Effects of blocking farm minkś feed access with open water

Selostus: Tarhatun minkin syömään pääsyn estäminen vesialtaalla

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Development of phase retrieval algorithm and techniques for optical spectrum analysis

Coherent anti-Stokes Raman scattering is the powerful method of laser spectroscopy in which significant successes are achieved. However, the non-linear nature of CARS complicates the analysis of the received spectra. The objective of this Thesis is to develop a new phase retrieval algorithm for CARS. It utilizes the maximum entropy method and the new wavelet approach for spectroscopic background correction of a phase function. The method was developed to be easily automated and used on a large number of spectra of different substances.. The algorithm was successfully tested on experimental data.

Stress testing and risk evaluation of new capacity payment algorithm proposed by Market Council

In the Russian Wholesale Market, electricity and capacity are traded separately. Capacity is a special good, the sale of which obliges suppliers to keep their generating equipment ready to produce the quantity of electricity indicated by the System Operator. The purpose of the formation of capacity trading was the maintenance of reliable and uninterrupted delivery of electricity in the wholesale market. The price of capacity reflects constant investments in construction, modernization and maintenance of power plants. So, the capacity sale creates favorable conditions to attract investments in the energy sector because it guarantees the investor that his investments will be returned.

Studies on Neuromuscular Blocking Agents and Their Antagonists During Anaesthesia

Neuromuscular blocking agents (NMBAs) are widely used in clinical anaesthesia and emergency medicine. Main objectives are to facilitate endotracheal intubation and to allow surgery by reducing muscle tone and eliminating sudden movements, which may otherwise lead to trauma and complications. The most commonly used NMBAs are non-depolarizing agents with a medium duration of action, such as rocuronium and cisatracurium. They bind to the acetylcholine receptors in the neuromuscular junction, thus inhibiting the depolarization of the postsynaptic (muscular) membrane, which is a prerequisite for muscle contraction to take place. Previously, it has been assumed that nitrous oxide (N2O), which is commonly used in combination with volatile or intravenous anaesthetics during general anaesthesia, has no effect on NMBAs. Several studies have since claimed that N2O in fact does increase the effect of NMBAs when using bolus administration of the relaxant. The effect of N2O on the infusion requirements of two NMBAs (rocuronium and cisatracurium) with completely different molecular structure and pharmacological properties was assessed. A closed-loop feedback controlled infusion of NMBA with duration of at least 90 minutes at a 90% level of neuromuscular block was used. All patients received total intravenous anaesthesia (TIVA) with propofol and remifentanil. In both studies the study group (n=35) received N2O/Oxygen and the control group (n=35) Air/Oxygen. There were no significant differences in the mean steady state infusion requirements of NMBA (rocuronium in Study I; cisatracurium in Study II) between the groups in either study. In Study III the duration of the unsafe period of recovery after reversal of rocuronium-induced neuromuscular block by using neostigmine or sugammadex as a reversal agent was analyzed. The unsafe period of recovery was defined as the time elapsed from the moment of no clinical (visual) fade in the train-of-four (TOF) sequence until an objectively measured TOF-ratio of 0.90 was achieved. The duration of these periods were 10.3 ± 5.5 and 0.3 ± 0.3 min after neostigmine and sugammadex, respectively (P < 0.001). Study IV investigated the possible effect of reversal of a rocuronium NMB by sugammadex on depth of anaesthesia as indicated by the bispectral index and entropy levels in thirty patients. Sugammadex did not affect the level of anaesthesia as determined by EEG-derived indices of anaesthetic depth such as the bispectral index and entropy.

Solving Leontief Input-Output Model with Trapezoidal Fuzzy Numbers and Gauss-Seidel Algorithm

In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.

GAMS MINLP Solver comparisons and some improvements to the AlphaECP algorithm

I doktorsavhandlingen undersöks förmågan att lösa hos ett antal lösare för optimeringsproblem och ett antal svårigheter med att göra en rättvis lösarjämförelse avslöjas. Dessutom framläggs några förbättringar som utförts på en av lösarna som heter GAMS/AlphaECP. Optimering innebär, i det här sammanhanget, att finna den bästa möjliga lösningen på ett problem. Den undersökta klassen av problem kan karaktäriseras som svårlöst och förekommer inom ett flertal industriområden. Målet har varit att undersöka om det finns en lösare som är universellt snabbare och hittar lösningar med högre kvalitet än någon av de andra lösarna. Det kommersiella optimeringssystemet GAMS (General Algebraic Modeling System) och omfattande problembibliotek har använts för att jämföra lösare. Förbättringarna som presenterats har utförts på GAMS/AlphaECP lösaren som baserar sig på skärplansmetoden Extended Cutting Plane (ECP). ECP-metoden har utvecklats främst av professor Tapio Westerlund på Anläggnings- och systemteknik vid Åbo Akademi.

Power and Performance Management Strategies on NoC-Based Multicore Platforms, Using DVFS, Adaptive Algorithm and Task Parallelism

This work presents synopsis of efficient strategies used in power managements for achieving the most economical power and energy consumption in multicore systems, FPGA and NoC Platforms. In this work, a practical approach was taken, in an effort to validate the significance of the proposed Adaptive Power Management Algorithm (APMA), proposed for system developed, for this thesis project. This system comprise arithmetic and logic unit, up and down counters, adder, state machine and multiplexer. The essence of carrying this project firstly, is to develop a system that will be used for this power management project. Secondly, to perform area and power synopsis of the system on these various scalable technology platforms, UMC 90nm nanotechnology 1.2v, UMC 90nm nanotechnology 1.32v and UMC 0.18 μmNanotechnology 1.80v, in order to examine the difference in area and power consumption of the system on the platforms. Thirdly, to explore various strategies that can be used to reducing system’s power consumption and to propose an adaptive power management algorithm that can be used to reduce the power consumption of the system. The strategies introduced in this work comprise Dynamic Voltage Frequency Scaling (DVFS) and task parallelism. After the system development, it was run on FPGA board, basically NoC Platforms and on these various technology platforms UMC 90nm nanotechnology1.2v, UMC 90nm nanotechnology 1.32v and UMC180 nm nanotechnology 1.80v, the system synthesis was successfully accomplished, the simulated result analysis shows that the system meets all functional requirements, the power consumption and the area utilization were recorded and analyzed in chapter 7 of this work. This work extensively reviewed various strategies for managing power consumption which were quantitative research works by many researchers and companies, it's a mixture of study analysis and experimented lab works, it condensed and presents the whole basic concepts of power management strategy from quality technical papers.

Probing MST1 Kinase Sequence and Structure for Rational Drug Discovery (Targeting diabetes by blocking protein-protein interactions)

Apoptotic beta cell death is an underlying cause majorly for type I and to a lesser extent for type II diabetes. Recently, MST1 kinase was identified as a key apoptotic agent in diabetic condition. In this study, I have examined MST1 and closely related kinases namely, MST2, MST3 and MST4, aiming to tackle diabetes by exploring ways to selectively block MST1 kinase activity. The first investigation was directed towards evaluating possibilities of selectively blocking the ATP binding site of MST1 kinase that is essential for the activity of the enzymes. Structure and sequence analyses of this site however revealed a near absolute conservation between the MSTs and very few changes with other kinases. The observed residue variations also displayed similar physicochemical properties making it hard for selective inhibition of the enzyme. Second, possibilities for allosteric inhibition of the enzyme were evaluated. Analysis of the recognized allosteric site also posed the same problem as the MSTs shared almost all of the same residues. The third analysis was made on the SARAH domain, which is required for the dimerization and activation of MST1 and MST2 kinases. MST3 and MST4 lack this domain, hence selectivity against these two kinases can be achieved. Other proteins with SARAH domains such as the RASSF proteins were also examined. Their interaction with the MST1 SARAH domain were evaluated to mimic their binding pattern and design a peptide inhibitor that interferes with MST1 SARAH dimerization. In molecular simulations the RASSF5 SARAH domain was shown to strongly interact with the MST1 SARAH domain and possibly preventing MST1 SARAH dimerization. Based on this, the peptidic inhibitor was suggested to be based on the sequence of RASSF5 SARAH domain. Since the MST2 kinase also interacts with RASSF5 SARAH domain, absolute selectivity might not be achieved.