154 research outputs found
Commissioning and performance of a phase-compensated optical link for the AWAKE experiment at CERN
In this work, we analyze the performance of the solution adopted for the
compensation of the phase drift of a 3 km optical fiber link used for the AWAKE
experiment at CERN. The link is devoted to transmit the reference signals used
to synchronize the SPS beam with the experiment to have a fixed phase relation,
regardless of the external conditions of the electronics and the link itself.
The system has been operating for more than a year without observed drift in
the beam phases. Specific measurements have proven that the jitter introduced
by the system is lower than 0.6 ps and the maximum phase drift of the link is
at the picosecond level.Comment: Poster presented at LLRF Workshop 2017 (LLRF2017, arXiv:1803.07677
A case report of metastasis of malignant mesothelioma to the oral gingiva
Introduction:
Metastatic mesothelioma to the oral cavity arises from the pleura or peritoneum and distant hematogenous metastases are seen in more than half of cases but only a few cases are reported to the oral cavity
Case:
A 75 year old male suffering from metastatic mesothelioma presents an hyperplasia of the attached gingiva. Malignant mesothelioma is a rare tumour arising from pleura, pericardium or peritoneum.
Conclusion:
This article highlights the importance of biopsy and histopathological diagnosis of oral lesions especially in case of a malignant history
Integrable models and quantum spin ladders: comparison between theory and experiment for the strong coupling ladder compounds
(abbreviated) This article considers recent advances in the investigation of
the thermal and magnetic properties of integrable spin ladder models and their
applicability to the physics of real compounds. The ground state properties of
the integrable two-leg spin-1/2 and the mixed spin-(1/2,1) ladder models at
zero temperature are analyzed by means of the Thermodynamic Bethe Ansatz.
Solving the TBA equations yields exact results for the critical fields and
critical behaviour. The thermal and magnetic properties of the models are
investigated in terms of the recently introduced High Temperature Expansion
method, which is discussed in detail. It is shown that in the strong coupling
limit the integrable spin-1/2 ladder model exhibits three quantum phases: (i) a
gapped phase in the regime , (ii) a fully polarised phase for
, and (iii) a Luttinger liquid magnetic phase in the regime
. The critical behaviour in the vicinity of the critical
points is of the Pokrovsky-Talapov type. The temperature-dependent thermal and
magnetic properties are directly evaluated from the exact free energy
expression and compared to known experimental results for a range of strong
coupling ladder compounds. Similar analysis of the mixed spin-(1/2,1) ladder
model reveals a rich phase diagram, with a 1/3 and a full saturation
magnetisation plateau within the strong antiferromagnetic rung coupling regime.
For weak rung coupling, the fractional magnetisation plateau is diminished and
a new quantum phase transition occurs. The phase diagram can be directly
deduced from the magnetisation curve obtained from the exact result derived
from the HTE. The thermodynamics of the spin-orbital model with different
single-ion anisotropies is also investigated.Comment: 90 pages, 33 figures, extensive revisio
Probabilistic models of information retrieval based on measuring the divergence from randomness
We introduce and create a framework for deriving probabilistic models of Information Retrieval. The models are nonparametric models of IR obtained in the language model approach. We derive term-weighting models by measuring the divergence of the actual term distribution from that obtained under a random process. Among the random processes we study the binomial distribution and Bose--Einstein statistics. We define two types of term frequency normalization for tuning term weights in the document--query matching process. The first normalization assumes that documents have the same length and measures the information gain with the observed term once it has been accepted as a good descriptor of the observed document. The second normalization is related to the document length and to other statistics. These two normalization methods are applied to the basic models in succession to obtain weighting formulae. Results show that our framework produces different nonparametric models forming baseline alternatives to the standard tf-idf model
Progress with the Upgrade of the SPS for the HL-LHC Era
The demanding beam performance requirements of the High Luminosity (HL-) LHC
project translate into a set of requirements and upgrade paths for the LHC
injector complex. In this paper the performance requirements for the SPS and
the known limitations are reviewed in the light of the 2012 operational
experience. The various SPS upgrades in progress and still under consideration
are described, in addition to the machine studies and simulations performed in
2012. The expected machine performance reach is estimated on the basis of the
present knowledge, and the remaining decisions that still need to be made
concerning upgrade options are detailed.Comment: 3 p. Presented at 4th International Particle Accelerator Conference
(IPAC 2013
Entanglement entropy of two disjoint intervals in c=1 theories
We study the scaling of the Renyi entanglement entropy of two disjoint blocks
of critical lattice models described by conformal field theories with central
charge c=1. We provide the analytic conformal field theory result for the
second order Renyi entropy for a free boson compactified on an orbifold
describing the scaling limit of the Ashkin-Teller (AT) model on the self-dual
line. We have checked this prediction in cluster Monte Carlo simulations of the
classical two dimensional AT model. We have also performed extensive numerical
simulations of the anisotropic Heisenberg quantum spin-chain with tree-tensor
network techniques that allowed to obtain the reduced density matrices of
disjoint blocks of the spin-chain and to check the correctness of the
predictions for Renyi and entanglement entropies from conformal field theory.
In order to match these predictions, we have extrapolated the numerical results
by properly taking into account the corrections induced by the finite length of
the blocks to the leading scaling behavior.Comment: 37 pages, 23 figure
Life expectancy and agricultural environmental impacts in Addis Ababa can be improved through optimized plant and animal protein consumption
In Ethiopia, children and adults face a double burden of malnutrition, with undernutrition and stunting coexisting with non-communicable diseases. Here we use a framework of comparative risk assessment, local dietary surveys and relative risks from large observational studies to quantify the health and environmental impacts of meeting adult and child recommended daily protein intakes in urban Addis Ababa. We find that plant-based foods, especially legumes, would have the lowest environmental impact and substantially increase life expectancy in adults, while animal-source proteins could be beneficial for children. This context-specific approachâaccounting for regional constraints and trade-offsâcould aid policymakers in developing culturally appropriate, nutritionally adequate and sustainable dietary recommendations
Accurate and Transparent Path Prediction Using Process Mining
Anticipating the next events of an ongoing series of activities has many compelling applications in various industries. It can be used to improve customer satisfaction, to enhance operational efficiency, and to streamline health-care services, to name a few. In this work, we propose an algorithm that predicts the next events by leveraging business process models obtained using process mining techniques. Because we are using business process models to build the predictions, it allows business analysts to interpret and alter the predictions. We tested our approach with more than 30 synthetic datasets as well as 6 real datasets. The results have superior accuracy compared to using neural networks while being orders of magnitude faster
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