Curvature properties and Shafarevich conjecture for toroidal compactifications of ball quotients

We study toroidal compactifications of finite volume complex hyperbolic manifolds. We obtain results on the existence or nonexistence of K\"ahler metrics satisfying certain nonpositive curvature properties on these compactifications. Starting from quotients of complex hyperbolic space by deep enough non-uniform arithmetic lattices, we also verify the Shafarevich conjecture for their compactifications, by showing that their universal covers are Stein.Comment: 26 pages, comments welcome

Modélisation de l’observance et détermination de son impact biopharmaceutique

L’observance, qui décrit à quel degré le patient suit la prescription, est un facteur essentiel pour que le traitement réussisse. Les observances des patients varient beaucoup et l’efficacité du médicament varie parallèlement. Par conséquent, il faut avoir des paramètres sensibles et fiables pour mesurer l’observance. Dans la littérature, on trouve beaucoup de paramètres pour évaluer l’observance mais leurs avantages, limites et inconvénients, en ce qui concerne l’évaluation de l’impact de l’observance sur les effets des médicaments n’ont pas encore été étudiés en profondeur. L’évaluation de ces paramètres nécessite de les tester dans différentes situations. Comme les données disponibles sur l’observance ne concernent pas un ensemble exhaustif de situations, le recours à la simulation, en s’inspirant des cas réels ou plausibles, est très pertinent. On a ainsi réussi à développer un modèle dont les paramètres sont simples et compréhensibles et qui est pratique et flexible pour simuler les différents cas et même les cas extrêmes de l’observance. On a proposé de nouveaux paramètres pour mesurer l’impact biopharmaceutique de l’observance. Ensuite, on a comparé la performance, en termes de sensibilité et la fiabilité, des paramètres proposés et celles de paramètres déjà utilisés. En conclusion, on peut souligner qu’il n’y a pas de paramètre parfait étant donné que chacun a ses propres limites. Par exemple, pour les médicaments dont les effets sont directement liés aux leurs concentrations plasmatiques, le pourcentage des doses prises, qui est le paramètre le plus utilisé, offre la pire performance; par contre, le pourcentage des doses correctes nettes qui est un nouveau paramètre possède une bonne performance et des avantages prometteurs.Compliance, which refers to the degree of the conformity to the prescription, is an essential factor for a successful treatment. The compliances of patients vary widely and the effectiveness of medication varies in parallel. Therefore, we need to have reliable and sensible parameters to measure it. In literature, there are many parameters to describe it, but their advantages, disadvantages and limitations regarding the assessment of the impact of compliance on drug have not yet been studied in depth. The evaluation of these parameters requires testing them in different situations. As available compliance data are not exhaustive, the use of the simulation, based on real or plausible cases, is very relevant. We succeeded to develop a model whose parameters are simple and understandable and which is convenient and flexible to simulate the different cases and even the extreme cases of compliance. We proposed new parameters for measuring the biopharmaceutical impact of compliance. Then, we compared the performance, in terms of sensibility and reliability, of these parameters and those already used to assess compliance and discussed their performances and limitations. In conclusion, we can emphasize that there is no ideal parameter since each one has its own limitations. For example, for drugs whose effects are directly related to their plasma concentrations, the percentage of taken doses, which is the most used parameter, has the worst performance, on the other hand, the percentage of the weighted correct doses, which is a new parameter, possesses a good performance and promising advantages

Limited sampling strategies for estimation of cyclosporine exposure in pediatric hematopoietic stem cell transplant recipients : methodological improvement and introduction of sampling time deviation analysis

Le suivi thérapeutique est recommandé pour l’ajustement de la dose des agents immunosuppresseurs. La pertinence de l’utilisation de la surface sous la courbe (SSC) comme biomarqueur dans l’exercice du suivi thérapeutique de la cyclosporine (CsA) dans la transplantation des cellules souches hématopoïétiques est soutenue par un nombre croissant d’études. Cependant, pour des raisons intrinsèques à la méthode de calcul de la SSC, son utilisation en milieu clinique n’est pas pratique. Les stratégies d’échantillonnage limitées, basées sur des approches de régression (R-LSS) ou des approches Bayésiennes (B-LSS), représentent des alternatives pratiques pour une estimation satisfaisante de la SSC. Cependant, pour une application efficace de ces méthodologies, leur conception doit accommoder la réalité clinique, notamment en requérant un nombre minimal de concentrations échelonnées sur une courte durée d’échantillonnage. De plus, une attention particulière devrait être accordée à assurer leur développement et validation adéquates. Il est aussi important de mentionner que l’irrégularité dans le temps de la collecte des échantillons sanguins peut avoir un impact non-négligeable sur la performance prédictive des R-LSS. Or, à ce jour, cet impact n’a fait l’objet d’aucune étude. Cette thèse de doctorat se penche sur ces problématiques afin de permettre une estimation précise et pratique de la SSC. Ces études ont été effectuées dans le cadre de l’utilisation de la CsA chez des patients pédiatriques ayant subi une greffe de cellules souches hématopoïétiques. D’abord, des approches de régression multiple ainsi que d’analyse pharmacocinétique de population (Pop-PK) ont été utilisées de façon constructive afin de développer et de valider adéquatement des LSS. Ensuite, plusieurs modèles Pop-PK ont été évalués, tout en gardant à l’esprit leur utilisation prévue dans le contexte de l’estimation de la SSC. Aussi, la performance des B-LSS ciblant différentes versions de SSC a également été étudiée. Enfin, l’impact des écarts entre les temps d’échantillonnage sanguins réels et les temps nominaux planifiés, sur la performance de prédiction des R-LSS a été quantifié en utilisant une approche de simulation qui considère des scénarios diversifiés et réalistes représentant des erreurs potentielles dans la cédule des échantillons sanguins. Ainsi, cette étude a d’abord conduit au développement de R-LSS et B-LSS ayant une performance clinique satisfaisante, et qui sont pratiques puisqu’elles impliquent 4 points d’échantillonnage ou moins obtenus dans les 4 heures post-dose. Une fois l’analyse Pop-PK effectuée, un modèle structural à deux compartiments avec un temps de délai a été retenu. Cependant, le modèle final - notamment avec covariables - n’a pas amélioré la performance des B-LSS comparativement aux modèles structuraux (sans covariables). En outre, nous avons démontré que les B-LSS exhibent une meilleure performance pour la SSC dérivée des concentrations simulées qui excluent les erreurs résiduelles, que nous avons nommée « underlying AUC », comparée à la SSC observée qui est directement calculée à partir des concentrations mesurées. Enfin, nos résultats ont prouvé que l’irrégularité des temps de la collecte des échantillons sanguins a un impact important sur la performance prédictive des R-LSS; cet impact est en fonction du nombre des échantillons requis, mais encore davantage en fonction de la durée du processus d’échantillonnage impliqué. Nous avons aussi mis en évidence que les erreurs d’échantillonnage commises aux moments où la concentration change rapidement sont celles qui affectent le plus le pouvoir prédictif des R-LSS. Plus intéressant, nous avons mis en exergue que même si différentes R-LSS peuvent avoir des performances similaires lorsque basées sur des temps nominaux, leurs tolérances aux erreurs des temps d’échantillonnage peuvent largement différer. En fait, une considération adéquate de l'impact de ces erreurs peut conduire à une sélection et une utilisation plus fiables des R-LSS. Par une investigation approfondie de différents aspects sous-jacents aux stratégies d’échantillonnages limités, cette thèse a pu fournir des améliorations méthodologiques notables, et proposer de nouvelles voies pour assurer leur utilisation de façon fiable et informée, tout en favorisant leur adéquation à la pratique clinique.Therapeutic drug monitoring is recommended for dose adjustment of potent immunosuppressive agents. Accumulating evidence supports the usefulness of the area under the curve (AUC) for monitoring cyclosporine (CsA) in hematopoietic stem cell transplantation (HSCT). However, the use of AUC in clinical settings is restricted for practical reasons. Limited sampling strategies using regression (R-LSS) and Bayesian (B-LSS) approaches have been used to estimate AUC. However, for adequate application in clinical settings, these LSS approaches should be convenient in terms of the number of required concentration-time points as well as the duration of sampling. Furthermore, a particular attention should be given to ensure their adequate development and validation. Moreover, irregularity in the time of blood sample collection may have a non-negligible impact on the prediction performance of R-LSS; this impact has not yet been studied. The investigation of these issues is the main focus of the current study in order to ultimately achieve convenient and reliable estimation of AUC using LSS. Pediatric HSCT patients receiving intravenous (IV) and oral (PO) CsA were investigated. Thorough regression and population-pharmacokinetic (Pop-PK) analyses were carried out in order to adequately develop and validate LSS. Several Pop-PK models were evaluated while bearing in mind their intended use for AUC estimation. The performance of B-LSS for targeting different versions of AUC was also investigated. Moreover, the impact of the deviations of actual sampling times from the planned nominal times on R-LSS prediction performance, in diverse sampling time deviation (STD) scenarios, was examined using a simulation approach. These investigations led to the identification of LSS that have clinically acceptable predictive performance. These LSS are suitable for clinical application since they require 4 or fewer sampling points drawn within 4 hours post-dose. Besides, following the Pop-PK analysis, a two-compartment structural model with a lag time and a combined additive and proportional error was retained. However, the final covariate model did not improve B-LSS performance. It turned out that the structural models (without covariates) had a better performance. Moreover, B-LSS performed better for the estimation of the ‘underlying’ AUC derived from the Pop-PK simulated concentrations that exclude the residual errors, compared to their predictions of the observed AUC directly calculated using measured concentrations. Finally, our results showed that time deviation in blood sample collection have a significant impact on R-LSS prediction performance. This impact depends on the number of the involved samples, but more importantly on the duration of the sampling process. Furthermore, sampling errors at time points at which the concentration changes rapidly are critical for AUC prediction. Moreover, we have shown that R-LSS may have similar performance in terms of nominal times, but their tolerance to STD can be quite different. Hence, adequate consideration of the impact of STD can lead to a more reliable selection and use of R-LSS. This thesis provided a thorough investigation of different issues related to LSS. Methodological improvement and proposition of new avenues have been realized while giving a careful consideration to ensure a convenient use in real-life clinical practice

Industrial Perspective on Deep Brain Stimulation: History, Current State, and Future Developments

Deep brain stimulation (DBS) emerged in the late 1960s as a possible therapeutic alternative to lesioning in patients with severe, chronic, intractable pain. DBS devices in the era were based on cardiac pacing technology but were greatly modified in implementation due to the unique needs of DBS. Clinical studies in the 1970s and early 1980s have revealed a technique with modest results which did not lead to regulatory approval for the treatment of pain. In the 1980s a new application for DBS emerged in the treatment of movement disorders. Clinical trials confirmed the robustness of the therapy leading to approvals by regulatory authorities in the US and Europe for the treatment of tremor and the symptoms of Parkinson’s disease. Technology based on that used for earlier clinical research in pain was improved by leveraging advances in cardiac pacing technology resulting in the sophisticated and reliable systems available today. In the 1990s scientific exploration began in the treatment of psychiatric disorders which is ongoing today. Simultaneously, studies into the treatment of epilepsy were begun which resulted in regulatory approval in Europe. Suggestions have been made to expand these scientific explorations to other central nervous system dysfunctions. Opportunity remains to improve the technology including individualized and symptom specific stimulation patterns, more physician and patient friendly programming, and possibly closed-loop systems for more situation dependent and effective therapy

Solving Course Selection Problem by a Combination of Correlation Analysis and Analytic Hierarchy Process

In the universities where students have a chance to select and enroll in a particular course, they require special support to avoid the wrong combination of courses that might lead to delay their study. Analysis shows that the students' selection is mainly influenced by list of factors which we categorized them into three groups of concern: course factors, social factors, and individual factors. This paper proposed a two-phased model where the most correlated courses are generated and prioritized based on the student preferences. At this end, we have applied the multi-criteria analytic hierarchy process (MC-AHP) in order to generate the optimum set of courses from the available courses pool. To validate the model, we applied it to the data from students of the Information System Department at Taibah University, Kingdom of Saudi Arabia.

The Potential of Chrysanthemum and Pelargonium for Phytoextraction of Lead - Contaminated Soils

Phytoremediation is a set of technologies that uses plants to clean up contaminated soils and groundwater. Phytoremediation is environmentally friendly, successful and cost-effective compared to other in situ methods such as the electrokinetic method. In this work, two local plant species, Chrysanthemum and Pelargonium, were examined for their ability to uptake lead from lead contaminated soils (1000 ppm). Additionally, two types of soils were used for the phytoremediation study. The first soil was a silty clay soil, and the second was a carefully designed mixture of commercially available peat moss (33%), peyrlaite (16%), sand (16%), clay (17%) and organic “manure” fertilizer (18%). Commercially available pots as well as especially designed and manufactured pots were used for the phytoremediation experiments. Chrysanthemum showed greater potential for lead accumulation than Pelargonium. Chrysanthemum reduced lead from about1000 ppm to about 276 ppm in the soil in five months only. Most of the lead was found in the roots of the plant (73%), while 11%, 9% and 7% was found in the stems, leaves and flowers, respectively. Pelargonium, however, was not as effective as Chrysanthemum. Pelargonium reduced lead concentrations from about 1400 ppm to about 900 ppm

The effect of training set size in authorship attribution: application on short arabic texts

Authorship attribution (AA) is a subfield of linguistics analysis, aiming to identify the original author among a set of candidate authors. Several research papers were published and several methods and models were developed for many languages. However, the number of related works for Arabic is limited. Moreover, investigating the impact of short words length and training set size is not well addressed. To the best of our knowledge, no published works or researches, in this direction or even in other languages, are available. Therefore, we propose to investigate this effect, taking into account different stylomatric combination. The Mahalanobis distance (MD), Linear Regression (LR), and Multilayer Perceptron (MP) are selected as AA classifiers. During the experiment, the training dataset size is increased and the accuracy of the classifiers is recorded. The results are quite interesting and show different classifiers behaviours. Combining word-based stylomatric features with n-grams provides the best accuracy reached in average 93%

Personification in the Islamic archecture from positive and negative views and its results

  The research gives a clear image about Personification from the role of jurists and caliphs and what they serve in this field. Personification taboo or not ? and the results of that taboo. From the development of the written, the plants, and the engeering ornamention . thus, come out the muslim artist.they decorated the mosques with many painting. Some of them continued the process of Personification as a result of caliphs promotion. And the Ummayad palacs are an evidence about that. Although it was far from the religious Personification.Bringing the promising artists and led to the development and prosperity at the same time raised the anger and resentment some of the men ofreligion and that the more hotred increased evidence the photograghy, photograghy schools. These schools have left with thousands of images, great graphics. The saying of prohibiting the diagnosis is not with Allah some thing went of. Prohibition say a negative impact in some cases and the same time of the impact.Aparallel positive thus pay the muslim artist to search for new means of