892 resultados para ANTITUMOR AGENTS


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Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertation presented to obtain the Ph.D degree in Biochemistry

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The purpose of this work is to develop a practicable approach for Telecom firms to manage the credit risk exposition to their commercial agents’ network. Particularly it will try to approach the problem of credit concession to clients’ from a corporation perspective and explore the particular scenario of agents that are part of the commercial chain of the corporation and therefore are not end-users. The agents’ network that served as a model for the presented study is composed by companies that, at the same time, are both clients and suppliers of the Telecommunication Company. In that sense the credit exposition analysis must took into consideration all financial fluxes, both inbound and outbound. The current strain on the Financial Sector in Portugal, and other peripheral European economies, combined with the high leverage situation of most companies, generates an environment prone to credit default risk. Due to these circumstances managing credit risk exposure is becoming increasingly a critical function for every company Financial Department. The approach designed in the current study combined two traditional risk monitoring tools: credit risk scoring and credit limitation policies. The objective was to design a new credit monitoring framework that is more flexible, uses both external and internal relationship history to assess risk and takes into consideration commercial objectives inside the agents’ network. Although not explored at length, the blueprint of a Credit Governance model was created for implementing the new credit monitoring framework inside the telecom firm. The Telecom Company that served as a model for the present work decided to implement the new Credit Monitoring framework after this was presented to its Executive Commission.

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The potential and applicability of UHPSFC-MS/MS for anti-doping screening in urine samples were tested for the first time. For this purpose, a group of 110 doping agents with diverse physicochemical properties was analyzed using two separation techniques, namely UHPLC-MS/MS and UHPSFC-MS/MS in both ESI+ and ESI- modes. The two approaches were compared in terms of selectivity, sensitivity, linearity and matrix effects. As expected, very diverse retentions and selectivities were obtained in UHPLC and UHPSFC, proving a good complementarity of these analytical strategies. In both conditions, acceptable peak shapes and MS detection capabilities were obtained within 7min analysis time, enabling the application of these two methods for screening purposes. Method sensitivity was found comparable for 46% of tested compounds, while higher sensitivity was observed for 21% of tested compounds in UHPLC-MS/MS and for 32% in UHPSFC-MS/MS. The latter demonstrated a lower susceptibility to matrix effects, which were mostly observed as signal suppression. In the case of UHPLC-MS/MS, more serious matrix effects were observed, leading typically to signal enhancement and the matrix effect was also concentration dependent, i.e., more significant matrix effects occurred at the lowest concentrations.

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Taking advantage of homeostatic mechanisms to boost tumor-specific cellular immunity is raising increasing interest in the development of therapeutic strategies in the treatment of melanoma. Here, we have explored the potential of combining homeostatic proliferation, after transient immunosuppression, and antigenic stimulation of Melan-A/Mart-1 specific CD8 T-cells. In an effort to develop protocols that could be readily applicable to the clinic, we have designed a phase I clinical trial, involving lymphodepleting chemotherapy with Busulfan and Fludarabine, reinfusion of Melan-A specific CD8 T-cell containing peripheral blood mononuclear cells (exempt of growth factors), and Melan-A peptide vaccination. Six patients with advanced melanoma were enrolled in this outpatient regimen that demonstrated good feasibility combined with low toxicity. Consistent depletion of lymphocytes with persistent increased CD4/CD8 ratios was induced, although the proportion of circulating CD4 regulatory T-cells remained mostly unchanged. The study of the immune reconstitution period showed a steady recovery of whole T-cell numbers overtime. However, expansion of Melan-A specific CD8 T-cells, as measured in peripheral blood, was mostly inconsistent, accompanied with marginal phenotypic changes, despite vaccination with Melan-A/Mart-1 peptide. On the clinical level, 1 patient presented a partial but objective antitumor response following the beginning of the protocol, even though a direct effect of Busulfan/Fludarabine cannot be completely ruled out. Overall, these data provide further ground for the development of immunotherapeutic approaches to be both effective against melanoma and applicable in clinic.

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BACKGROUND: Glioblastoma multiforme (GBM), a highly invasive and vascular cancer, responds poorly to conventional cytotoxic therapy. Integrins, widely expressed in GBM and tumor vasculature, mediate cell survival, migration and angiogenesis. Cilengitide is a potent alphavbeta3 and alphavbeta5 integrin inhibitor. OBJECTIVE: To summarize the preclinical and clinical experience with cilengitide for GBM. METHODS: Preclinical studies and clinical trials evaluating cilengitide for GBM were reviewed. RESULTS/CONCLUSIONS: Cilengitide is active and synergizes with external beam radiotherapy in preclinical GBM models. In clinical trials for recurrent GBM, single-agent cilengitide has antitumor benefits and minimal toxicity. Among newly diagnosed GBM patients, single-arm studies incorporating cilengitide into standard external beam radiotherapy/temozolomide have shown encouraging activity with no increased toxicity and have led to a planned randomized Phase III trial.