An Architecture for Resource Bounded Agents

We study agents situated in partially observable environments, who do not have sufficient resources to create conformant (complete) plans. Instead, they create plans which are conditional and partial, execute or simulate them, and learn from experience to evaluate their quality. Our agents employ an incomplete symbolic deduction system based on Active Logic and Situation Calculus for reasoning about actions and their consequences. An Inductive Logic Programming algorithm generalises observations and deduced knowledge so that the agents can choose the best plan for execution. We describe an architecture which allows ideas and solutions from several subfields of Artificial Intelligence to be joined together in a controlled and manageable way. In our opinion, no situated agent can achieve true rationality without using at least logical reasoning and learning. In practice, it is clear that pure logic is not able to cope with all the requirements put on reasoning, thus more domain- specific solutions, like planners, are also necessary. Finally, any realistic agent needs a reactive module to meet demands of dynamic environments. Our architecture is designed in such a way that those three elements interact in order to complement each other’s weaknesses and reinforce each other’s strengths

The aromatase expression in myomas and myometriums of women in reproduction and perimenopausal age.

Uterine myomas represent one of the most common female pathologies. Uterine smooth muscle myomas or fibromas are benign tumours which respond to hormones and their etiology induces wide interest. The myomas were found to contain aromatase and, in addition, cells of the myomas were found to synthesize estrogen. This study was conducted on patients with the myomas, in either generative age or in the perimenopausal period. Expression of aromatase was detected in patients of various age, with large or small uterine myomas, using an immunohistochemical technique. In addition expression of the enzyme was examined at the periphery of every myoma

Verification of electron beam parameters in an intraoperative linear accelerator using dosimetric and radiobiological response methods

Background: The availability of linear accelerators (linac) for research purposes is often limited and therefore alternative radiation sources are needed to conduct radiobiological research. The National Centre for Radiation Research in Poland recently developed an intraoperative mobile linac that enables electron irradiation at energies ranging from 4 to 12 MeV and dose rates of 5 or 10 Gy/min. The present study was conducted to evaluate the electron beam parameters of this intraoperative linac and to verify the set-up to evaluate out-of-field doses in a water phantom, which were determined through dosimetric and biological response measurements. Materials and methods: The distribution of radiation doses along and across the radiation beam were measured in a water phantom using a semiconductor detector and absolute doses using an ionisation chamber. Two luminal breast cancer cell lines (T-47D and HER2 positive SK-BR-3) were placed in the phantom to study radiation response at doses ranging from 2 to 10 Gy.  Cell response was measured by clonogenic assays. Results and Conclusion: The electron beam properties, including depth doses and profiles, were within expected range for the stated energies. These results confirm the viability of this device and set-up as a source of megavoltage electrons to evaluate the radiobiological response of tumour cells

Antiarrhythmic and antioxidant activity of novel pyrrolidin-2-one derivatives with adrenolytic properties

A series of novel pyrrolidin-2-one derivatives (17 compounds) with adrenolytic properties was evaluated for antiarrhythmic, electrocardiographic and antioxidant activity. Some of them displayed antiarrhythmic activity in barium chloride-induced arrhythmia and in the rat coronary artery ligation-reperfusion model, and slightly decreased the heart rate, prolonged P–Q, Q–T intervals and QRS complex. Among them, compound EP-40 (1-[2-hydroxy-3-[4-[(2-hydroxyphenyl)piperazin-1-yl]propyl]pyrrolidin-2-one showed excellent antiarrhythmic activity. This compound had significantly antioxidant effect, too. The present results suggest that the antiarrhythmic effect of compound EP-40 is related to their adrenolytic and antioxidant properties. A biological activity prediction using the PASS software shows that compound EP-35 and EP-40 can be characterized by antiischemic activity; whereas, compound EP-68, EP-70, EP-71 could be good tachycardia agents

Semi-Natural Superabsorbents Based on Starch-g-poly(acrylic acid): Modification, Synthesis and Application

Biopolymer-based superabsorbent polymers (SAPs) are being synthesized and investigated as a biodegradable alternative for an entirely synthetic SAPs, particularly those based on acrylic acid and its derivatives. This article focuses on the chemical modification of starch (S), and synthesis of new potentially biodegradable polymers using acrylic acid (AA) as side chain monomer and crosslinking mediator together with N,N’-methylenebisacrylamide (MBA). The graft co-polymerization was initiated by ceric ammonium nitrate (CAN) or potassium persulfate (KPS), leading to different reaction mechanisms. For each of the initiators, three different synthetic routes were applied. The structures of new bio-based SAPs were characterized by means of IR spectroscopy. Thermogravimetric measurements were made to test the thermal stability, and morphology of the samples were examined using scanning electron microscopy (SEM). Physico-chemical measurements were performed to characterize properties of new materials such as swelling characteristics. The water absorption capacity of resulting hydrogels was measured in distilled water and 0.9% NaCl solution

Inductive logic programming algorithm for estimating quality of partial plans

We study agents situated in partially observable environments, who do not have the resources to create conformant plans. Instead, they create conditional plans which are partial, and learn from experience to choose the best of them for execution. Our agent employs an incomplete symbolic deduction system based on Active Logic and Situation Calculus for reasoning about actions and their consequences. An Inductive Logic Programming algorithm generalises observations and deduced knowledge in order to choose the best plan for execution. We show results of using PROGOL learning algorithm to distinguish "bad" plans, and we present three modifications which make the algorithm fit this class of problems better. Specifically, we limit the search space by fixing semantics of conditional branches within plans, we guide the search by specifying relative relevance of portions of knowledge base, and we integrate learning algorithm into the agent architecture by allowing it to directly access the agent's knowledge encoded in Active Logic. We report on experiments which show that those extensions lead to significantly better learning results

Relative Relevance of Subsets of Agent’s Knowledge

We study agents situated in partially observable environments, who do not have the resources to create conformant plans. Instead, they create conditional plans which are partial, and learn from experience to choose the best of them for execution. Our agent employs an incomplete symbolic deduction system based on Active Logic and Situation Calculus for reasoning about actions and their consequences. An Inductive Logic Programming algorithm generalises observations and deduced knowledge in order to distinguish “bad ” plans early, before agent’s computational resources are wasted on considering them. In this paper we present experiments which show that in order for learning to be successful, an agent’s knowledge needs to be filtered. We argue that this filtering nicely matches the intuitive notion of “knowledge relevance”. We also present a heuristic scheme, combining several natural rules, which can be used to automatically determine which formulae should be used for learning.