pinecone/core-2020-05-10-deduplication huggingface dataset:
Submarine mass movements and their consequences

Submarine spreading is a type of mass movement that involves the extension and fracturing of a thin surficial layer of sediment into coherent blocks and their finite displacement on a gently sloping slip surface. Its characteristic seafloor signature is a repetitive pattern of parallel ridges and troughs oriented perpendicular to the direction of mass movement. We map ~30 km2 of submarine spreads on the upper slope of the Hikurangi margin, east of Poverty Bay, North Island, New Zealand, using multibeam echosounder and 2D multichannel seismic data. These data show that spreading occurs in thin, gently-dipping, parallel-bedded clay, silt and sandy sedimentary units deposited as lowstand clinoforms. More importantly, high-amplitude and reverse polarity seismic reflectors, which we interpret as evidence of shallow gas accumulations, occur extensively in the fine sediments of the upper continental slope, but are either significantly weaker or entirely absent where the spreads are located. We use this evidence to propose that shallow gas, through the generation of pore pressure, has played a key role in establishing the failure surface above which submarine spreading occurred. Additional dynamic changes in pore pressure could have been triggered by a drop in sea level during the Last Glacial Maximum and seismic loading.peer-reviewe
Volcanic Generation of Tsunamis: Two New Zealand Palaeo-Events

Rapid emplacement of a mass via pyroclastic flows, or edifice failure, generates volcanic tsunamis. Physical modelling demonstrates that the efficiency of tsuna-mi generation is influenced by the angle the mass enters the ocean. Efficiency de-creases with increasing slope angle from 20° to 60°, before increasing to a maxi-mum at 90°, which corresponds to a mass falling directly into the ocean without interacting with the slope (impact tsunami). Further, in the case of surging pyro-clastic flows or regressive failures, successive closely spaced events may generate larger tsunami waves than a single event of comparable volume.
It is difficult to assess if physical model results are meaningful for real world tsu-nami events due to limited observational data. This paper compares numerical models developed from physical simulations with palaeotsunami deposits from two New Zealand palaeo-events – pyroclastic flows from Mt Tarawera and edi-fice failure at Whakaari (White Island) – which constrains numerical simulations of the source mechanisms. The Mt Tarawera event involved multiple pyroclastic flows entering a lake during the AD 1314±12 Kaharoa Eruption. The interaction of multiple closely spaced pyroclastic flows is necessary to generate the 6-7 m maximum wave height inferred from near source tsunami deposits. Tsunami de-posits in the Bay of Plenty, dated to 2962±52 BP, are consistent with edifice fail-ure at Whakaari. In this case a single event with a volume of 0.23 km3 is suffi-cient to account for the tsunami deposits. Hence, if the failure was regressive, the successive stages were sufficiently close together to be indistinguishable from a large single event
Hybrid Approach for Inductive Semi Supervised Learning using Label
  Propagation and Support Vector Machine

Semi supervised learning methods have gained importance in today's world
because of large expenses and time involved in labeling the unlabeled data by
human experts. The proposed hybrid approach uses SVM and Label Propagation to
label the unlabeled data. In the process, at each step SVM is trained to
minimize the error and thus improve the prediction quality. Experiments are
conducted by using SVM and logistic regression(Logreg). Results prove that SVM
performs tremendously better than Logreg. The approach is tested using 12
datasets of different sizes ranging from the order of 1000s to the order of
10000s. Results show that the proposed approach outperforms Label Propagation
by a large margin with F-measure of almost twice on average. The parallel
version of the proposed approach is also designed and implemented, the analysis
shows that the training time decreases significantly when parallel version is
used.Comment: Presented in the 11th International Conference, MLDM, Germany, July
  20 - 21, 2015. Springer, Machine Learning and Data Mining in Pattern
  Recognition, LNAI Vol. 9166, p. 199-213, 201
Query Click and Text Similarity Graph\ud
for Query Suggestions

Query suggestion is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of suggestions like query, image, movies, music and book etc. are used every day. Various types of data sources are used for the suggestions. If we model the data into various kinds of graphs then we can build a general method for any suggestions. In this paper, we have proposed a general method for query suggestion by combining two graphs: (1) query click graph which captures the relationship between queries frequently clicked on common URLs and (2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users’ need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product suggestion
Cytokine networks and cancer stem cells

Cell-to-cell communication is an integral function of multicellular organisms. Many of these signals are received by a myriad of cell-surface receptors that utilize a range of intracellular signaling pathways to communicate this to the nucleus, rapidly impacting on the transcription of target genes in order to elicit the desired response, such as proliferation, differentiation, activation, and survival. Dysregulation of these important signaling pathways, and networks, often lead to pathological conditions due to inappropriate cell responses with negative consequences. The aberrant signaling pathways have been associated with many diseases, including cancer. Cytokines and chemokines convey a multitude of messages to the target cell, many of which are beneficial for cancers and cancer stem cells, such as proliferation, survival and migration. By hijacking this communication network, cancers and cancer stem cells can become invasive and more pathogenic. Furthermore, by using these communication systems, cancer stem cells are able to evade current therapies. Therefore, novel therapies may be developed to break the communication systems of the cancer stem cells. This chapter explores the role of the cytokines TGF-&beta;, TNF-&alpha;, IL-1 and IL-6 and chemokine CXCL8 as well as NF-&kappa;B and their role in cancer stem cell survival and maintenance. Emerging therapies are beginning to target the cancer stem cell population, either specifically or synergistically with existing therapeutic options. These novel therapies may hold the key to breaking the communication network of cancer stem cells
Extreme waves and branching flows in optical media

We address light propagation properties in complex media consisting of random
distributions of lenses that have specific focusing properties. We present both
analytical and numerical techniques that can be used to study emergent
properties of light organization in these media. As light propagates, it
experiences multiple scattering leading to the formation of light bundles in
the form of branches; these are random yet occur systematically in the the
medium, particularly in the weak scattering limit. On the other hand, in the
strong scattering limit we find that coalescence of branches may lead to the
formation of extreme waves of the "rogue wave" type. These waves appear at
specific locations and arise in the linear as well as in the nonlinear regimes.
We present both the weak and strong scattering limit and show that these
complex phenomena can be studied numerically and analytically through simple
models.Comment: This is a Chapter from the book: Quodons in Mica: Nonlinear localized
  traveling excitations in crystals. Springer Series in Materials Scienc
Experimental observation of moving intrinsic localized modes in
  germanium

Deep level transient spectroscopy shows that defects created by alpha
irradiation of germanium are annealed by low energy plasma ions up to a depth
of several thousand lattice units. The plasma ions have energies of 2-8eV and
therefore can deliver energies of the order of a few eV to the germanium atoms.
The most abundant defect is identified as the E-center, a complex of the dopant
antimony and a vacancy with and annealing energy of 1.3eV as determined by our
measurements. The inductively coupled plasma has a very low density and a very
low flux of ions. This implies that the ion impacts are almost isolated both in
time and at the surface of the semiconductor. We conclude that energy of the
order of an eV is able to travel a large distance in germanium in a localized
way and is delivered to the defects effectively. The most likely candidates are
vibrational nonlinear wave packets known as intrinsic localized modes, which
exist for a limited range of energies. This property is coherent with the fact
that more energetic ions are less efficient at producing the annealing effect.Comment: 20 pages, 10 figure
The origin of defects induced in ultra-pure germanium by Electron Beam
  Deposition

The creation of point defects in the crystal lattices of various
semiconductors by subthreshold events has been reported on by a number of
groups. These observations have been made in great detail using sensitive
electrical techniques but there is still much that needs to be clarified.
Experiments using Ge and Si were performed that demonstrate that energetic
particles, the products of collisions in the electron beam, were responsible
for the majority of electron-beam deposition (EBD) induced defects in a
two-step energy transfer process. Lowering the number of collisions of these
energetic particles with the semiconductor during metal deposition was
accomplished using a combination of static shields and superior vacuum
resulting in devices with defect concentrations lower than $
10^{11}\,$cm$^{-3}$, the measurement limit of our deep level transient
spectroscopy (DLTS) system. High energy electrons and photons that samples are
typically exposed to were not influenced by the shields as most of these
particles originate at the metal target thus eliminating these particles as
possible damage causing agents. It remains unclear how packets of energy that
can sometimes be as small of 2eV travel up to a $\mu$m into the material while
still retaining enough energy, that is, in the order of 1eV, to cause changes
in the crystal. The manipulation of this defect causing phenomenon may hold the
key to developing defect free material for future applications.Comment: 18 pages, 9 figure
Numerical simulations of nonlinear modes in mica: past, present and
  future

We review research on the role of nonlinear coherent phenomena (e.g breathers
and kinks) in the formation linear decorations in mica crystal. The work is
based on a new model for the motion of the mica hexagonal K layer, which allows
displacement of the atoms from the unit cell. With a simple piece-wise
polynomial inter-particle potential, we verify the existence of localized
long-lived breathers in an idealized lattice at 0K. Moreover, our model allows
us to observe long-lived localized kinks. We study the interactions of such
localized modes along a lattice direction, and in addition demonstrate fully
two dimensional scattering of such pulses for the first time. For large
interatomic forces we observe a spreading horseshoe-shaped wave, a type of
shock wave but with a breather profile
A supersonic crowdion in mica: Ultradiscrete kinks with energy between
  $^{40}$K recoil and transmission sputtering

In this chapter we analyze in detail the behaviour and properties of the
kinks found in an one dimensional model for the close packed rows of potassium
ions in mica muscovite. The model includes realistic potentials obtained from
the physics of the problem, ion bombardment experiments and molecular dynamics
fitted to experiments. These kinks are supersonic and have an unique velocity
and energy. They are ultradiscrete involving the translation of an interstitial
ion, which is the reason they are called 'crowdions'. Their energy is below the
most probable source of energy, the decay of the $^{40}$K isotope and above the
energy needed to eject an atom from the mineral, a phenomenon that has been
observed experimentallyComment: 28 pages, 15 figure
Later Life: Living Alone, Social Connectedness and ICT

The paper presents a qualitative, interview-based study that seeks to describe participants’ perceptions and experiences with information and communication technology. The participants in the study were active people, aged 67 and over, who live alone in an urban setting. Interactionist theory of loneliness was used to guide the inquiry, in particular regarding the perception of the relation between the quality and quantity of connections, loneliness, and technology. A set of visual tools such as communication maps and cards were made to aid reflections and associations during interviews
Towards a Theory for Bio - Cyber Physical Systems Modelling

Currently, CyberPhysical Systems (CPS) represents a great challenge for
automatic control and smart systems engineering on both theoretical and
practical levels. Designing CPS requires approaches involving multidisciplinary
competences. However they are designed to be autonomous, the CPS present a part
of uncertainty, which requires interaction with human for engineering,
monitoring, controlling, performing operational maintenance, etc. This
human-CPS interaction led naturally to the human in-the-loop (HITL) concept.
Nevertheless, this HITL concept , which stems from a reductionist point of
view, exhibits limitations due to the different natures of the systems
involved. As opposed to this classical approach, we propose, in this paper, a
model of Bio-CPS (i.e. systems based on an integration of computational
elements within biological systems) grounded on theoretical biology, physics
and computer sciences and based on the key concept of human systems
integration.Comment: HCI International 2015, Aug 2015, Los Angeles, United States. LNCS
  9184, 2015, LNCS - Digital Human Modeling and applications in Health, Safety,
  Ergonomics and Risk Management: Human Modelling (Part I
Human Machine Epistemology Survey

Pluridisciplinar convergence is a major problem that had emerged with
Human-Artefact Systems and so-called " Augmented Humanity " as academical
fields and even more as technical fields. Problems come mainly from the
juxtaposition of two very different types of system, a biological one and an
artificial one. Thus, conceiving and designing the multiple couplings between
them has become a major difficulty. Some came with reductionnist solutions to
answer these problems but since we know that a biological system and a
technical system are different, this approach is limited from its beginning.
Using a specifically designed questionnaire and statistical analysis we
determined how specialists (medical practitioners, ergonomists and engineers)
in the domain conceive themselves what is a Human-Artifact System and how they
relate to existent traditions and showed that some of them relate to the
integrativist views
Equational reasoning with context-free families of string diagrams

String diagrams provide an intuitive language for expressing networks of
interacting processes graphically. A discrete representation of string
diagrams, called string graphs, allows for mechanised equational reasoning by
double-pushout rewriting. However, one often wishes to express not just single
equations, but entire families of equations between diagrams of arbitrary size.
To do this we define a class of context-free grammars, called B-ESG grammars,
that are suitable for defining entire families of string graphs, and crucially,
of string graph rewrite rules. We show that the language-membership and
match-enumeration problems are decidable for these grammars, and hence that
there is an algorithm for rewriting string graphs according to B-ESG rewrite
patterns. We also show that it is possible to reason at the level of grammars
by providing a simple method for transforming a grammar by string graph
rewriting, and showing admissibility of the induced B-ESG rewrite pattern.Comment: International Conference on Graph Transformation, ICGT 2015. The
  final publication is available at Springer via
  http://dx.doi.org/10.1007/978-3-319-21145-9_
A Comparison of Two-Level and Multi-level Modelling for Cloud-Based Applications

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-21151-0_2The Cloud Modelling Framework (CloudMF) is an approach to apply model-driven engineering principles to the specification and execution of cloud-based applications. It comprises a domain-specific language to model the deployment topology of multi-cloud applications, along with a models@run-time environment to facilitate reasoning and adaptation of these applications at run-time. This paper reports on some challenges encountered during the design of CloudMF, related to the adoption of the two-level modelling approach and especially the type-instance pattern. Moreover, it proposes the adoption of an alternative, multi-level modelling approach to tackle these challenges, and provides a set of criteria to compare both approaches.The research leading to these results has received funding from the European Commission’s Seventh Framework Programme (FP7/2007-2013) under grant agreement numbers 317715 (PaaSage), 318392 (Broker@Cloud), and 611125 (MONDO), the Spanish Ministry under project Go Lite (TIN2011-24139), and the Madrid Region under project SICOMORO (S2013/ICE-3006)
Reusable model transformation components with bentō

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-21155-8_5Building high-quality transformations that can be used in real projects is complex and time-consuming. For this reason, the ability to reuse existing transformations in different, unforeseen scenarios is very valuable. However, there is scarce tool support for this task. This paper presents bentō, a tool which supports the development and execution of reusable transformation components. In bentō, a reusable transformation is written as a regular ATL transformation, but it uses concepts as meta-models. Reuse is achieved by binding such concepts to meta-models, which induces the transformation adaptation. Moreover, composite components enable chaining transformations, and it is possible to convert an existing transformation into a reusable component. Bentō is implemented as an Eclipse plug-in, available as free software.This work was supported by the Spanish Ministry of Economy and Competitivity with project Go-Lite (TIN2011-24139), the R&D programme of the Madrid Region with project (SICOMORO S2013/ICE-3006), and the EU commission with project MONDO (FP7-ICT 2013-10, #611125)
Convolutional LSTM Networks for Subcellular Localization of Proteins

Machine learning is widely used to analyze biological sequence data.
Non-sequential models such as SVMs or feed-forward neural networks are often
used although they have no natural way of handling sequences of varying length.
Recurrent neural networks such as the long short term memory (LSTM) model on
the other hand are designed to handle sequences. In this study we demonstrate
that LSTM networks predict the subcellular location of proteins given only the
protein sequence with high accuracy (0.902) outperforming current state of the
art algorithms. We further improve the performance by introducing convolutional
filters and experiment with an attention mechanism which lets the LSTM focus on
specific parts of the protein. Lastly we introduce new visualizations of both
the convolutional filters and the attention mechanisms and show how they can be
used to extract biological relevant knowledge from the LSTM networks
Lectures on bifunctors and finite generation of rational cohomology
  algebras

This text is an updated version of material used for a course at Universit\'e
de Nantes, part of `Functor homology and applications', April 23-27, 2012. The
proof by Touz\'e of my conjecture on cohomological finite generation (CFG) has
been one of the successes of functor homology. We will not treat the original
proof in any detail. Instead we will focus on a formality conjecture of
Cha{\l}upnik that leads to second generation proof of the existence of the
universal classes of Touz\'e.Comment: 30 pages; title change
Machine Learning applied to Rule-Based Machine Translation

Lexical and morphological ambiguities present a serious challenge in rule-based machine translation (RBMT). This chapter describes an approach to resolve morphologically ambiguous verb forms if a rule-based decision is not possible due to parsing or tagging errors. The rule-based core system has a set of rules to decide, based on context information, which verb form should be generated in the target language. However, if the parse tree is not correct, part of the context information might be missing and the rules cannot make a safe decision. In this case, we use a classifier to assign a verb form. We tested the classifier on a set of four texts, increasing the correct verb forms in the translation from 78.68\%, with the purely rule-based disambiguation, to 95.11\% with the hybrid approach
Kitaev's quantum double model from a local quantum physics point of view

A prominent example of a topologically ordered system is Kitaev's quantum
double model $\mathcal{D}(G)$ for finite groups $G$ (which in particular
includes $G = \mathbb{Z}_2$, the toric code). We will look at these models from
the point of view of local quantum physics. In particular, we will review how
in the abelian case, one can do a Doplicher-Haag-Roberts analysis to study the
different superselection sectors of the model. In this way one finds that the
charges are in one-to-one correspondence with the representations of
$\mathcal{D}(G)$, and that they are in fact anyons. Interchanging two of such
anyons gives a non-trivial phase, not just a possible sign change. The case of
non-abelian groups $G$ is more complicated. We outline how one could use
amplimorphisms, that is, morphisms $A \to M_n(A)$ to study the superselection
structure in that case. Finally, we give a brief overview of applications of
topologically ordered systems to the field of quantum computation.Comment: Chapter contributed to R. Brunetti, C. Dappiaggi, K. Fredenhagen, J.
  Yngvason (eds), Advances in Algebraic Quantum Field Theory (Springer 2015).
  Mainly revie