Ore-degree threshold for the square of a Hamiltonian cycle

A classic theorem of Dirac from 1952 states that every graph with minimum degree at least n/2 contains a Hamiltonian cycle. In 1963, P\'osa conjectured that every graph with minimum degree at least 2n/3 contains the square of a Hamiltonian cycle. In 1960, Ore relaxed the degree condition in the Dirac's theorem by proving that every graph with $deg(u) + deg(v) \geq n$ for every $uv \notin E(G)$ contains a Hamiltonian cycle. Recently, Ch\^au proved an Ore-type version of P\'osa's conjecture for graphs on $n\geq n_0$ vertices using the regularity--blow-up method; consequently the $n_0$ is very large (involving a tower function). Here we present another proof that avoids the use of the regularity lemma. Aside from the fact that our proof holds for much smaller $n_0$, we believe that our method of proof will be of independent interest.Comment: 24 pages, 1 figure. In addition to some fixed typos, this updated version contains a simplified "connecting lemma" in Section 3.

Permissioned Blockchain-Based Security for SDN in IoT Cloud Networks

The advancement in cloud networks has enabled connectivity of both traditional networked elements and new devices from all walks of life, thereby forming the Internet of Things (IoT). In an IoT setting, improving and scaling network components as well as reducing cost is essential to sustain exponential growth. In this domain, software-defined networking (SDN) is revolutionizing the network infrastructure with a new paradigm. SDN splits the control/routing logic from the data transfer/forwarding. This splitting causes many issues in SDN, such as vulnerabilities of DDoS attacks. Many solutions (including blockchain based) have been proposed to overcome these problems. In this work, we offer a blockchain-based solution that is provided in redundant SDN (load-balanced) to service millions of IoT devices. Blockchain is considered as tamper-proof and impossible to corrupt due to the replication of the ledger and consensus for verification and addition to the ledger. Therefore, it is a perfect fit for SDN in IoT Networks. Blockchain technology provides everyone with a working proof of decentralized trust. The experimental results show gain and efficiency with respect to the accuracy, update process, and bandwidth utilization.Comment: Accepted to International Conference on Advances in the Emerging Computing Technologies (AECT) 202

Language Independent Sentiment Analysis

Social media platforms and online forums generate rapid and increasing amount of textual data. Businesses, government agencies, and media organizations seek to perform sentiment analysis on this rich text data. The results of these analytics are used for adapting marketing strategies, customizing products, security and various other decision makings. Sentiment analysis has been extensively studied and various methods have been developed for it with great success. These methods, however apply to texts written in a specific language. This limits applicability to a limited demographic and a specific geographic region. In this paper we propose a general approach for sentiment analysis on data containing texts from multiple languages. This enables all the applications to utilize the results of sentiment analysis in a language oblivious or language-independent fashion

Short-Term Load Forecasting Using AMI Data

Accurate short-term load forecasting is essential for efficient operation of the power sector. Predicting load at a fine granularity such as individual households or buildings is challenging due to higher volatility and uncertainty in the load. In aggregate loads such as at grids level, the inherent stochasticity and fluctuations are averaged-out, the problem becomes substantially easier. We propose an approach for short-term load forecasting at individual consumers (households) level, called Forecasting using Matrix Factorization (FMF). FMF does not use any consumers' demographic or activity patterns information. Therefore, it can be applied to any locality with the readily available smart meters and weather data. We perform extensive experiments on three benchmark datasets and demonstrate that FMF significantly outperforms the computationally expensive state-of-the-art methods for this problem. We achieve up to 26.5% and 24.4 % improvement in RMSE over Regression Tree and Support Vector Machine, respectively and up to 36% and 73.2% improvement in MAPE over Random Forest and Long Short-Term Memory neural network, respectively

Immunoinformatics design of multivalent epitope vaccine against monkeypox virus and its variants using membrane-bound, enveloped, and extracellular proteins as targets

IntroductionThe current monkeypox (MPX) outbreak, caused by the monkeypox virus (MPXV), has turned into a global concern, with over 59,000 infection cases and 23 deaths worldwide.ObjectivesHerein, we aimed to exploit robust immunoinformatics approach, targeting membrane-bound, enveloped, and extracellular proteins of MPXV to formulate a chimeric antigen. Such a strategy could similarly be applied for identifying immunodominant epitopes and designing multi-epitope vaccine ensembles in other pathogens responsible for chronic pathologies that are difficult to intervene against.MethodsA reverse vaccinology pipeline was used to select 11 potential vaccine candidates, which were screened and mapped to predict immunodominant B-cell and T-cell epitopes. The finalized epitopes were merged with the aid of suitable linkers, an adjuvant (Resuscitation-promoting factor), a PADRE sequence (13 aa), and an HIV TAT sequence (11 aa) to formulate a multivalent epitope vaccine. Bioinformatics tools were employed to carry out codon adaptation and computational cloning. The tertiary structure of the chimeric vaccine construct was modeled via I-TASSER, and its interaction with Toll-like receptor 4 (TLR4) was evaluated using molecular docking and molecular dynamics simulation. C-ImmSim server was implemented to examine the immune response against the designed multi-epitope antigen.Results and discussionThe designed chimeric vaccine construct included 21 immunodominant epitopes (six B-cell, eight cytotoxic T lymphocyte, and seven helper T-lymphocyte) and is predicted non-allergen, antigenic, soluble, with suitable physicochemical features, that can promote cross-protection among the MPXV strains. The selected epitopes indicated a wide global population coverage (93.62%). Most finalized epitopes have 70%–100% sequence similarity with the experimentally validated immune epitopes of the vaccinia virus, which can be helpful in the speedy progression of vaccine design. Lastly, molecular docking and molecular dynamics simulation computed stable and energetically favourable interaction between the putative antigen and TLR4.ConclusionOur results show that the multi-epitope vaccine might elicit cellular and humoral immune responses and could be a potential vaccine candidate against the MPXV infection. Further experimental testing of the proposed vaccine is warranted to validate its safety and efficacy profile

Prise en charge initiale de la maladie de Parkinson par les médecins généralistes en région Rhône-Alpes

Le choix thérapeutique initial dans la maladie de Parkinson agit non seulement sur la symptomatologie présentée par le patient, mais aussi sur l'évolution de la maladie. L'introduction de la Lévodopa doit être différée, notamment chez le sujet jeune, afin de retarder l'apparition des complications motrices. Néanmoins, un recours systématique au neurologue pour l'initiation thérapeutique paraît difficile étant donné 1' augmentation de la prévalence de la maladie de Parkinson avec le vieillissement de la population. Une prise en charge par les médecins généralistes peut se discuter. Or peu d'études analysent leur pratique face à cette pathologie complexe. Analyser la prise en charge initiale de la maladie de Parkinson réalisée par les médecins généralistes, afin d'évaluer si l'initiation thérapeutique par le médecin généraliste était conforme aux recommandations, au même titre que le neurologue. Nous avons réalisé une étude descriptive rétrospective. Un questionnaire informatisé a été envoyé aux médecins généralistes exerçant une activité libérale en région Rhône-Alpes. Chaque médecin généraliste pouvait renseigner le dossier clinique d'un à trois patients présentant la maladie de Parkinson. Leur prise en charge était comparée à trois consensus, français et européens. Notre étude incluait 99 patients grâce à la participation de 70 médecins généralistes sur les 2607 interrogés. Le traitement de la maladie de Parkinson était initié par le médecin généraliste pour 30% des patients. Sur les 99 patients, 92 avaient eu une consultation neurologique, que ce soit avant ou après l'initiation thérapeutique. Il n'y avait pas de différence statistiquement significative entre les médecins généralistes et les neurologues dans le suivi des recommandations, que ce soit pour les recommandations du texte des experts de 2000 (p 0.210), de la Haute Autorité de Santé de 2012 (p 0.924), ou de l'European Federation of Neurological Societies/Movement Disorder Society de 2013 (p 0.924). La Lévodopa seule était prescrite pour 24 patients (77%) pris en charge par le médecin généraliste (n=30) et 34 patients (49%) pris en charge par le neurologue (n=69). Pour 31 des 42 patients âgés de moins de 65 ans (74%), l'initiation thérapeutique était réalisée par un neurologue. Il prescrivait dans 55% des cas (n=17) un agoniste dopaminergique non dérivé de l'ergot de seigle seul ou en association, alors que les médecins généralistes administraient ce traitement chez un patient (9%) de cette tranche d'âge. Bien que les médecins généralistes respectent les recommandations, la prescription des agonistes dopaminergiques semble sous utilisée. Au vu de l'importance du choix thérapeutique initial dans l'évolution de la maladie, notamment chez le sujet jeune, nous conseillons une prise en charge neurologique précoce. De façon générale, le soin d'un patient parkinsonien doit être axé sur la multidisciplinarité et centré sur le patient et ses aidantsLYON1-BU Santé (693882101) / SudocSudocFranceF