Analysis of outliers in electricity spot prices with exampleof New England and New Zealand markets

Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

Genesis and Emplacement of Carbonatites and Lamprophyres in the Svecofennian Domain

A small carbonatite dyke swarm has been identified at Naantali, southwest Finland. Several swarms of shoshonitic lamprophyres are also known along the Archean-Proterozoic boundary in eastern Finland and northwest Russia. These intrusions, along with the carbonatite intrusion at Halpanen, eastern Finland, represent a stage of widespread low-volume mantle-sourced alkaline magmatism in the Svecofennian Domain. Using trace element and isotope geochemistry coupled with precise geochronology from these rocks, a model is presented for the Proterozoic metasomatic evolution of the Fennoscandian subcontinental lithospheric mantle. At ~2.2-2.06 Ga, increased biological production in shallow seas linked to continental rifting, resulted in increased burial rates of organic carbon. Subduction between ~1.93-1.88 Ga returned organic carbon-enriched sediments of mixed Archean and Proterozoic provenance to the mantle. Dehydration reactions supplied water to the mantle wedge, driving arc volcanism, while mica, amphibole and carbonate were brought deeper into the mantle with the subducting slab. The cold subducted slab was heated conductively from the surrounding warm mantle, while pressures continued to gradually increase as a result of crustal thickening. The sediments began to melt in a two stage process, first producing a hydrous alkaline silicate melt, which infiltrated the mantle wedge and crystallised as metasomatic veins. At higher temperatures, carbonatite melt was produced, which preferentially infiltrated the pre-existing metasomatic vein network. At the onset of post-collisional extension, deep fault structures formed, providing conduits for mantle melts to reach the upper crust. Low-volume partial melting of the enriched mantle at depths of at least 110 km led to the formation of first carbonatitic magma and subsequently lamprophyric magma. Carbonatite was emplaced in the upper crust at Naantali at 1795.7 ± 6.8 Ma; lamprophyres along the Archean-Proterozoic boundary were emplaced between 1790.1 ± 3.3 Ma and 1781 ± 20 Ma.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Electrical status epilepticus during sleep. Continuous spikes and waves during sleep

ABSTRACT Maria Peltola Electrical status epilepticus during sleep – Continuous spikes and waves during sleep Department of Clinical Neurophysiology, University of Turku Department of Clinical Neurophysiology and Department of Pediatric Neurology, Children’s Hospital, Helsinki University Central Hospital Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Finland, 2014 Background: Electrical status epilepticus during sleep (ESES) is an EEG phenomenon of frequent spikes and waves occurring in slow sleep. ESES relates to cognitive deterioration in heterogeneous childhood epilepsies. Validated methods to quantitate ESES are missing. The clinical syndrome, called epileptic encephalopathy with continuous spikes and waves during sleep (CSWS) is pharmacoresistant in half of the patients. Limited data exists on surgical treatment of CSWS. Aims and methods: The effects of surgical treatment were studied by investigating electroclinical outcomes in 13 operated patients (nine callosotomies, four resections) with pharmacoresistant CSWS and cognitive decline. Secondly, an objective paradigm was searched for assessing ESES by the semiautomatic quantification of spike index (SI) and measuring spike strength from EEG. Results: Postoperatively, cognitive deterioration was stopped in 12 (92%) patients. Three out of four patients became seizure-free after resective surgery. Callosotomy resulted in greater than 90% reduction of atypical absences in six out of eight patients. The preoperative propagation of ESES from one hemisphere to the other was associated with a good response. Semiautomatic quantification of SI was a robust method when the maximal interspike interval of three seconds was used to determine the “continuous” discharge in ten EEGs. SI of the first hour of sleep appeared representative of the whole night SI. Furthermore, the spikes’ root mean square was found to be a stable measure of spike strength when spatially integrated over multiple electrodes during steady NREM sleep. Conclusions: Patients with pharmacoresistant CSWS, based on structural etiology, may benefit from resective surgery or corpus callosotomy regarding both seizure outcome and cognitive prognosis. The semiautomated SI quantification, with proper userdefined settings and the new spatially integrated measure of spike strength, are robust and promising tools for quantifying ESES. Keywords: Electrical status epilepticus during sleep, ESES, continuous spikes and waves during sleep, CSWS, epilepsy surgery, spike index, spike strength, RMS TIIVISTELMÄ Maria Peltola Unenaikainen sähköinen status epilepticus Kliininen neurofysiologia, Turun yliopisto Kliininen neurofysiologia ja lastenneurologia, Lasten ja nuorten sairaala, Helsingin yliopistollinen keskussairaala Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Suomi, 2014 Tausta: Sähköinen status epilepticus unessa (ESES) on aivosähkökäyrä (EEG)-ilmiö, jossa hidasaaltounen aikana esiintyy tiheä piikkihidasaaltopurkaus. ESES:n kvantifioimiseen ei ole olemassa validoituja menetelmiä. ESES on liitetty kognitiivisen tason laskuun ja tällöin puhutaan CSWS (continuous spikes and waves during sleep) - oireyhtymästä. CSWS ei vastaa lääkehoitoon puolella potilaista ja sen epilepsiakirurgisesta hoidosta on olemassa vain vähän tietoa. Tavoitteet ja menetelmät: Selvitimme retrospektiivisesti epilepsiakirurgian vaikusta elektrokliinisiin löydöksiin 13:lla lääkeresistenttiä CSWS-oireyhtymää sairastavalla lapsella, joilla oli rakenteellinen aivojen poikkeavuus. Toinen tavoite oli löytää objektiivinen puoliautomaattinen tapa mitata purkauksen määrää ja piikkien voimakkuutta EEG:stä. Tulokset: Kognitiivisen tason jatkuva heikentyminen loppui 12 (92 %) potilaalla leikkauksen jälkeen. Kolme neljästä resektiopotilaasta tuli kohtauksettomaksi. Kallosotomian jälkeen kuudella kahdeksasta potilaasta päivittäiset kohtaukset vähenivät yli 90 %:lla. Purkauksen leviäminen leikkausta edeltävästi vain yhdestä hemisfääristä toiseen liittyi hyvään leikkaushoitovasteeseen. Piikki-indeksi, jossa käytetään jatkuvan purkauksen määritelmänä maksimissaan kolmea sekuntia piikkien välillä, osoittautui luotettavaksi menetelmäksi ESES:n kvantifioimiseen. Useammasta elektrodista integroitu piikkien neliöllinen keskiarvo oli piikin voimakkuuden vakaa mitta häiriintymättömässä NREM-unessa. Päätelmät: Lääkehoidolle vastaamatonta CSWS:ää sairastavat potilaat, joilla on rakenteellinen aivopoikkeavuus ja yhdensuuntainen purkauksen leviämismalli, näyttävät kohtausten vähenemisen lisäksi hyötyvän epilepsiakirurgiasta kognitiivisesti. Puoliautomaattinen piikki-indeksin kvantifiointi sopivilla käyttäjäasetuksilla ja uusi spatiaalisesti integroitu piikin voimakkuuden mittari ovat stabiileja ja lupaavia ESES:n kvantitatiivisia mittareita. Avainsanat: Unenaikainen sähköinen status epilepticus, ESES, CSWS, epilepsiakirurgia, piikki-indeksi, piikin voimakkuus, neliöllinen keskiarvo

Potential and Challenges of Analog Reconfigurable Computation in Modern and Future CMOS

In this work, the feasibility of the floating-gate technology in analog computing platforms in a scaled down general-purpose CMOS technology is considered. When the technology is scaled down the performance of analog circuits tends to get worse because the process parameters are optimized for digital transistors and the scaling involves the reduction of supply voltages. Generally, the challenge in analog circuit design is that all salient design metrics such as power, area, bandwidth and accuracy are interrelated. Furthermore, poor flexibility, i.e. lack of reconfigurability, the reuse of IP etc., can be considered the most severe weakness of analog hardware. On this account, digital calibration schemes are often required for improved performance or yield enhancement, whereas high flexibility/reconfigurability can not be easily achieved. Here, it is discussed whether it is possible to work around these obstacles by using floating-gate transistors (FGTs), and analyze problems associated with the practical implementation. FGT technology is attractive because it is electrically programmable and also features a charge-based built-in non-volatile memory. Apart from being ideal for canceling the circuit non-idealities due to process variations, the FGTs can also be used as computational or adaptive elements in analog circuits. The nominal gate oxide thickness in the deep sub-micron (DSM) processes is too thin to support robust charge retention and consequently the FGT becomes leaky. In principle, non-leaky FGTs can be implemented in a scaled down process without any special masks by using “double”-oxide transistors intended for providing devices that operate with higher supply voltages than general purpose devices. However, in practice the technology scaling poses several challenges which are addressed in this thesis. To provide a sufficiently wide-ranging survey, six prototype chips with varying complexity were implemented in four different DSM process nodes and investigated from this perspective. The focus is on non-leaky FGTs, but the presented autozeroing floating-gate amplifier (AFGA) demonstrates that leaky FGTs may also find a use. The simplest test structures contain only a few transistors, whereas the most complex experimental chip is an implementation of a spiking neural network (SNN) which comprises thousands of active and passive devices. More precisely, it is a fully connected (256 FGT synapses) two-layer spiking neural network (SNN), where the adaptive properties of FGT are taken advantage of. A compact realization of Spike Timing Dependent Plasticity (STDP) within the SNN is one of the key contributions of this thesis. Finally, the considerations in this thesis extend beyond CMOS to emerging nanodevices. To this end, one promising emerging nanoscale circuit element - memristor - is reviewed and its applicability for analog processing is considered. Furthermore, it is discussed how the FGT technology can be used to prototype computation paradigms compatible with these emerging two-terminal nanoscale devices in a mature and widely available CMOS technology.

Comparison of five popular normalization methods using a spike-in proteomics data set

Mass spectrometry (MS)-based proteomics has seen significant technical advances during the past two decades and mass spectrometry has become a central tool in many biosciences. Despite the popularity of MS-based methods, the handling of the systematic non-biological variation in the data remains a common problem. This biasing variation can result from several sources ranging from sample handling to differences caused by the instrumentation. Normalization is the procedure which aims to account for this biasing variation and make samples comparable. Many normalization methods commonly used in proteomics have been adapted from the DNA-microarray world. Studies comparing normalization methods with proteomics data sets using some variability measures exist. However, a more thorough comparison looking at the quantitative and qualitative differences of the performance of the different normalization methods and at their ability in preserving the true differential expression signal of proteins, is lacking. In this thesis, several popular and widely used normalization methods (the Linear regression normalization, Local regression normalization, Variance stabilizing normalization, Quantile-normalization, Median central tendency normalization and also variants of some of the forementioned methods), representing different strategies in normalization are being compared and evaluated with a benchmark spike-in proteomics data set. The normalization methods are evaluated in several ways. The performance of the normalization methods is evaluated qualitatively and quantitatively on a global scale and in pairwise comparisons of sample groups. In addition, it is investigated, whether performing the normalization globally on the whole data or pairwise for the comparison pairs examined, affects the performance of the normalization method in normalizing the data and preserving the true differential expression signal. In this thesis, both major and minor differences in the performance of the different normalization methods were found. Also, the way in which the normalization was performed (global normalization of the whole data or pairwise normalization of the comparison pair) affected the performance of some of the methods in pairwise comparisons. Differences among variants of the same methods were also observed.