Développement de méthodologies en un seul pot impliquant une réaction de méthylénation : utilisation de complexes d'iridium dans les réactions d'oléfination

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal

A Manifest-Based Framework for Organizing the Management of Personal Data at the Edge of the Network

Smart disclosure initiatives and new regulations such as GDPR allow individuals to get the control back on their data by gathering their entire digital life in a Personal Data Management Systems (PDMS). Multiple PDMS architectures exist, from centralized web hosting solutions to self-data hosting at home. These solutions strongly differ on their ability to preserve data privacy and to perform collective computations crossing data of multiple individuals (e.g., epidemiological or social studies) but none of them satisfy both objectives. The emergence of Trusted Execution Environments (TEE) changes the game. We propose a solution called Trusted PDMS, combining the TEE and PDMS properties to manage the data of each individual, and a Manifest-based framework to securely execute collective computation on top of them. We demonstrate the practicality of the solution through a real case-study being conducted over 10.000 patients in the healthcare field

crisis management between organization strategy and the actors strategies

لم تعد الأزمة مجرد حالة استثنائية بل أصبحت ظاهرة مألوفة وصفة غالبة، فالأحداث المتلاحقة والتطورات التي تعيشها المجتمعات والمنظمات اليوم تتطلب ضرورة اعداد خطط تمكنها من تحقيق الجاهزية المرتفعة والتنبؤ المبكر بالأزمة، إذ لا تكمن المشكلة في حدوث الأزمة بل في ردود فعلنا تجاهها، فإدارة الأزمات لم تعد تعتمد على اللوائح والقوانين المتعلقة بالطوارئ بل أصبحت استراتيجيات إدارية دقيقة وواضحة. وكما للمنظمة استراتيجياتها كذلك للفاعلين استراتيجياتهم.The crisis is not only an exceptional case, but has become a familiar and dominant phenomenon. The successive events and developments that societies and organizations are experiencing today require the necessity to prepare plans that enable them to achieve high readiness and early prediction of the crisis, as the problem is not the occurrence of the crisis but rather in our reactions to it. They are no longer dependent on regulations and laws related to emergencies, but rather have become accurate and clear management strategies. As the organization has its strategies, so do the actors

ANTIOXIDANT, ANTI-INFLAMMATORY AND DIABETES RELATED ENZYME INHIBITION PROPERTIES OF LEAVES EXTRACT FROM SELECTED VARIETIES OF PHOENYX DACTYLIFERA L.

Objective: to investigate the antioxidant, anti-inflammatory, and antidiabetic activities of ethanolic leaves extracts of three selected varieties of Phoenyx dactylifera L. namely: Gharsâ€, Deglet Nour†and Hamrayaâ€. Methods: The assessment of the antioxidant potential of crude leaves extracts, using superoxide anions inhibition, DPPH and total antioxidant activity essays, was carried out. Furthermore, the anti-inflammatory properties of the extracts were determined by measuring the inhibition of nitric oxide (NO) production. Moreover, the antidiabetic effect was evaluated by inhibition of α-amylase and α-glucosidase enzymes. The total phenolic content measured by Folin-ciocalteu method was as well conducted. Results: The raw leaves extracts of the selected varieties was found to contain a high content of total phenolic content (342.45 mg GAE/ gDW for GE) and therefore exhibited a higher antioxidant activity and inhibitory effect of radicals scavenging activity against DPPH and superoxide anion (IC50=7.44 μg/mL and 39.11 μg/mL respectively). The three varieties exhibited significant anti-inflammatory effects using in-vitro inhibition of NO (IC50=240.28 μg/mL for GE). The extracts also displayed high inhibition actions against α-amylase. Conclusion: the results suggest that the leaves of the three selected varieties of Phoenyx dactylifera can be considered as a good source of natural antioxidant and anti-inflammation drugs as well as potent antidiabetic medicine

Mitigating Leakage from Data Dependent Communications in Decentralized Computing using Differential Privacy

Imagine a group of citizens willing to collectively contribute their personal data for the common good to produce socially useful information, resulting from data analytics or machine learning computations. Sharing raw personal data with a centralized server performing the computation could raise concerns about privacy and a perceived risk of mass surveillance. Instead, citizens may trust each other and their own devices to engage into a decentralized computation to collaboratively produce an aggregate data release to be shared. In the context of secure computing nodes exchanging messages over secure channels at runtime, a key security issue is to protect against external attackers observing the traffic, whose dependence on data may reveal personal information. Existing solutions are designed for the cloud setting, with the goal of hiding all properties of the underlying dataset, and do not address the specific privacy and efficiency challenges that arise in the above context. In this paper, we define a general execution model to control the data-dependence of communications in user-side decentralized computations, in which differential privacy guarantees for communication patterns in global execution plans can be analyzed by combining guarantees obtained on local clusters of nodes. We propose a set of algorithms which allow to trade-off between privacy, utility and efficiency. Our formal privacy guarantees leverage and extend recent results on privacy amplification by shuffling. We illustrate the usefulness of our proposal on two representative examples of decentralized execution plans with data-dependent communications

OPTASSIST: A RELATIONAL DATA WAREHOUSE OPTIMIZATION ADVISOR

Data warehouses store large amounts of data usually accessed by complex decision making queries with many selection, join and aggregation operations. To optimize the performance of the data warehouse, the administrator has to make a physical design. During physical designphase, the Data Warehouse Administrator has to select some optimization techniques to speed up queries. He must make many choices as optimization techniques to perform,their selection algorithms, parametersof these algorithms and the attributes and tables used by some of these techniques. We describe in this paper the nature of the difficulties encountered by the administrator during physical design. We subsequently present a tool which helps the administrator to make the right choicesfor optimization. We demonstrate the interactive use of this tool using a relational data warehouse created and populated from the APB-1 Benchmark

Starch digestion in pearl millet (<i>Pennisetum glaucum</i> (L.) R. Br.) flour from arid area of Algeria

To assess the nutritive value of minor cereals cultivated in arid areas of Algeria, nine pearl millet landraces were sampled from two regions: Tidikelt and Hoggar. Some qualitative and quantitative characters of the panicle and grain were measured, as well as in vitro starch digestion of the grain flour. Considerable variation was recorded in seed color, endosperm texture and nutritional value of starch and protein content. In vitro starch digestion displayed a first-order kinetic model. For all pearl millet landraces, starch was digested to a different extent; the hydrolysis index (HI) ranged from 22.29% to 35.52% and the expected glycemic index (eGI) ranged from 27.41 to 38.82. The results show that there is diversity in the physical and chemical properties of pearl millet accessions from the arid areas of Algeria: Tidikelt and Hoggar. This study confirms that pearl millet has an acceptable nutritional value with a low glycemic index suitable for human health and nutrition

Impact of credibility on opinion analysis in social media

© 2018 IOS Press. All rights reserved. In conjunction with the rapid growth and adoption of social media, people are more and more willing to share their personal experiences and opinions about products and/or services with the community. Opinions could be the basis of developing systems that would advise future users on how to proceed with any purchase without risking any disappointment. Unfortunately, opinions are not always genuine due to for instance, biased users as well as mixed feedback coming from the same users (i.e., multi-identity). This paper presents an approach for opinion analysis using credibility as a decisive criterion for supporting future users make sound decisions. The effectiveness of this approach has been tested using opinions posted on Twitter

Databases and Information Systems in the AI Era: Contributions from ADBIS, TPDL and EDA 2020 Workshops and Doctoral Consortium

Research on database and information technologies has been rapidly evolving over the last couple of years. This evolution was lead by three major forces: Big Data, AI and Connected World that open the door to innovative research directions and challenges, yet exploiting four main areas: (i) computational and storage resource modeling and organization; (ii) new programming models, (iii) processing power and (iv) new applications that emerge related to health, environment, education, Cultural Heritage, Banking, etc. The 24th East-European Conference on Advances in Databases and Information Systems (ADBIS 2020), the 24th International Conference on Theory and Practice of Digital Libraries (TPDL 2020) and the 16th Workshop on Business Intelligence and Big Data (EDA 2020), held during August 25–27, 2020, at Lyon, France, and associated satellite events aimed at covering some emerging issues related to database and information system research in these areas. The aim of this paper is to present such events, their motivations, and topics of interest, as well as briefly outline the papers selected for presentations. The selected papers will then be included in the remainder of this volume

Mechanism and Enantioselectivity in Palladium-Catalyzed Conjugate Addition of Arylboronic Acids to β‑Substituted Cyclic Enones: Insights from Computation and Experiment

Enantioselective conjugate additions of arylboronic acids to β-substituted cyclic enones have been previously reported from our laboratories. Air- and moisture-tolerant conditions were achieved with a catalyst derived in situ from palladium(II) trifluoroacetate and the chiral ligand (S)-t-BuPyOx. We now report a combined experimental and computational investigation on the mechanism, the nature of the active catalyst, the origins of the enantioselectivity, and the stereoelectronic effects of the ligand and the substrates of this transformation. Enantioselectivity is controlled primarily by steric repulsions between the t-Bu group of the chiral ligand and the α-methylene hydrogens of the enone substrate in the enantiodetermining carbopalladation step. Computations indicate that the reaction occurs via formation of a cationic arylpalladium(II) species, and subsequent carbopalladation of the enone olefin forms the key carbon–carbon bond. Studies of nonlinear effects and stoichiometric and catalytic reactions of isolated (PyOx)Pd(Ph)I complexes show that a monomeric arylpalladium–ligand complex is the active species in the selectivity-determining step. The addition of water and ammonium hexafluorophosphate synergistically increases the rate of the reaction, corroborating the hypothesis that a cationic palladium species is involved in the reaction pathway. These additives also allow the reaction to be performed at 40 °C and facilitate an expanded substrate scope