1,794 research outputs found
Simulating all non-signalling correlations via classical or quantum theory with negative probabilities
Many-party correlations between measurement outcomes in general probabilistic
theories are given by conditional probability distributions obeying the
non-signalling condition. We show that any such distribution can be obtained
from classical or quantum theory, by relaxing positivity constraints on either
the mixed state shared by the parties, or the local functions which generate
measurement outcomes. Our results apply to generic non-signalling correlations,
but in particular they yield two distinct quasi-classical models for quantum
correlations.Comment: 6 page
Reversible Dynamics in Strongly Non-Local Boxworld Systems
In order to better understand the structure of quantum theory, or speculate
about theories that may supercede it, it can be helpful to consider alternative
physical theories. ``Boxworld'' describes one such theory, in which all
non-signaling correlations are achievable. In a limited class of multipartite
Boxworld systems - wherein all subsystems are identical and all measurements
have the same number of outcomes - it has been demonstrated that the set of
reversible dynamics is `trivial', generated solely by local relabellings and
permutations of subsystems. We develop the convex formalism of Boxworld to give
an alternative proof of this result, then extend this proof to all multipartite
Boxworld systems, and discuss the potential relevance to other theories. These
results lend further support to the idea that the rich reversible dynamics in
quantum theory may be the key to understanding its structure and its
informational capabilities.Comment: 5 pages + appendice
Information causality from an entropic and a probabilistic perspective
The information causality principle is a generalisation of the no-signalling
principle which implies some of the known restrictions on quantum correlations.
But despite its clear physical motivation, information causality is formulated
in terms of a rather specialised game and figure of merit. We explore different
perspectives on information causality, discussing the probability of success as
the figure of merit, a relation between information causality and the non-local
`inner-product game', and the derivation of a quadratic bound for these games.
We then examine an entropic formulation of information causality with which one
can obtain the same results, arguably in a simpler fashion.Comment: 7 pages, v2: some references added and minor improvement
Inhibition of Rac 1 Protect Against Platelet Induced Liver and Kidney ‎Injury in Diabetes Mellitus
Diabetes mellitus both (Type 1 and Type 2) are one of the common causes for activation of platelet. Inflammation-induced abnormal platelet function contributes to chronic complications, which are the leading causes of death and morbidity among diabetics. Rac1 has been shown to regulate a variety of platelet functions; predicted Rac1could regulate platelet release of CXCL4, which leads to kidney injury in Diabetes Mellitus. Diabetes mellitus' effect on Rac1 activation, a 21kD G-protein implicated in platelet activation, was investigated and platelet induced inflammation and kidney injury. Swiss albino male mice were pretreated with 5 mg/kg of a specific Rac1 inhibitor NSC23766 and injected with (45 mg/kg body wt.) streptozotocin, twice for five days. Moreover, the concentration of serum chemokines CXCL4 were assayed using ELISA and histology score for kidney were examined. Our results showed that Diabetes mellitus was induced in mice by streptozotocin. In addition, platelet chemokines (CXCL4) were markedly higher in diabetic mice when compared to the sham (control) group. Moreover, pretreatment with NSC23766 decreased liver and kidney injury assessed by histology score, P-value <0.05. Our study reveals that Rac1 has a critical role in platelet chemokines secretion due to diabetes-induced inflammation in the liver and kidneys, targeting Rac1 could be a target for innovative treatment to control inflammation in diabetic individual. Targeting platelets involved in inflammatory pathways could be part of a strategy in order to control and manage diabetes and its consequences
The JK System to Detect Plagiarism
In this research a system, referred to as Jubair-Khaireddin (JK), has been developed to assess the degree of similarity between two programs even though they look superficially dissimilar. The JK system has the capability to detect deliberate attempts of plagiarism. Reverse engineering technique is used to bring each suspected program back to its initial specification stage. This operation enables us to extract the structure of the program which is an important factor in detecting plagiarism. This can be achieved through the extraction of the Static Execution Tree (SET) for each program. The SET is then transformed into Terminating Binary Sequence (TBS). The TBSs generated from the tested programs are compared in order to get similar branches. Reengineering technique is then applied on these similar branches in order to compute its entropy (information content). The entropy is computed to prove or disprove the existence of similarities between programs. The JK system has been tested on different Java programs with different modifications, and proved successful in detecting almost all cases including those of partially plagiarised programs.Facultad de Informátic
Peningkatan Aktivitas Belajar Siswa dalam Pembelajaran IPA dengan Metode Demonstrasi di Sekolah Dasar
The purpose of this research in general is to improve this quality of science teaching practices though enchanced student learning activities in class V 001 public elementary school district, the district Tambelan Bintan. The method used is descriptipe methode. There is an in crease in student learning activities 22% of its initial I cycle increased to 40,5% in the second cycle of learning activities of student to 68% and then became 75% in the third cycle. After briefly unsettiled IPA increased activity in learning the differece between. The increase in cycle I and cycle II of 27,5%. Late in the cycle II to cycle III increased to 7%. This the averange achivement of students learning activities in cycle 1 and II are high compared with the cycle in category III which can be low
Editorial [to] Analysis of nonlinear dynamics of neural networks
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