Clinical Decision-Making: A Survey on the Influence of Specialty and Experience in Treatment Planning of Multidisciplinary Cases

Objective: to evaluate the effect of specialization and experience on treatment planning multidisciplinary cases. Materials and Methods: A survey presenting 7 clinical scenarios and their potential treatment plans was designed and disseminated electronically to five groups of dentists (general dentists, endodontists, prosthodontists, orthodontists, periodontists). 509 responses were collected and analyzed for distribution and levels of agreement. Results: A moderate kappa was found (k=0.4-0.6) between endodontists and periodontists and within endodontists. There was no agreement on the type of restorations that are used between different specialties and within specialties of different years of experience. Conclusion: Specialists and general dentists use a similar approach in their decisionmaking process. The more complex the clinical presentation, the more divergence there is in selecting treatment modalities. General dentists and specialists recognize the importance of periodontal health and the role of orthodontic therapy in cases of missing or affected teeth and overall treatment planning. Endodontists consistently chose root canal therapy instead of dental replacement. Work setting does not appear to influence iv treatment planning decisions. More experienced dentists (\u3e20 years) tend to choose less conservative restorative treatments when compared to newer graduates. Interdisciplinary collaboration during treatment can enhance the patient’s outcome as each specialist expands the envelope of available treatment options

Reconstruction of Exchange–Correlation Potentials from Their Matrix Representations

Within a basis set of one-electron functions that form linearly independent products (LIPs), it is always possible to construct a unique local (multiplicative) real-space potential that is precisely equivalent to an arbitrary given operator. Although standard basis sets of quantum chemistry rarely form LIPs in a numerical sense, occupied and low-lying virtual canonical Kohn–Sham orbitals often do so, at least for small atoms and molecules. Using these principles, we construct atomic and molecular exchange–correlation potentials from their matrix representations in LIP basis sets of occupied canonical Kohn–Sham orbitals. The reconstructions are found to imitate the original potentials in a consistent but exaggerated way. Since the original and reconstructed potentials produce the same ground-state electron density and energy within the associated LIP basis set, the procedure may be regarded as a rigorous solution to the Kohn–Sham inversion problem within the subspace spanned by the occupied Kohn–Sham orbitals

Multiplicative potentials for kinetic energy and exact exchange.

Harriman showed that within finite basis sets of one-electron functions that form linearly independent products (LIP), differential and integral operators can be represented exactly and unambiguously by multiplicative (local) potentials. Although almost no standard basis sets of quantum chemistry form LIPs in a numerical sense, occupied self-consistent field (SCF) orbitals routinely do so. Using minimal LIP basis sets of occupied SCF orbitals, we construct multiplicative potentials for electronic kinetic energy and exact exchange that reproduce the Hartree-Fock and Kohn-Sham Hamiltonian matrices and electron densities for atoms and molecules. The results highlight fundamental differences between local and nonlocal operators and suggest a practical possibility of developing exact kinetic energy functionals within finite basis sets by using effective local potentials

Gestion conjointe de ressources de communication et de calcul pour les réseaux sans fils à base de cloud

Mobile Edge Cloud brings the cloud closer to mobile users by moving the cloud computational efforts from the internet to the mobile edge. We adopt a local mobile edge cloud computing architecture, where small cells are empowered with computational and storage capacities. Mobile users’ offloaded computational tasks are executed at the cloud-enabled small cells. We propose the concept of small cells clustering for mobile edge computing, where small cells cooperate in order to execute offloaded computational tasks. A first contribution of this thesis is the design of a multi-parameter computation offloading decision algorithm, SM-POD. The proposed algorithm consists of a series of low complexity successive and nested classifications of computational tasks at the mobile side, leading to local computation, or offloading to the cloud. To reach the offloading decision, SM-POD jointly considers computational tasks, handsets, and communication channel parameters. In the second part of this thesis, we tackle the problem of small cell clusters set up for mobile edge cloud computing for both single-user and multi-user cases. The clustering problem is formulated as an optimization that jointly optimizes the computational and communication resource allocation, and the computational load distribution on the small cells participating in the computation cluster. We propose a cluster sparsification strategy, where we trade cluster latency for higher system energy efficiency. In the multi-user case, the optimization problem is not convex. In order to compute a clustering solution, we propose a convex reformulation of the problem, and we prove that both problems are equivalent. With the goal of finding a lower complexity clustering solution, we propose two heuristic small cells clustering algorithms. The first algorithm is based on resource allocation on the serving small cells where tasks are received, as a first step. Then, in a second step, unserved tasks are sent to a small cell managing unit (SCM) that sets up computational clusters for the execution of these tasks. The main idea of this algorithm is task scheduling at both serving small cells, and SCM sides for higher resource allocation efficiency. The second proposed heuristic is an iterative approach in which serving small cells compute their desired clusters, without considering the presence of other users, and send their cluster parameters to the SCM. SCM then checks for excess of resource allocation at any of the network small cells. SCM reports any load excess to serving small cells that re-distribute this load on less loaded small cells. In the final part of this thesis, we propose the concept of computation caching for edge cloud computing. With the aim of reducing the edge cloud computing latency and energy consumption, we propose caching popular computational tasks for preventing their re-execution. Our contribution here is two-fold: first, we propose a caching algorithm that is based on requests popularity, computation size, required computational capacity, and small cells connectivity. This algorithm identifies requests that, if cached and downloaded instead of being re-computed, will increase the computation caching energy and latency savings. Second, we propose a method for setting up a search small cells cluster for finding a cached copy of the requests computation. The clustering policy exploits the relationship between tasks popularity and their probability of being cached, in order to identify possible locations of the cached copy. The proposed method reduces the search cluster size while guaranteeing a minimum cache hit probability.Cette thèse porte sur le paradigme « Mobile Edge cloud» qui rapproche le cloud des utilisateurs mobiles et qui déploie une architecture de clouds locaux dans les terminaisons du réseau. Les utilisateurs mobiles peuvent désormais décharger leurs tâches de calcul pour qu’elles soient exécutées par les femto-cellules (FCs) dotées de capacités de calcul et de stockage. Nous proposons ainsi un concept de regroupement de FCs dans des clusters de calculs qui participeront aux calculs des tâches déchargées. A cet effet, nous proposons, dans un premier temps, un algorithme de décision de déportation de tâches vers le cloud, nommé SM-POD. Cet algorithme prend en compte les caractéristiques des tâches de calculs, des ressources de l’équipement mobile, et de la qualité des liens de transmission. SM-POD consiste en une série de classifications successives aboutissant à une décision de calcul local, ou de déportation de l’exécution dans le cloud.Dans un deuxième temps, nous abordons le problème de formation de clusters de calcul à mono-utilisateur et à utilisateurs multiples. Nous formulons le problème d’optimisation relatif qui considère l’allocation conjointe des ressources de calculs et de communication, et la distribution de la charge de calcul sur les FCs participant au cluster. Nous proposons également une stratégie d’éparpillement, dans laquelle l’efficacité énergétique du système est améliorée au prix de la latence de calcul. Dans le cas d’utilisateurs multiples, le problème d’optimisation d’allocation conjointe de ressources n’est pas convexe. Afin de le résoudre, nous proposons une reformulation convexe du problème équivalente à la première puis nous proposons deux algorithmes heuristiques dans le but d’avoir un algorithme de formation de cluster à complexité réduite. L’idée principale du premier est l’ordonnancement des tâches de calculs sur les FCs qui les reçoivent. Les ressources de calculs sont ainsi allouées localement au niveau de la FC. Les tâches ne pouvant pas être exécutées sont, quant à elles, envoyées à une unité de contrôle (SCM) responsable de la formation des clusters de calculs et de leur exécution. Le second algorithme proposé est itératif et consiste en une formation de cluster au niveau des FCs ne tenant pas compte de la présence d’autres demandes de calculs dans le réseau. Les propositions de cluster sont envoyées au SCM qui évalue la distribution des charges sur les différentes FCs. Le SCM signale tout abus de charges pour que les FCs redistribuent leur excès dans des cellules moins chargées.Dans la dernière partie de la thèse, nous proposons un nouveau concept de mise en cache des calculs dans l’Edge cloud. Afin de réduire la latence et la consommation énergétique des clusters de calculs, nous proposons la mise en cache de calculs populaires pour empêcher leur réexécution. Ici, notre contribution est double : d’abord, nous proposons un algorithme de mise en cache basé, non seulement sur la popularité des tâches de calculs, mais aussi sur les tailles et les capacités de calculs demandés, et la connectivité des FCs dans le réseau. L’algorithme proposé identifie les tâches aboutissant à des économies d’énergie et de temps plus importantes lorsqu’elles sont téléchargées d’un cache au lieu d’être recalculées. Nous proposons ensuite d’exploiter la relation entre la popularité des tâches et la probabilité de leur mise en cache, pour localiser les emplacements potentiels de leurs copies. La méthode proposée est basée sur ces emplacements, et permet de former des clusters de recherche de taille réduite tout en garantissant de retrouver une copie en cache

Enzymatic Macrocyclization of 1,2,3-Triazole Peptide Mimetics

The macrocyclization of linear peptides is very often accompanied by significant improvements in their stability and biological activity. Many strategies are available for their chemical macrocyclization, however, enzyme-mediated methods remain of great interest in terms of synthetic utility. To date, known macrocyclization enzymes have been shown to be active on both peptide and protein substrates. Here we show that the macrocyclization enzyme of the cyanobactin family, PatGmac, is capable of macrocyclizing substrates with one, two, or three 1,4-substituted 1,2,3-triazole moieties. The introduction of non-peptidic scaffolds into macrocycles is highly desirable in tuning the activity and physical properties of peptidic macrocycles. We have isolated and fully characterized nine non-natural triazole-containing cyclic peptides, a further ten molecules are also synthesized. PatGmac has now been shown to be an effective and versatile tool for the ring closure by peptide bond formation

Synthesis of hybrid cyclopeptides through enzymatic macrocyclization.

Natural products comprise a diverse array of molecules, many of which are biologically active. Most natural products are derived from combinations of polyketides, peptides, sugars, and fatty-acid building blocks. Peptidic macrocycles have attracted attention as potential therapeutics possessing cell permeability, stability, and easy-to-control variability. Here, we show that enzymes from the patellamide biosynthetic pathway can be harnessed to make macrocycles that are hybrids of amino acids and a variety of manmade chemical building blocks, including aryl rings, polyethers, and alkyl chains. We have made macrocycles with only three amino acids, one of which can be converted to a thiazoline or a thiazole ring. We report the synthesis of 18 peptide hybrid macrocycles, nine of which have been isolated and fully characterized

Energy Harvesting Wireless Sensor Networks: From Characterization to Duty Cycle Dimensioning

International audienceEnergy harvesting capabilities are challenging our understanding of wireless sensor networks by adding recharging capacity to sensor nodes. This has a significant impact on the communication paradigm, as networking mechanisms can benefit from these potentially infinite renewable energy sources. In this work, we study the consequences of implementing photovoltaic energy harvesting on the duty cycle of a wireless sensor node, in both outdoor and indoor scenarios. We show that for the static duty cycle approach in outdoor scenarios, very high duty cycles, in the order of tens of percents, are achieved. This further eliminates the need for additional energy conservation schemes. In the indoor case, our analysis shows that the dynamic duty cycle approach based solely on the battery residual energy does not necessarily achieve better results than the static approach. We identify the main reasons behind this behavior, and test new design considerations by adding information on the battery level variation to the duty cycle computation. We demonstrate that this approach always outperforms static solutions when perfect knowledge of the harvestable energy is assumed, as well as in realistic deployments, where this information is not available