<p>2-Methoxyestradiol (2-ME), a metabolite of 17β-estradiol, is a potent antitumor and antiangiogenesis agent in vitro and in vivo. This study aimed to investigate the effects of 2-ME on human cervical and endometrial cancers in vitro and in vivo. Human cervical cancer HeLaS3 cells, endometrial cancer HEC-1-A and RL-95-2 cells, and severe combined immune deficient (SCID) mice were used. On cervical cancer HeLaS3 cells, 2-ME inhibited the cell growth which is accompanied by apoptosis via iNOS pathway and by G₂/M cell cycle arrest. 2-ME had slight effects on normal cervical epithelial cells. In vivo on SCID mice, 2-ME (75 mg/kg p.o.) inhibited the growth of human cervical carcinoma by 34% (p < 0.05) and showed slight side effects to liver and spleen. On human endometrial cancer cells (HEC-1-A and RL-95-2 cells), 2-ME inhibited the growth by blocking cell cycle progress in S- and G₂/M-phase in both cell types, and by inducing apoptosis in HEC-1-A cells and by causing necrosis in RL-95-2 cells. 2-ME had no effects on normal endometrial cells. The apoptotic effect, in HEC-1-A cells, was prevented by iNOS-inhibitor 1400W and eliminated by Caspase-inhibitor Z-VAD-FMK. The necrosis, on RL-95-2 cells, was due to a severe disruption of the mitochondrial membrane potential. Unfortunately, 2-ME had no significant effects on endometrial cancer xenografts. It showed slight toxicity to liver, spleen and proliferative effect on uterus. In conclusion, 2-ME inhibits the growth of human cervical and endometrial cancer cells in vitro. However, a weaker anti-tumor effect was observed in our animal model and 2-ME was slightly toxic to liver and spleen. Considering the proliferative effect on uterus, 2-ME might not be a suitable therapeutic agent in gynecological tumors.</p>

2-Methoxyestradiol (2-ME), a metabolite of 17β-estradiol, is a potent antitumor and antiangiogenesis agent in vitro and in vivo. This study aimed to investigate the effects of 2-ME on human cervical and endometrial cancers in vitro and in vivo. Human cervical cancer HeLaS3 cells, endometrial cancer HEC-1-A and RL-95-2 cells, and severe combined immune deficient (SCID) mice were used. On cervical cancer HeLaS3 cells, 2-ME inhibited the cell growth which is accompanied by apoptosis via iNOS pathway and by G2/M cell cycle arrest. 2-ME had slight effects on normal cervical epithelial cells. In vivo on SCID mice, 2-ME (75 mg/kg p.o.) inhibited the growth of human cervical carcinoma by 34% (p &lt; 0.05) and showed slight side effects to liver and spleen. On human endometrial cancer cells (HEC-1-A and RL-95-2 cells), 2-ME inhibited the growth by blocking cell cycle progress in S- and G2/M-phase in both cell types, and by inducing apoptosis in HEC-1-A cells and by causing necrosis in RL-95-2 cells. 2-ME had no effects on normal endometrial cells. The apoptotic effect, in HEC-1-A cells, was prevented by iNOS-inhibitor 1400W and eliminated by Caspase-inhibitor Z-VAD-FMK. The necrosis, on RL-95-2 cells, was due to a severe disruption of the mitochondrial membrane potential. Unfortunately, 2-ME had no significant effects on endometrial cancer xenografts. It showed slight toxicity to liver, spleen and proliferative effect on uterus. In conclusion, 2-ME inhibits the growth of human cervical and endometrial cancer cells in vitro. However, a weaker anti-tumor effect was observed in our animal model and 2-ME was slightly toxic to liver and spleen. Considering the proliferative effect on uterus, 2-ME might not be a suitable therapeutic agent in gynecological tumors.

New materials and new fabrication techniques in turbomachinery lead to monolithic<p>structures with extremely low damping which may be responsible for severe vibrations<p>and possible high-cycle fatigue problems. To solve this, various techniques<p>of damping enhancement are under investigation. The present work is focused on<p>piezoelectric shunt damping.<p>This thesis considers the RL shunt damping of rotationally periodic structures using<p>an array of piezoelectric patches, with an application to a bladed drum representative<p>of those used in turbomachinery. Due to the periodicity and the cyclic symmetry of<p>the structure, the blade modes occur by families with very close resonance frequencies,<p>and harmonic shape in the circumferential direction; the proposed RL shunt<p>approaches take advantage of these two features.<p>When a family of modes is targeted for damping, the piezoelectric patches are<p>shunted independently on identical RL circuits, and tuned roughly on the average<p>value of the resonance frequencies of the targeted modes. This independent<p>configuration offers a damping solution effective on the whole family of modes, but<p>it requires the use of synthetic inductors, which is a serious drawback for rotating<p>machines.<p>When a specific mode with n nodal diameters has been identified as critical and<p>is targeted for damping, one can take advantage of its harmonic shape to organize<p>the piezoelectric patches in two parallel loops. This parallel approach reduces considerably<p>the demand on the inductors of the tuned inductive shunt, as compared<p>to independent loops, and offers a practical solution for a fully passive integration<p>of the inductive shunt in a rotating structure.<p>Various methods are investigated numerically and experimentally on a cantilever<p>beam, a bladed rail, a circular plate, and a bladed drum. The influence of blade<p>mistuning is also investigated. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

Submitted by Nadir Basilio (nadirsb@uninove.br) on 2016-06-01T19:06:09Z No. of bitstreams: 1 Carlos Roberto Franzini Filho.pdf: 953434 bytes, checksum: ad55f7d0771d38a54591c6a4aa6da6b2 (MD5) / Made available in DSpace on 2016-06-01T19:06:09Z (GMT). No. of bitstreams: 1 Carlos Roberto Franzini Filho.pdf: 953434 bytes, checksum: ad55f7d0771d38a54591c6a4aa6da6b2 (MD5) Previous issue date: 2015-03-31 / Currently in Brazil and the worldwide, the "end of life vehicles" (ELV) has been considered as a serious problem to environment. It is considered as an ELV the vehicle that concluded his life cycle or vehicle damaged due accidents. Unlike countries where recovery ELV happens because of specific ELV laws, recovery of ELV parts in Brazil has been guided by profit in reason of the possibility to reselling parts with highest market value after the first phase of use. The aim of this study was to identify what are necessary steps to propose a framework to implementation of reverse logistics process to ELVs in Brazil. The methodology used to achieve the aim was a theoretical / conceptual research from bibliometric review of the literature available in five databases (CAPES, EBSCO, PROQUEST, SCIENCE DIRECT, GOOGLE ACADÊMICO) and documentary research in Unions and class Associations. A content analysis from collected data allowed the identification of the main aspects and activities related to reverse logistics to ELV. Considering the current scenario for ELVs in Brazil and the data obtained from the literature during the content analysis, a framework was proposed with the required steps to implement the reverse logistics to ELV in Brazil. In reason of a theoretical study, there are limitations because of the different realities from researched countries: changing regulatory, social structures, political systems, laws, economic systems and also the level of development from the country. / Atualmente no Brasil e no mundo, os “Veículos em Final de Vida” (VFV) têm sido um grande problema para o meio ambiente. É considerado como VFV o veículo que chegou ao final de seu ciclo de vida útil ou o veículo que teve o seu ciclo de vida útil interrompido prematuramente em razão de acidentes. Diferentemente dos países onde a recuperação de VFV acontece em razão de obrigações legais especificas, no Brasil a recuperação das peças constituintes dos VFV têm sido impulsionada pela possibilidade de obtenção de lucro com a revenda destas peças para reuso, remanufatura ou reciclagem. Neste contexto, o presente trabalho tem como objetivo propor um framework com as etapas necessárias para a implementação do processo de logística reversa para VFV no Brasil. A metodologia utilizada para atingir o objetivo proposto foi uma pesquisa teórico/conceitual a partir de revisão bibliométrica da literatura em cinco bases de dados disponíveis (CAPES, EBSCO, PROQUEST, SCIENCE DIRECT, GOOGLE ACADÊMICO) e uma pesquisa documental em órgãos de classe do setor automotivo. Uma análise de conteúdo feita nos dados coletados permitiu a identificação dos principais aspectos e atividades relacionadas ao processo de logística reversa para VFV. Foram apresentados os principais estimuladores e barreiras identificadas na literatura para a implementação da logística reversa para VFV. Considerando o atual cenário para VFV no Brasil e as os dados apurados na literatura durante a análise de conteúdo, foi proposto um framework com as etapas necessárias para a implementação do processo de logística reversa para VFV no Brasil. Por tratar-se de um estudo teórico, as limitações deste estudo se devem ao fato das diferentes realidades entre os países pesquisados: diferentes regulamentações governamentais, estruturas sociais, sistemas políticos, sistemas econômicos e também o nível de desenvolvimento do país.

Preserving the performance of cloud services according to service level agreements (SLAs) is one of the most important challenges in cloud infrastructure. Since the workload is always changing incrementally or decremental, managing the cloud resources efficiently is considered an important challenge to satisfy non-functional requirements like high availability and cost. Although many common approaches like predictive autoscaling could solve this problem, it is still not so efficient because of its constraints like requiring a workload pattern as training data. Reinforcement machine learning (RL) can be considered a significant solution for this problem. Even though reinforcement learning needs some time to be stable and needs many trials to decide the value of factors like discount rate, this approach can adapt with the dynamic workload. In this  thesis, through a controlled experiment research method, we show how a model-free reinforcement algorithm like Q-learning can adapt to the dynamic workload by applying horizontal autoscaling to keep the performance of cloud services at the required level. Furthermore, the Amazon web services (AWS) platform is used to demonstrate the efficiency of the Q-learning algorithm in dealing with dynamic workload and achieving high availability.

<p>The capacity of deep reinforcement learning policy networks has been found to affect the performance of trained agents. It has been observed that policy networks with more parameters have better training performance and generalization ability than smaller networks. In this work, we find cases where this does not hold true. We observe unimodal variance in the zero-shot test return of varying width policies, which accompanies a drop in both train and test return. Empirically, we demonstrate mostly monotonically increasing performance or mostly optimal performance as the width of deep policy networks increase, except near the variance mode. Finally, we find a scenario where larger networks have increasing performance up to a point, then decreasing performance. We hypothesize that these observations align with the theory of double descent in supervised learning, although with specific differences.</p>

No description available.

Les algorithmes actuels d'apprentissage profond par renforcement (RL) sont encore très spécifiques à leur tâche et n'ont pas la capacité de généraliser à de nouveaux environnements. L'apprentissage tout au long de la vie (LLL), cependant, vise à résoudre plusieurs tâches de manière séquentielle en transférant et en utilisant efficacement les connaissances entre les tâches. Malgré un regain d'intérêt pour le RL tout au long de la vie ces dernières années, l'absence d'un banc de test réaliste rend difficile une évaluation robuste des algorithmes d'apprentissage tout au long de la vie. Le RL multi-agents (MARL), d'autre part, peut être considérée comme un scénario naturel pour le RL tout au long de la vie en raison de sa non-stationnarité inhérente, puisque les politiques des agents changent avec le temps. Dans cette thèse, nous présentons un banc de test multi-agents d'apprentissage tout au long de la vie qui prend en charge un paramétrage à la fois zéro et quelques-coups. Notre configuration est basée sur Hanabi - un jeu multi-agents partiellement observable et entièrement coopératif qui s'est avéré difficile pour la coordination zéro coup. Son vaste espace stratégique en fait un environnement souhaitable pour les tâches RL tout au long de la vie. Nous évaluons plusieurs méthodes MARL récentes et comparons des algorithmes d'apprentissage tout au long de la vie de pointe dans des régimes de mémoire et de calcul limités pour faire la lumière sur leurs forces et leurs faiblesses. Ce paradigme d'apprentissage continu nous fournit également une manière pragmatique d'aller au-delà de la formation centralisée qui est le protocole de formation le plus couramment utilisé dans MARL. Nous montrons empiriquement que les agents entraînés dans notre environnement sont capables de bien se coordonner avec des agents inconnus, sans aucune hypothèse supplémentaire faite par des travaux précédents. Mots-clés: le RL multi-agents, l'apprentissage tout au long de la vie. / Current deep reinforcement learning (RL) algorithms are still highly task-specific and lack the ability to generalize to new environments. Lifelong learning (LLL), however, aims at solving multiple tasks sequentially by efficiently transferring and using knowledge between tasks. Despite a surge of interest in lifelong RL in recent years, the lack of a realistic testbed makes robust evaluation of lifelong learning algorithms difficult. Multi-agent RL (MARL), on the other hand, can be seen as a natural scenario for lifelong RL due to its inherent non-stationarity, since the agents' policies change over time. In this thesis, we introduce a multi-agent lifelong learning testbed that supports both zero-shot and few-shot settings. Our setup is based on Hanabi --- a partially-observable, fully cooperative multi-agent game that has been shown to be challenging for zero-shot coordination. Its large strategy space makes it a desirable environment for lifelong RL tasks. We evaluate several recent MARL methods, and benchmark state-of-the-art lifelong learning algorithms in limited memory and computation regimes to shed light on their strengths and weaknesses. This continual learning paradigm also provides us with a pragmatic way of going beyond centralized training which is the most commonly used training protocol in MARL. We empirically show that the agents trained in our setup are able to coordinate well with unknown agents, without any additional assumptions made by previous works. Key words: multi-agent reinforcement learning, lifelong learning.

No description available.

Monitoring waterbirds have several benefits, including analyzing the number of endangered species, giving a reliable indication of public health, etc. Monitoring waterbirds in their habitat is a challenging task since the location is distant, and the collection of monitoring data requires large bandwidth. A promising technology to tackle these challenges is thought to be Wireless Multimedia Sensor Networks (WMSN). These networks are composed of small energy-constrained IoT devices that communicate together to collect data or monitor a given location. Performances in such networks are impacted by not only upper-layer protocols (transmission, routing, application layer) but also Medium Access Control (MAC) Layer. Therefore, improvement in this layer can increase the performance considerably. Traditional contention-based MAC modes like CSMA have large energy expenditure even though they have a good network performance profile. Energy-constrained devices cannot have a long lifespan with this type of MAC layer technology. Therefore, the IEEE 802.15.4e amendment proposed TSCH MAC mode which takes advantage of time-slotted access and channel hopping techniques. IETF integrated TSCH protocol into IPv6-based wireless sensor networks and standardized it as 6TiSCH which is a unique protocol stack for Low-Power and Lossy Networks (LLN). WMSN applications (e.g. Waterbirds Monitoring Application) generates heterogeneous traffic. Heterogeneous traffic can be defined as a mixture of different traffic types (light: temperature, humidity, etc. and heavy: audio, picture, video, etc.). TSCH-based WMSNs are considered a fit for this kind of traffic since they provide better performance and low power usage.  Yet, the 6TiSCH Working Group left open the scheduling of TSCH communication for industries to make TSCH more easily adaptable to any kind of application. Until now, there have been a huge number of scheduling algorithms from industries and academia. Each scheduling algorithm has a different objective that maximizes the network performance of a specific application. This thesis work studies the most recent state-of-the-art scheduling algorithms (protocols) and compares them in a unique simulation environment with heterogeneous traffic to find out which protocol performs well while maintaining low energy consumption. Particularly, this work studies a new approach in TSCH scheduling which is Reinforcement Learning based scheduling. We implemented one of the state-of-the-art RL-based schedulers in Contiki-NG and included it in our comparison of TSCH schedulers. The experiment results showed that the RL-based scheduler implemented in this work demonstrated better performance in PDR and latency compared to other scheduling protocols. However, it presented high energy usage. On the other hand, Orchestra performed well while keeping the energy expenditure of nodes at a low level.