151 research outputs found
Cadenes de Markov aplicades als sistemes bonus-malus
Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Josep Vives i Santa Eulàlia i M. Mercè Claramunt Bielsa[en] Insurance world is reinventing itself every time there are new technologies or people meet new needs. People want fair prices in accordance with their needs, but is it easy to give a price of a service that none knows how much could cost?
This degree project studies Markov chains to apply them in Bonus-Malus Systems (BMS). Firstly, we will study how BMS works. Secondly, an analysis of some tools to compare different BMS will be carry out. Finally, we will see some doubts and questions that professionals face when they create and optimize it
Dual Auction Mechanism for Transaction Forwarding and Validation in Complex Wireless Blockchain Network
In traditional blockchain networks, transaction fees are only allocated to
full nodes (i.e., miners) regardless of the contribution of forwarding
behaviors of light nodes. However, the lack of forwarding incentive reduces the
willingness of light nodes to relay transactions, especially in the
energy-constrained Mobile Ad Hoc Network (MANET). This paper proposes a novel
dual auction mechanism to allocate transaction fees for forwarding and
validation behaviors in the wireless blockchain network. The dual auction
mechanism consists of two auction models: the forwarding auction and the
validation auction. In the forwarding auction, forwarding nodes use Generalized
First Price (GFP) auction to choose transactions to forward. Besides,
forwarding nodes adjust the forwarding probability through a no-regret
algorithm to improve efficiency. In the validation auction, full nodes select
transactions using Vickrey-Clarke-Grove (VCG) mechanism to construct the block.
We prove that the designed dual auction mechanism is Incentive Compatibility
(IC), Individual Rationality (IR), and Computational Efficiency (CE).
Especially, we derive the upper bound of the social welfare difference between
the social optimal auction and our proposed one. Extensive simulation results
demonstrate that the proposed dual auction mechanism decreases energy and
spectrum resource consumption and effectively improves social welfare without
sacrificing the throughput and the security of the wireless blockchain network
Experience-driven Networking: A Deep Reinforcement Learning based Approach
Modern communication networks have become very complicated and highly
dynamic, which makes them hard to model, predict and control. In this paper, we
develop a novel experience-driven approach that can learn to well control a
communication network from its own experience rather than an accurate
mathematical model, just as a human learns a new skill (such as driving,
swimming, etc). Specifically, we, for the first time, propose to leverage
emerging Deep Reinforcement Learning (DRL) for enabling model-free control in
communication networks; and present a novel and highly effective DRL-based
control framework, DRL-TE, for a fundamental networking problem: Traffic
Engineering (TE). The proposed framework maximizes a widely-used utility
function by jointly learning network environment and its dynamics, and making
decisions under the guidance of powerful Deep Neural Networks (DNNs). We
propose two new techniques, TE-aware exploration and actor-critic-based
prioritized experience replay, to optimize the general DRL framework
particularly for TE. To validate and evaluate the proposed framework, we
implemented it in ns-3, and tested it comprehensively with both representative
and randomly generated network topologies. Extensive packet-level simulation
results show that 1) compared to several widely-used baseline methods, DRL-TE
significantly reduces end-to-end delay and consistently improves the network
utility, while offering better or comparable throughput; 2) DRL-TE is robust to
network changes; and 3) DRL-TE consistently outperforms a state-ofthe-art DRL
method (for continuous control), Deep Deterministic Policy Gradient (DDPG),
which, however, does not offer satisfying performance.Comment: 9 pages, 12 figures, paper is accepted as a conference paper at IEEE
Infocom 201
Efficient privacy preserving predicate encryption with fine-grained searchable capability for cloud storage
With the fast development in Cloud storage technologies and ever increasing use of Cloud data centres, data privacy and confidentiality has become a must. Indeed, Cloud data centres store each time more sensitive data such as personal data, organizational and enterprise data, transactional data, etc. However, achieving confidentiality with flexible searchable capability is a challenging issue. In this article, we show how to construct an efficient predicate encryption with fine-grained searchable capability. Predicate Encryption (PEPE) can achieve more sophisticated and flexible functionality compared with traditional public key encryption. We propose an efficient predicate encryption scheme by utilizing the dual system encryption technique, which can also be proved to be IND-AH-CPA (indistinguishable under chosen plain-text attack for attribute-hiding) secure without random oracle. We also carefully analyse the relationship between predicate encryption and searchable encryption. To that end, we introduce a new notion of Public-Key Encryption with Fine-grained Keyword Search (PEFKSPEFKS). Our results show that an IND-AH-CPA secure PE scheme can be used to construct an IND-PEFKS-CPA (indistinguishable under chosen plain-text attack for public-key encryption with fine-grained keyword search) secure PEFKSPEFKS scheme. A new transformation of PE-to-PEFKS is also proposed and used to construct an efficient PEFKSPEFKS scheme based on the transformation from the proposed PEPE scheme. Finally, we design a new framework for supporting privacy preserving predicate encryption with fine-grained searchable capability for Cloud storage. Compared to most prominent frameworks, our framework satisfies more features altogether and can serve as a basis for developing such frameworks for Cloud data centres.Peer ReviewedPostprint (author's final draft
miR-133a Regulates Adipocyte Browning In Vivo.
Prdm16 determines the bidirectional fate switch of skeletal muscle/brown adipose tissue (BAT) and regulates the thermogenic gene program of subcutaneous white adipose tissue (SAT) in mice. Here we show that miR-133a, a microRNA that is expressed in both BAT and SATs, directly targets the 3′ UTR of Prdm16. The expression of miR-133a dramatically decreases along the commitment and differentiation of brown preadipocytes, accompanied by the upregulation of Prdm16. Overexpression of miR-133a in BAT and SAT cells significantly inhibits, and conversely inhibition of miR-133a upregulates, Prdm16 and brown adipogenesis. More importantly, double knockout of miR-133a1 and miR-133a2 in mice leads to elevations of the brown and thermogenic gene programs in SAT. Even 75% deletion of miR-133a (a1−/−a2+/−) genes results in browning of SAT, manifested by the appearance of numerous multilocular UCP1-expressing adipocytes within SAT. Additionally, compared to wildtype mice, miR-133a1−/−a2+/− mice exhibit increased insulin sensitivity and glucose tolerance, and activate the thermogenic gene program more robustly upon cold exposure. These results together elucidate a crucial role of miR-133a in the regulation of adipocyte browning in vivo
Dynamic spin-lattice coupling and nematic fluctuations in NaFeAs
We use inelastic neutron scattering to study acoustic phonons and spin
excitations in single crystals of NaFeAs, a parent compound of iron pnictide
superconductors. NaFeAs exhibits a tetragonal-to-orthorhombic structural
transition at K and a collinear antiferromagnetic (AF) order at
K. While longitudinal and out-of-plane transverse acoustic
phonons behave as expected, the in-plane transverse acoustic phonons reveal
considerable softening on cooling to , and then harden on approaching
before saturating below . In addition, we find that spin-spin
correlation lengths of low-energy magnetic excitations within the FeAs layer
and along the -axis increase dramatically below , and show weak anomaly
across . These results suggest that the electronic nematic phase present
in the paramagnetic tetragonal phase is closely associated with dynamic
spin-lattice coupling, possibly arising from the one-phonon-two-magnon
mechanism
The Misconception of Antibiotic Equal to an Anti-Inflammatory Drug Promoting Antibiotic Misuse among Chinese University Students.
Massive misuse of antibiotics is one of the most important reasons for antimicrobial resistance (AMR). Misconceptions of antibiotics contribute to antibiotic misuse behaviors. This study aims to examine whether university students hold the misconception that Antibiotic is a Xiaoyanyao (literally means anti-inflammatory drug in Chinese), and association between this misconception and antibiotic misuse behaviors. A cross-sectional study was conducted among university students using the cluster random sampling method in six universities of six regions in China (one university per region). The Chi-square test was used to assess the relationship between the misconception and antibiotic misuse behaviors. Logistic regression was conducted to identify the risk factors for antibiotic misuse behaviors. 11,192 of university students completed the entire questionnaire. There were 3882 (34.7%) students who were considered to have the misconception. Female students were more likely to have the misconception compared with males (36.7% vs. 32.6%, P < 0.001). Those students with a background of social science/humanities were more likely to have the misconception compared with those from science and medicine (44.1% vs. 30.3% vs. 20.1%, P < 0.001). Students came from rural areas compared with those from urban areas (37.5% vs. 32.5%, P < 0.001) were more likely to have the misconception. Students who had the misconception were 1.51 (95% CI 1.21⁻1.89, P < 0.001) times, 1.34 (95% CI 1.21⁻1.48, P < 0.001) times, and 1.36 (95% CI 1.24⁻1.50, P < 0.001) times more likely to report self-medication, request to obtain antibiotics, and take antibiotics prophylactically than those who did not have this misconception, respectively. The high proportion of university students' misconception on Antibiotic is a Xiaoyanyao is worth more attention. Effective health education and interventions need to be promoted among university students and the whole population
High-energy magnetic excitations from heavy quasiparticles in CeCuSi
Magnetic fluctuations is the leading candidate for pairing in cuprate,
iron-based and heavy fermion superconductors. This view is challenged by the
recent discovery of nodeless superconductivity in CeCuSi, and calls for
a detailed understanding of the corresponding magnetic fluctuations. Here, we
mapped out the magnetic excitations in \ys{superconducting (S-type)}
CeCuSi using inelastic neutron scattering, finding a strongly
asymmetric dispersion for ~meV, which at higher energies evolve
into broad columnar magnetic excitations that extend to meV. While
low-energy magnetic excitations exhibit marked three-dimensional
characteristics, the high-energy magnetic excitations in CeCuSi are
almost two-dimensional, reminiscent of paramagnons found in cuprate and
iron-based superconductors. By comparing our experimental findings with
calculations in the random-phase approximation,we find that the magnetic
excitations in CeCuSi arise from quasiparticles associated with its
heavy electron band, which are also responsible for superconductivity. Our
results provide a basis for understanding magnetism and superconductivity in
CeCuSi, and demonstrate the utility of neutron scattering in probing
band renormalization in heavy fermion metals
The performance of large-pitch AC-LGAD with different N+ dose
AC-Coupled LGAD (AC-LGAD) is a new 4D detector developed based on the Low
Gain Avalanche Diode (LGAD) technology, which can accurately measure the time
and spatial information of particles. Institute of High Energy Physics (IHEP)
designed a large-size AC-LGAD with a pitch of 2000 {\mu}m and AC pad of 1000
{\mu}m, and explored the effect of N+ layer dose on the spatial resolution and
time resolution. The spatial resolution varied from 32.7 {\mu}m to 15.1 {\mu}m
depending on N+ dose. The time resolution does not change significantly at
different N+ doses, which is about 15-17 ps. AC-LGAD with a low N+ dose has a
large attenuation factor and better spatial resolution. Large signal
attenuation factor and low noise level are beneficial to improve the spatial
resolution of the AC-LGAD sensor
Characterisation of Spatial and Timing Resolution of IHEP AC-LGAD Strip
AC-coupled LGAD(AC-LGAD) Strip is a new design of LGAD that allows
high-precision detection of particle spatiotemporal information whereas
reducing the density of readout electronics. For AC-LGAD Strips, there is
limited research on the impact of different strip pitches on the spatiotemporal
detection performance at the small amount of injected charge. The Institute of
High Energy Physics has designed an AC-LGAD Strip prototype with pitches of 150
, 200 , and 250 . The spatial and timing resolutions of
the prototype are studied through the laser Transient Current Technique (TCT)
scan with different amounts of injected charge. The results show that both the
spatial and timing resolution improves as the strip pitch decreases. Increases
in both temporal and spatial resolutions as the amount of charge injected
increases are observed. The spatial and timing resolution is better than 60 ps
and 40 at 1 Minimum Ionizing Particle (MIP), and better than 10 ps and
5 at 40 MIPs. Increasing Signal-to-Noise Ratio (SNR) is the key to
improving spatial and temporal resolution, whereas increasing the signal
attenuation rate by reducing the gap between adjacent electrodes also helps to
improve spatial resolution. The enhancements of spatial and timing resolutions
by both SNR and signal attenuation rate decrease with increasing amount of MIP.
This study can help design and optimize the AC-LGAD Strip detectors and readout
electronics
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