God’s Freedom In Creating an Image of Human Knowledge and Human Freedom In Receiving It in Descartes’ Philosophy.

The topic of freedom in Descartes’ philosophy is usually being connected with human freedom. It is understood in the traditional perspective of distinguishing right from wrong and truth from false. This aspect is, in my opinion, sufficiently explained. The same applies to Descartes’ ethics, connections of which with Antiquity were often mentioned. In the paper I bring up quite different issue. It rests on the question what it means that God creates the truth and what consequences it has for human validity (and necessity) of recognizing and receiving it, what is its status and, finally, how it reconfigures the relation between God and the man

Genetics

With the financial support of Internal Security Fund Police Programme European Commission Directorate General Home Affairs. This project has been founded with support from the European Commission. This publication reflects the views only of the authors, and European Commission cannot be held responsible for any use which may be made of the information contained therein

Threshold Accepting Heuristic for Fair Flow Optimization in Wireless Mesh Networks

Developing effective, fairness-preserving optimization algorithms is of considerable importance in systems which serve many users. In this paper we show the results of the threshold accepting procedure applied to extremely difficult problem of fair resource allocation in wireless mesh networks (WMN). The fairness is modeled by allowing preferences with regard to distribution of Internet traffic between network participants. As aggregation operator we utilize weighted ordered weighted averaging (WOWA). In the underlaying optimization problem, the physical medium properties cause strong interference among simultaneously operating node devices, leading to nonlinearities in the mixed-integer pricing subproblem. That is where the threshold accepting procedure is applied. We show that, the threshold accepting heuristic performs much better than the widely utilized simulated annealing algorithm

Decision Support under Risk by Optimization of Scenario Importance Weighted OWA Aggregations, Journal of Telecommunications and Information Technology, 2009, nr 3

The problem of evaluation outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuzzy operator defined as the so-called weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. TheWOWA aggregation, similar to the classical ordered weighted averaging (OWA), uses the preferential weights assigned to the ordered values (i.e., to the worst value, the second worst and so on) rather than to the specific criteria. This allows one to model various preferences with respect to the risk. Simultaneously, importance weighting of scenarios can be introduced. In this paper we analyze solution procedures for optimization problems with the WOWA objective functions related to decisions under risk. Linear programming formulations are introduced for optimization of the WOWA objective representing risk averse preferences. Their computational efficiency is demonstrated

On equitable approaches to resource allocation problems: the conditional minimax solutions, Journal of Telecommunications and Information Technology, 2002, nr 3

In this paper we introduce and analyze a solution concept of the conditional minimax as a generalization of the minimax solution concept extended to take into account the number of services (the portion of demand) related to the worst performances. Namely, for a specified portion of demand we take into account the corresponding portion of the maximum results and we consider their average as the worst conditional mean to be minimized. We show that, similar to the standard minimax approach, the minimization of the worst conditional mean can be defined by a linear objective and a number of auxiliary linear inequalities. We report some results of initial computational experience with the new solution concept

Elevated Level of DNA Damage and Impaired Repair of Oxidative DNA Damage in Patients with Recurrent Depressive Disorder

Background: Depressive disorder (DD), including recurrent DD (rDD), is a severe psychological disease, which affects a large percentage of the world population. Although pathogenesis of the disease is not known, a growing body of evidence shows that inflammation together with oxidative stress may contribute to development of DD. Since reactive oxygen species produced during stress may damage DNA, we wanted to evaluate the extent of DNA damage and efficiency of DNA repair in patients with depression. Material and Methods: We measured and compared the extent of endogenous DNA damage – single- and double-strand breaks, alkali-labile sites, and oxidative damage of the pyrimidines and purines – in peripheral blood mononuclear cells isolated from rDD patients (n=40) and healthy controls (n=46) using comet assay. We also measured DNA damage evoked by hydrogen peroxide and monitored changes in DNA damage during repair incubation. Results: We found an increased number DNA breaks, alkali-labile sites, and oxidative modification of DNA bases in the patients compared to the controls. Exposure to hydrogen peroxide evoked the same increased damage in both groups. Examination of the repair kinetics of both groups revealed that the lesions were more efficiently repaired in the controls than in the patients. Conclusions: For the first time we showed that patients with depression, compared with non-depresses individuals, had more DNA breaks, alkali-labile sites, and oxidative DNA damage, and that those lesions may be accumulated by impairments of the DNA repair systems. More studies must be conducted to elucidate the role of DNA damage and repair in depression

Fair resource allocation schemes and network dimensioning problems, Journal of Telecommunications and Information Technology, 2003, nr 3

Resource allocation problems are concerned with the allocation of limited resources among competing activities so as to achieve the best overall performances of the system but providing fair treatment of all the competitors. Telecommunication networks are facing the increasing demand for Internet services. Therefore, a problem of network dimensioning with elastic traffic arises which requires to allocate bandwidth to maximize service flows with fair treatment of all the services. In such applications, the so-called max-min fairness (MMF) solution concept is widely used to formulate the resource allocation scheme. This guarantees the fairness but may lead to significant losses in the overall throughput of the network. In this paper we show how multiple criteria optimization concepts can be used to generate various fair resource allocation schemes. The solution concepts are tested on the network dimensioning problem and their abilities to model various preferences are demonstrated