms of the expansion.
This allows us to obtain an approximation of the solution of the Navier-Stokes
equations
Modeling user mobility via user psychological and geographical behaviors towards point of-interest recommendation

© Springer International Publishing Switzerland 2016. The pervasive employments of Location-based Social Network call for precise and personalized Point-of-Interest (POI) recommendation to predict which places the users prefer. Modeling user mobility, as an important component of understanding user preference, plays an essential role in POI recommendation. However, existing methods mainly model user mobility through analyzing the check-in data and formulating a distribution without considering why a user checks in at a specific place from psychological perspective. In this paper, we propose a POI recommendation algorithm modeling user mobility by considering check-in data and geographical information. Specifically, with check-in data, we propose a novel probabilistic latent factor model to formulate user psychological behavior from the perspective of utility theory, which could help reveal the inner information underlying the comparative choice behaviors of users. Geographical behavior of all the historical check-ins captured by a power law distribution is then combined with probabilistic latent factor model to form the POI recommendation algorithm. Extensive evaluation experiments conducted on two real-world datasets confirm the superiority of our approach over state-of-the-art methods
Model Selection for Financial Distress Prediction by Aggregating TOPSIS and PROMETHEE Rankings

Ponencia presentada al 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016Many models have been explored for financial distress prediction, but no consistent conclusions have been drawn on which method shows the best behavior when different performance evaluation measures are employed. Accordingly, this paper proposes the integration of the ranking scores given by two popular multiple-criteria decision-making tools as an important step to help decision makers in selecting the model(s) properly. Selection of the most appropriate prediction method is here shaped as a multiple-criteria decision-making problem that involves a number of performance measures (criteria) and a set of techniques (alternatives). An empirical study is carried out to assess the performance of ten algorithms over six real-life bankruptcy and credit risk databases. The results reveal that the use of a unique performance measure often leads to contradictory conclusions, while the multiple-criteria decision-making techniques may yield a more reliable analysis. Besides, these allow the decision makers to weight the relevance of the individual performance metrics as a function of each particular problem.This work has partially been supported by the Spanish Ministry of Economy
[TIN2013-46522-P], the Generalitat Valenciana [PROMETEOII/2014/062], the
Mexican PRODEP [DSA/103.5/15/7004] and the Mexican Science and Technology
Council through the Postdoctoral Fellowship Program [232167]
Makespaces: From Redistributed Manufacturing to a Circular Economy

Redistributed manufacturing is an emerging concept which captures the anticipated reshoring and localisation of production from large scale manufacturing plants to smaller-scale localised, customisable production units, largely driven by new additive digital production technologies. Critically, community based digital fabrication workshops, or makespaces, are anticipated to be the hothouse for this new era of localised production and as such are key to future sustainable design and manufacturing practices. In parallel, the concept of the circular economy (CE) conceptualises the move from a linear economy of take-make-waste to a closed loop system, through repair, remanufacturing, refurbishment and recycling which maintains the value of materials and resources. Despite the clear interplay between RdM and CE, there is limited research exploring this relationship. In light of these interconnected developments, the aim of this paper is to explore the role of makespaces in contributing to a circular economy through RdM activities. This is achieved through six semi-structured interviews with thought leaders on these topics. The research findings identify barriers and opportunities to both CE and RdM, uncover key overlaps between CE and RdM, and identify a range of future research directions that can support the coming together of these areas. The research contributes to a wider conversation on embedding circular practices within makespaces and their role in RdM
Modelling and Verification of Energy Consumption in CNC Milling

Electrical energy consumption forms 99% of the environmental impact of machining operations. Whilst replacing existing machineries for more energy efficient ones does not deem possible in short term, process planning for machining with energy consumption in mind is a more accessible solution. The effect of cutting parameters on power consumption in CNC milling of 6082 T6 aluminum alloy was investigated in this paper. Mathematical models were developed to estimate the energy and power consumption in CNC milling machines. The analysis indicated that the two less studied parameters of axial and radial depth of cut have significant impact on the total energy consumption of machining processes. Increased axial and radial depth of cut not only increase material removal rate but also increase the portion of machine tool’s power consumption dedicated to material cutting. This study indicated that 82% reduction in energy consumption can be achieved through precise selection of cutting parameters
A bottom-up design framework for CAD tools to support design for additive manufacturing

Additive manufacturing (AM) technology is enabling a platform to produce parts with enhanced shape complexity. Design engineers are exploiting this capability to produce high performance functional parts. The current top-down approach to design for AM requires the designer to develop a design model in CAD software and then use optimization tools to adapt the design for the AM technology, however this approach neglects a number of desired criteria. This paper proposes an alternative bottom-up design framework for a new type of CAD tool which combines the knowledge required to design a part with evolutionary programming in order to design parts specifically for the AM platform
Can re-distributed manufacturing and digital intelligence enable a regenerative economy? An integrative literature review

This paper uses an integrative literature review to explore the concept of re-distributed manufacturing and the opportunities to deliver more regenerative and resilient systems of production and consumption through the application of circular innovation. The study identified multiple similarities between the drivers of re-distributed and circular models of production and consumption that could be fostered by the use of digital intelligence. A set of criteria for redistributed manufacturing and circular innovation were developed and used to identify 33 existing case studies of consumer goods production. Case study analysis resulted in the identification of three types of re-distributed manufacturing that integrated characteristics of circular innovation. The paper concludes by describing some of the future research challenges in the transition towards re-distributed and circular models of production
Makespaces: From Redistributed Manufacturing to a Circular Economy

Redistributed manufacturing is an emerging concept which captures the anticipated reshoring and localisation of production from large scale mass manufacturing plants to smaller-scale localised, customisable production units, largely driven by new digital production technologies. Critically, community-based digital fabrication workshops, or makespaces, are anticipated to be one hothouse for this new era of localised production and as such are key to future sustainable design and manufacturing practices. In parallel, the concept of the circular economy conceptualises the move from a linear economy of take-make-waste to a closed loop system, through repair, remanufacturing, and recycling to ultimately extend the value of products and materials. Despite the clear interplay between redistributed manufacturing and circular economy, there is limited research exploring this relationship. In light of these interconnected developments, the aim of this paper is to explore the role of makespaces in contributing to a circular economy through redistributed manufacturing activities. This is achieved through six semi-structured interviews with thought leaders on these topics. The research findings identify barriers and opportunities to both circular economy and redistributed manufacturing, uncover overlaps between circular economy and redistributed manufacturing, and identify a range of future research directions that can support the coming together of these areas. The research contributes to a wider conversation on embedding circular practices within makespaces and their role in redistributed manufacturing