pinecone/core-2020-05-10-deduplication huggingface dataset:
Displacement and Resettlement: Understanding the Role of Climate Change in Contemporary Migration

How do we understand displacement and resettlement in the context of climate change? This chapter outlines challenges and debates in the literature connecting climate change to the growing global flow of people. We begin with an outline of the literature on environmental migration, specifically the definitions, measurements, and forms of environmental migration. The discussion then moves to challenges in the reception of migrants, treating the current scholarship on migrant resettlement. We detail a selection of cases in which the environment plays a role in the displacement of a population, including sea level rise in Pacific Island States, cyclonic storms in Bangladesh, and desertification in West Africa, as well as the role of deforestation in South America’s Southern Cone as a driver of both climate change and migration. We outline examples of each, highlighting the complex set of losses and damages incurred by populations in each case
Supporting Climate Risk Management at Scale. Insights from the Zurich Flood Resilience Alliance Partnership Model Applied in Peru & Nepal

There has been increasing interest in the potential of effective science-society partnership models for identifying and implementing options that manage critical disaster risks “on the ground.” This particularly holds true for debate around Loss and Damage. Few documented precedents and little documented experience exists, however, for such models of engagement. How to organise such partnerships? What are learnings from existing activities and how can these be upscaled? We report on one such partnership, the Zurich Flood Resilience Alliance, a multi-actor partnership launched in 2013 to enhance communities’ resilience to flooding at local to global scales. The program brings together the skills and expertise of NGOs, the private sector and research institutions in order to induce transformational change for managing flood risks. Working in a number of countries facing different challenges and opportunities the program uses a participatory and iterative approach to develop sustainable portfolios of interventions that tackle both flood risk and development objectives in synergy. We focus our examination on two cases of Alliance engagement, where livelihoods are particularly being eroded by flood risk, including actual and potential contributions by climate change: (i) in the Karnali river basin in West Nepal, communities are facing rapid on-set flash floods during the monsoon season; (ii) in the Rimac basin in Central Peru communities are exposed to riverine flooding amplified by El Niño episodes. We show how different tools and methods can be co-generated and used at different learning stages and across temporal and agency scales by researchers and practitioners. Seamless integration is neither possible, nor desirable, and in many instances, an adaptive management approach through, what we call, a Shared Resilience Learning Dialogue, can provide the boundary process that connects the different analytical elements developed and particularly links those up with community-led processes. Our critical examination of the experience from the Alliance leads into suggestions for identifying novel funding and support models involving NGOs, researchers and the private sector working side by side with public sector institutions to deliver community level support for managing risks that may go “beyond adaptation.
Loss and Damage in the Rapidly Changing Arctic

Arctic climate change is happening much faster than the global average. Arctic change also has global consequences, in addition to local ones. Scientific evidence shows that meltwater of Arctic sources contributes to sea-level rise significantly while accounting for 35% of current global sea-level rise. Arctic communities have to find ways to deal with rapidly changing environmental conditions that are leading to social impacts such as outmigration, similarly to the global South. International debates on Loss and Damage have not addressed the Arctic so far. We review literature to show what impacts of climate change are already visible in the Arctic, and present local cases in order to provide empirical evidence of losses and damages in the Arctic region. This evidence is particularly well presented in the context of outmigration and relocation of which we highlight examples. The review reveals a need for new governance mechanisms and institutional frameworks to tackle Loss and Damage. Finally, we discuss what implications Arctic losses and damages have for the international debate
The Ethical Challenges in the Context of Climate Loss and Damage

This chapter lays out what we take to be the main types of justice and ethical challenges concerning those adverse effects of climate change leading to climate-related Loss and Damage (L&D). We argue that it is essential to clearly differentiate between the challenges concerning mitigation and adaptation and those ethical issues exclusively relevant for L&D in order to address the ethical aspects pertaining to L&D in international climate policy. First, we show that depending on how mitigation and adaptation are distinguished from L&D, the primary focus of policy measures and their ethical implications will vary. Second, we distinguish between a distributive justice framework and a compensatory justice scheme for delivering L&D measures. Third, in order to understand the differentiated remedial responsibilities concerning L&D, we categorise the measures and policy approaches available. Fourth, depending on the kind of L&D and which remedies are possible, we explain the difference between remedial and outcome responsibilities of different actors
Insurance as a Response to Loss and Damage?

This chapter asks whether insurance instruments, especially micro-insurance and regional insurance pools, can serve as a risk-reducing and equitable compensatory response to climate-attributed losses and damages from climate extremes occurring in developing countries, and consequently if insurance instruments can serve the preventative and curative targets of the Warsaw International Mechanism for Loss and Damage (WIM). The discussion emphasises the substantial benefits of both micro-insurance programs and regional insurance pools, and at the same time details their significant costs. Beyond costs and benefits, a main message is that if no significant intervention is undertaken in their design and implementation, market-based insurance mechanisms will likely fall short of fully meeting WIM aspirations of loss reduction and equitable compensation. Interventions can include subsidies and other types of support that make insurance affordable to poor clients; interventions can also enable public-private arrangements that genuinely catalyse risk reduction and adaptation. Many such interventions are already in place, and the chapter highlights two potential success stories for insurance instruments serving the most vulnerable: the African R4 micro-insurance program and the African Risk Capacity (ARC) regional insurance pool. While support to these and other insurance programs continues to be framed as humanitarian aid based on the principle of solidarity, discussions on the G7 initiative to insure vulnerable households, as well as on ARC’s initiative to link international payments to climate risks, raise the question whether the narrative will evolve from solidarity to responsibility based on the principle of developed country accountability
The Risk and Policy Space for Loss and Damage: Integrating Notions of Distributive and Compensatory Justice with Comprehensive Climate Risk Management

The Warsaw Loss and Damage Mechanism holds high appeal for complementing actions on climate change adaptation and mitigation, and for delivering needed support for tackling intolerable climate related-risks that will neither be addressed by mitigation nor by adaptation. Yet, negotiations under the UNFCCC are caught between demands for climate justice, understood as compensation, for increases in extreme and slow-onset event risk, and the reluctance of other parties to consider Loss and Damage outside of an adaptation framework. Working towards a jointly acceptable position we suggest an actionable way forward for the deliberations may be based on aligning comprehensive climate risk analytics with distributive and compensatory justice considerations. Our proposed framework involves in a short-medium term, needs-based perspective support for climate risk management beyond countries ability to absorb risk. In a medium-longer term, liability-based perspective we particularly suggest to consider liabilities attributable to anthropogenic climate change and associated impacts. We develop the framework based on principles of need and liability, and identify the policy space for Loss and Damage as composed of curative and transformative measures. Transformative measures, such as managed retreat, have already received attention in discussions on comprehensive climate risk management. Curative action is less clearly defined, and more contested. Among others, support for a climate displacement facility could qualify here. For both sets of measures, risk financing (such as ‘climate insurance’) emerges as an entry point for further policy action, as it holds potential for both risk management as well as compensation functions. To quantify the Loss and Damage space for specific countries, we suggest as one option to build on a risk layering approach that segments risk and risk interventions according to risk tolerance. An application to fiscal risks in Bangladesh and at the global scale provides an estimate of countries’ financial support needs for dealing with intolerable layers of flood risk. With many aspects of Loss and Damage being of immaterial nature, we finally suggest that our broad risk and justice approach in principle can also see application to issues such as migration and preservation of cultural heritage
Asymmetric Combination of Logics is Functorial: A Survey

Asymmetric combination of logics is a formal process that develops the characteristic features of a specific logic on top of another one. Typical examples include the development of temporal, hybrid, and probabilistic dimensions over a given base logic. These examples are surveyed in the paper under a particular perspective—that this sort of combination of logics possesses a functorial nature. Such a view gives rise to several interesting questions. They range from the problem of combining translations (between logics), to that of ensuring property preservation along the process, and the way different asymmetric combinations can be related through appropriate natural transformations
Angluin learning via logic

In this paper we will provide a fresh take on Dana Angluin's algorithm for learning using ideas from coalgebraic modal logic. Our work opens up possibilities for applications of tools & techniques from modal logic to automata learning and vice versa. As main technical result we obtain a generalisation of Angluin's original algorithm from DFAs to coalgebras for an arbitrary finitary set functor T in the following sense: given a (possibly infinite) pointed T-coalgebra that we assume to be regular (i.e. having an equivalent finite representation) we can learn its finite representation by asking (i) "logical queries" (corresponding to membership queries) and (ii) making conjectures to which the teacher has to reply with a counterexample. This covers (a known variant) of the original L* algorithm and the learning of Mealy/Moore machines. Other examples are bisimulation quotients of (probabilistic) transition systems
Simultaneous Matrix Diagonalization for Structural Brain Networks
  Classification

This paper considers the problem of brain disease classification based on
connectome data. A connectome is a network representation of a human brain. The
typical connectome classification problem is very challenging because of the
small sample size and high dimensionality of the data. We propose to use
simultaneous approximate diagonalization of adjacency matrices in order to
compute their eigenstructures in more stable way. The obtained approximate
eigenvalues are further used as features for classification. The proposed
approach is demonstrated to be efficient for detection of Alzheimer's disease,
outperforming simple baselines and competing with state-of-the-art approaches
to brain disease classification
Cycle-centrality in complex networks

Networks are versatile representations of the interactions between entities
in complex systems. Cycles on such networks represent feedback processes which
play a central role in system dynamics. In this work, we introduce a measure of
the importance of any individual cycle, as the fraction of the total
information flow of the network passing through the cycle. This measure is
computationally cheap, numerically well-conditioned, induces a centrality
measure on arbitrary subgraphs and reduces to the eigenvector centrality on
vertices. We demonstrate that this measure accurately reflects the impact of
events on strategic ensembles of economic sectors, notably in the US economy.
As a second example, we show that in the protein-interaction network of the
plant Arabidopsis thaliana, a model based on cycle-centrality better accounts
for pathogen activity than the state-of-art one. This translates into
pathogen-targeted-proteins being concentrated in a small number of triads with
high cycle-centrality. Algorithms for computing the centrality of cycles and
subgraphs are available for download
Seed selection for information cascade in multilayer networks

Information spreading is an interesting field in the domain of online social
media. In this work, we are investigating how well different seed selection
strategies affect the spreading processes simulated using independent cascade
model on eighteen multilayer social networks. Fifteen networks are built based
on the user interaction data extracted from Facebook public pages and tree of
them are multilayer networks downloaded from public repository (two of them
being Twitter networks). The results indicate that various state of the art
seed selection strategies for single-layer networks like K-Shell or VoteRank do
not perform so well on multilayer networks and are outperformed by Degree
Centrality
A generative model for sparse, evolving digraphs

Generating graphs that are similar to real ones is an open problem, while the
similarity notion is quite elusive and hard to formalize. In this paper, we
focus on sparse digraphs and propose SDG, an algorithm that aims at generating
graphs similar to real ones. Since real graphs are evolving and this evolution
is important to study in order to understand the underlying dynamical system,
we tackle the problem of generating series of graphs. We propose SEDGE, an
algorithm meant to generate series of graphs similar to a real series. SEDGE is
an extension of SDG. We consider graphs that are representations of software
programs and show experimentally that our approach outperforms other existing
approaches. Experiments show the performance of both algorithms
Consistent Estimation of Mixed Memberships with Successive Projections

This paper considers the parameter estimation problem in Mixed Membership
Stochastic Block Model (MMSB), which is a quite general instance of random
graph model allowing for overlapping community structure. We present the new
algorithm successive projection overlapping clustering (SPOC) which combines
the ideas of spectral clustering and geometric approach for separable
non-negative matrix factorization. The proposed algorithm is provably
consistent under MMSB with general conditions on the parameters of the model.
SPOC is also shown to perform well experimentally in comparison to other
algorithms
Modeling peer and external influence in online social networks

Opinion polls mediated through a social network can give us, in addition to
usual demographics data like age, gender and geographic location, a friendship
structure between voters and the temporal dynamics of their activity during the
voting process. Using a Facebook application we collected friendship
relationships, demographics and votes of over ten thousand users on the
referendum on the definition of marriage in Croatia held on 1st of December
2013. We also collected data on online news articles mentioning our
application. Publication of these articles align closely with large peaks of
voting activity, indicating that these external events have a crucial influence
in engaging the voters. Also, existence of strongly connected friendship
communities where majority of users vote during short time period, and the fact
that majority of users in general tend to friend users that voted the same
suggest that peer influence also has its role in engaging the voters. As we are
not able to track activity of our users at all times, and we do not know their
motivations for expressing their votes through our application, the question is
whether we can infer peer and external influence using friendship network of
users and the times of their voting. We propose a new method for estimation of
magnitude of peer and external influence in friendship network and demonstrate
its validity on both simulated and actual data
Discourse, sentence grammar and the left periphery of the clause

The term left periphery refers to that area on the left of the subject, in the syntactic representation of a clause, where the relationships with the context are encoded. In this work I propose a syntactic analysis that goes beyond mere sentence grammar and integrates prosodic and discourse features as well. On the one hand, this move accounts for some observations previously not fully understood, such as the anomalous syntactic properties of Clitic Left Dislocation and Hanging Topic, their differences with respect to Focus and their similarities with parentheticals. On the other, it aims at providing a theory of grammar able to encode the relationships between sentence grammar, context and bigger units such as discourses
Application of semifinite index theory to weak topological phases

Recent work by Prodan and the second author showed that weak invariants of
topological insulators can be described using Kasparov's $KK$-theory. In this
note, a complementary description using semifinite index theory is given. This
provides an alternative proof of the index formulae for weak complex
topological phases using the semifinite local index formula. Real invariants
and the bulk-boundary correspondence are also briefly considered.Comment: To appear in the conference proceedings from the MATRIX-program
  'Refining C*-algebraic invariants for dynamics using KK-theory' in Creswick,
  Australia (2016
Unravelling the Dodecahedral Spaces

The hyperbolic dodecahedral space of Weber and Seifert has a natural
non-positively curved cubulation obtained by subdividing the dodecahedron into
cubes. We show that the hyperbolic dodecahedral space has a 6-sheeted irregular
cover with the property that the canonical hypersurfaces made up of the
mid-cubes give a very short hierarchy. Moreover, we describe a 60-sheeted cover
in which the associated cubulation is special. We also describe the natural
cubulation and covers of the spherical dodecahedral space (aka Poincar\'e
homology sphere).Comment: 15 pages + 6 pages appendix, 7 figures, 4 table
Lecture notes on infinity-properads

These are notes for three lectures on higher properads given at a program at
the mathematical institute MATRIX in Australia in June 2016. The first lecture
covers the case of operads, and provides a brief introduction to the
Moerdijk-Weiss theory of dendroidal sets. The second lecture extends the
discussion to properads and our work with Donald Yau on graphical sets. These
two lectures conclude with models for higher (pr)operads given by an inner horn
filling condition. Finally, in the last lecture, we explore some properties of
the graphical category and use them to give a Segal-type model for higher
properads.Comment: These lecture notes will eventually appear in the MATRIX book series
  http://www.matrix-inst.org.au/book-series/. Comments are always welcome
Quantum lattice Boltzmann study of random-mass Dirac fermions in one
  dimension

We study the time evolution of quenched random-mass Dirac fermions in one
dimension by quantum lattice Boltzmann simulations. For nonzero noise strength,
the diffusion of an initial wave packet stops after a finite time interval,
reminiscent of Anderson localization. However, instead of exponential
localization we find algebraically decaying tails in the disorder-averaged
density distribution. These qualitatively match $\propto x^{-3/2}$ decay, which
has been predicted by analytic calculations based on zero-energy solutions of
the Dirac equation.Comment: 5 pages, 8 figure
Cloud Ownership and Reliability – Issues\ud
and Developments

Cloud computing is a composite paradigm that provides crucial\ud
services to individuals and organisations over networked infrastructure at a cost.\ud
The Cloud provides custom built applications, made available by a CSP to\ud
customers. Several customers can access an instance of one application. The\ud
Cloud also affords an avenue for customers to build their own application in a\ud
language compatible with a CSP and subsequently deploy that application on\ud
the Cloud. In addition, massive scalable storage and computing devices are\ud
available on the Cloud. A customers expects optimum services whenever and\ud
wherever it is required. Hence, system failure on the part of a CSP must not\ud
affect the services being provided to the customer. This paper examines present\ud
trends in the area of Cloud ownership reliability and provides a guide for future\ud
research. The paper aims to answer the following question: what is the current\ud
trend and development in Cloud ownership reliability? In addition, analysis was\ud
done on existing work published in journals, conferences, white papers and\ud
those published in reputable magazines, to answer the question raised. The\ud
expected result is the identification of trends in Cloud ownership and reliability\ud
which will be of benefit to prospective Cloud users and service providers alike
Knowledge-based interoperability for mathematical software systems

Funding: OpenDreamKit Horizon 2020 European Research Infrastructures project (#676541) and DFG project RA-18723-1 OAF.There is a large ecosystem of mathematical software systems. Individually, these are optimized for particular domains and functionalities, and together they cover many needs of practical and theoretical mathematics. However, each system specializes on one area, and it remains very difficult to solve problems that need to involve multiple systems. Some integrations exist, but the are ad-hoc and have scalability and maintainability issues. In particular, there is not yet an interoperability layer that combines the various systems into a virtual research environment (VRE) for mathematics. The OpenDreamKit project aims at building a toolkit for such VREs. It suggests using a central system-agnostic formalization of mathematics (Math-in-the-Middle, MitM) as the needed interoperability layer. In this paper, we conduct the first major case study that instantiates the MitM paradigm for a concrete domain as well as a concrete set of systems. Specifically, we integrate GAP, Sage, and Singular to perform computation in group and ring theory. Our work involves massive practical efforts, including a novel formalization of computational group theory, improvements to the involved software systems, and a novel mediating system that sits at the center of a star-shaped integration layout between mathematical software systems.Postprin