Telomere fluorescence measurements in granulocytes and T lymphocyte subsets point to a high turnover of hematopoietic stem cells and memory T cells in early childhood.

To study telomere length dynamics in hematopoietic cells with age, we analyzed the average length of telomere repeat sequences in diverse populations of nucleated blood cells. More than 500 individuals ranging in age from 0 to 90 yr, including 36 pairs of monozygous and dizygotic twins, were analyzed using quantitative fluorescence in situ hybridization and flow cytometry. Granulocytes and naive T cells showed a parallel biphasic decline in telomere length with age that most likely reflected accumulated cell divisions in the common precursors of both cell types: hematopoietic stem cells. Telomere loss was very rapid in the first year, and continued for more than eight decades at a 30-fold lower rate. Memory T cells also showed an initial rapid decline in telomere length with age. However, in contrast to naive T cells, this decline continued for several years, and in older individuals lymphocytes typically had shorter telomeres than did granulocytes. Our findings point to a dramatic decline in stem cell turnover in early childhood and support the notion that cell divisions in hematopoietic stem cells and T cells result in loss of telomeric DNA.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Patient-ventilator asynchrony during noninvasive pressure support ventilation and neurally adjusted ventilatory assist in infants and children.

OBJECTIVES: To document the prevalence of asynchrony events during noninvasive ventilation in pressure support in infants and in children and to compare the results with neurally adjusted ventilatory assist. DESIGN: Prospective randomized cross-over study in children undergoing noninvasive ventilation. SETTING: The study was performed in a PICU. PATIENTS: From 4 weeks to 5 years. INTERVENTIONS: Two consecutive ventilation periods (pressure support and neurally adjusted ventilatory assist) were applied in random order. During pressure support (PS), three levels of expiratory trigger (ETS) setting were compared: initial ETS (PSinit), and ETS value decreased and increased by 15%. Of the three sessions, the period allowing for the lowest number of asynchrony events was defined as PSbest. Neurally adjusted ventilator assist level was adjusted to match the maximum airway pressure during PSinit. Positive end-expiratory pressure was the same during pressure support and neurally adjusted ventilator assist. Asynchrony events, trigger delay, and cycling-off delay were quantified for each period. RESULTS: Six infants and children were studied. Trigger delay was lower with neurally adjusted ventilator assist versus PSinit and PSbest (61 ms [56-79] vs 149 ms [134-180] and 146 ms [101-162]; p = 0.001 and 0.02, respectively). Inspiratory time in excess showed a trend to be shorter during pressure support versus neurally adjusted ventilator assist. Main asynchrony events during PSinit were autotriggering (4.8/min [1.7-12]), ineffective efforts (9.9/min [1.7-18]), and premature cycling (6.3/min [3.2-18.7]). Premature cycling (3.4/min [1.1-7.7]) was less frequent during PSbest versus PSinit (p = 0.059). The asynchrony index was significantly lower during PSbest versus PSinit (40% [28-65] vs 65.5% [42-76], p < 0.001). With neurally adjusted ventilator assist, all types of asynchronies except double triggering were reduced. The asynchrony index was lower with neurally adjusted ventilator assist (2.3% [0.7-5] vs PSinit and PSbest, p < 0.05 for both comparisons). CONCLUSION: Asynchrony events are frequent during noninvasive ventilation with pressure support in infants and in children despite adjusting the cycling-off criterion. Compared with pressure support, neurally adjusted ventilator assist allows improving patient-ventilator synchrony by reducing trigger delay and the number of asynchrony events. Further studies should determine the clinical impact of these findings.

Visual measurement of laser-arc hybrid welding

Tässä työssä raportoidaan hybridihitsauksesta otettujen suurnopeuskuvasarjojen automaattisen analyysijärjestelmän kehittäminen.Järjestelmän tarkoitus oli tuottaa tietoa, joka avustaisi analysoijaa arvioimaan kuvatun hitsausprosessin laatua. Tutkimus keskittyi valokaaren taajuuden säännöllisyyden ja lisäainepisaroiden lentosuuntien mittaamiseen. Valokaaria havaittiin kuvasarjoista sumean c-means-klusterointimenetelmän avullaja perättäisten valokaarien välistä aikaväliä käytettiin valokaaren taajuuden säännöllisyyden mittarina. Pisaroita paikannettiin menetelmällä, jossa yhdistyi pääkomponenttianalyysi ja tukivektoriluokitin. Kalman-suodinta käytettiin tuottamaan arvioita pisaroiden lentosuunnista ja nopeuksista. Lentosuunnanmääritysmenetelmä luokitteli pisarat niiden arvioitujen lentosuuntien perusteella. Järjestelmän kehittämiseen käytettävissä olleet kuvasarjat poikkesivat merkittävästi toisistaan kuvanlaadun ja pisaroiden ulkomuodon osalta, johtuen eroista kuvaus- ja hitsausprosesseissa. Analyysijärjestelmä kehitettiin toimimaan pienellä osajoukolla kuvasarjoja, joissa oli tietynlainen kuvaus- ja hitsausprosessi ja joiden kuvanlaatu ja pisaroiden ulkomuoto olivat samankaltaisia, mutta järjestelmää testattiin myös osajoukon ulkopuolisilla kuvasarjoilla. Testitulokset osoittivat, että lentosuunnanmääritystarkkuus oli kohtuullisen suuri osajoukonsisällä ja pieni muissa kuvasarjoissa. Valokaaren taajuuden säännöllisyyden määritys oli tarkka useammassa kuvasarjassa.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Technology selection and group decision support systems: Case studies on supporting strategic technology selection processes

The objective of the dissertation is to increase understanding and knowledge in the field where group decision support system (GDSS) and technology selection research overlap in the strategic sense. The purpose is to develop pragmatic, unique and competent management practices and processes for strategic technology assessment and selection from the whole company's point of view. The combination of the GDSS and technology selection is approached from the points of view of the core competence concept, the lead user -method, and different technology types. In this research the aim is to find out how the GDSS contributes to the technology selection process, what aspects should be considered when selecting technologies to be developed or acquired, and what advantages and restrictions the GDSS has in the selection processes. These research objectives are discussed on the basis of experiences and findings in real life selection meetings. The research has been mainly carried outwith constructive, case study research methods. The study contributes novel ideas to the present knowledge and prior literature on the GDSS and technology selection arena. Academic and pragmatic research has been conducted in four areas: 1) the potential benefits of the group support system with the lead user -method,where the need assessment process is positioned as information gathering for the selection of wireless technology development projects; 2) integrated technology selection and core competencies management processes both in theory and in practice; 3) potential benefits of the group decision support system in the technology selection processes of different technology types; and 4) linkages between technology selection and R&D project selection in innovative product development networks. New type of knowledge and understanding has been created on the practical utilization of the GDSS in technology selection decisions. The study demonstrates that technology selection requires close cooperation between differentdepartments, functions, and strategic business units in order to gather the best knowledge for the decision making. The GDSS is proved to be an effective way to promote communication and co-operation between the selectors. The constructs developed in this study have been tested in many industry fields, for example in information and communication, forest, telecommunication, metal, software, and miscellaneous industries, as well as in non-profit organizations. The pragmatic results in these organizations are some of the most relevant proofs that confirm the scientific contribution of the study, according to the principles of the constructive research approach.

Sheeting efficiency improvement through production planning and control development.

Arkitus on kartongin jatkojalostusmuoto, jonka tehokkuus muodostuu monen tekijän vaikutuksesta. Tämän työn tavoitteena oli parantaa arkitustehokkuutta tutkitussa kahden folioleikkurin arkittamossa tuotannonsuunnittelun ja tuotannonohjauksen kehittämisellä. Kartonkitehtaan sisäisessä jalostusketjussa arkitus on viimeinen vaihe, mikä tekee siitä pitkälti riippuvaisen edeltävistä konevaiheista, eli kartonkikoneista ja PE-päällystyskoneista. Pelkkä arkituksen tuotannonsuunnittelun huomiointi ei siis vielä takaa hyvää lopputulosta arkitustehokkuuden kannalta. Folioarkitustoiminta on hyvin asiakassuuntautunutta. Arkkikoot määräytyvät asiakkaiden omien tarpeiden perusteella, jolloin eri arkkikokojen kokonaismäärä kasvaa huomattavan suureksi. Viime vuosien trendinä on ollut tilauseräkokojen pieneneminen. Näiden tekijöiden yhteisvaikutuksena arkituksen tuotantoprosessille on ominaista erilaisten asetusten aiheuttama katkonaisuus. Lisäksi pelkästään yhden millimetrin muutos arkin leveydessä voi usein vaikuttaa arkitustehokkuuteen hyvinkin merkittävästi. Näistä syistä arkituksen tuotannonsuunnittelun apuvälineeksi tarvitaan tarkkuuteen ja joustavuuteen kykenevää tietojärjestelmää. Tehokkaan tuotannonohjauksen tueksi tarvitaan lisäksi erilaisia leikkuri- ja kartonkilaatukohtaisia raportteja. Työn teoriaosassa käsitellään tarkemmin arkitustoiminnan ominaisuuksia ja sen tehokkuuteen vaikuttavia tekijöitä. Lisäksi käsitellään tuotannonsuunnittelun ja tuotannonohjauksen periaatteita ja toimintoja.

Visual Measurement and Modelling of Tool Wear in Rough Turning

Huolimatta korkeasta automaatioasteesta sorvausteollisuudessa, muutama keskeinen ongelma estää sorvauksen täydellisen automatisoinnin. Yksi näistä ongelmista on työkalun kuluminen. Tämä työ keskittyy toteuttamaan automaattisen järjestelmän kulumisen, erityisesti viistekulumisen, mittaukseen konenäön avulla. Kulumisen mittausjärjestelmä poistaa manuaalisen mittauksen tarpeen ja minimoi ajan, joka käytetään työkalun kulumisen mittaukseen. Mittauksen lisäksi tutkitaan kulumisen mallinnusta sekä ennustamista. Automaattinen mittausjärjestelmä sijoitettiin sorvin sisälle ja järjestelmä integroitiin onnistuneesti ulkopuolisten järjestelmien kanssa. Tehdyt kokeet osoittivat, että mittausjärjestelmä kykenee mittaamaan työkalun kulumisen järjestelmän oikeassa ympäristössä. Mittausjärjestelmä pystyy myös kestämään häiriöitä, jotka ovat konenäköjärjestelmille yleisiä. Työkalun kulumista mallinnusta tutkittiin useilla eri menetelmillä. Näihin kuuluivat muiden muassa neuroverkot ja tukivektoriregressio. Kokeet osoittivat, että tutkitut mallit pystyivät ennustamaan työkalun kulumisasteen käytetyn ajan perusteella. Parhaan tuloksen antoivat neuroverkot Bayesiläisellä regularisoinnilla.

Implementing Role Based Access Control into the Enterprise Environment to Support Business and IT Functions

The thesis studies role based access control and its suitability in the enterprise environment. The aim is to research how extensively role based access control can be implemented in the case organization and how it support organization’s business and IT functions. This study points out the enterprise’s needs for access control, factors of access control in the enterprise environment and requirements for implementation and the benefits and challenges it brings along. To find the scope how extensively role based access control can be implemented into the case organization, firstly is examined the actual state of access control. Secondly is defined a rudimentary desired state (how things should be) and thirdly completed it by using the results of the implementation of role based access control application. The study results the role model for case organization unit, and the building blocks and the framework for the organization wide implementation. Ultimate value for organization is delivered by facilitating the normal operations of the organization whilst protecting its information assets.

Security Authentication using Phase-Encoded Nanoparticle Structures and Polarized Light

Phase encoded nano structures such as Quick Response (QR) codes made of metallic nanoparticles are suggested to be used in security and authentication applications. We present a polarimetric optical method able to authenticate random phase encoded QR codes. The system is illuminated using polarized light and the QR code is encoded using a phase-only random mask. Using classification algorithms it is possible to validate the QR code from the examination of the polarimetric signature of the speckle pattern. We used Kolmogorov-Smirnov statistical test and Support Vector Machine algorithms to authenticate the phase encoded QR codes using polarimetric signatures.

Polyclonal antibodies to the coat protein of Apple stem grooving virus expressed in Escherichia coli: production and use in immunodiagnosis

The coat protein gene of Apple stem grooving virus (ASGV) was amplified by RT-PCR, cloned, sequenced and subcloned in the expression vector pMal-c2. This plasmid was used to transform Escherichia coli BL21c+ competent cells. The ASGV coat protein (cp) was expressed as a fusion protein containing a fragment of E. coli maltose binding protein (MBP). Bacterial cells were disrupted by sonication and the ASGVcp/MBP fusion protein was purified by amylose resin affinity chromatography. Polyclonal antibodies from rabbits immunized with the fusion protein gave specific reactions to ASGV from infected apple (Malus domestica) cv. Fuji Irradiada and Chenopodium quinoa at dilutions of up to 1:1,000 and 1:2,000, respectively, in plate trapped ELISA. The ASGVcp/MBP fusion protein reacted to a commercial antiserum against ASGV in immunoblotting assay. The IgG against ASGVcp/MBP performed favorably in specificity and sensitivity to the virus. This method represents an additional tool for the efficient ASGV-indexing of apple propagative and mother stock materials, and for use in support of biological and molecular techniques.

Steganografia ja kuvien digitaalinen vesileimaus

Steganografian tarkoituksena on salaisen viestin piilottaminen muun informaation sekaan. Tutkielmassa perehdytään kirjallisuuden pohjalta steganografiaan ja kuvien digitaaliseen vesileimaamiseen. Tutkielmaan kuuluu myös kokeellinen osuus. Siinä esitellään vesileimattujen kuvien tunnistamiseen kehitetty testausjärjestelmä ja testiajojen tulokset. Testiajoissa kuvasarjoja on vesileimattu valituilla vesileimausmenetelmillä parametreja vaihdellen. Tunnistettaville kuville tehdään piirreirrotus. Erotellut piirteet annetaan parametreina luokittimelle, joka tekee lopullisen tunnistamispäätöksen. Tutkimuksessa saatiin toteutettua toimiva ohjelmisto vesileiman lisäämiseen ja vesileimattujen kuvien tunnistamiseen kuvajoukosta. Tulosten perusteella, sopivalla piirreirrottimella ja tukivektorikoneluokittimella päästään yli 95 prosentin tunnistamistarkkuuteen.

Prediction of market switching and delisting events from OMX First North Nordic multilateral stock exchange

This thesis studies the predictability of market switching and delisting events from OMX First North Nordic multilateral stock exchange by using financial statement information and market information from 2007 to 2012. This study was conducted by using a three stage process. In first stage relevant theoretical framework and initial variable pool were constructed. Then, explanatory analysis of the initial variable pool was done in order to further limit and identify relevant variables. The explanatory analysis was conducted by using self-organizing map methodology. In the third stage, the predictive modeling was carried out with random forests and support vector machine methodologies. It was found that the explanatory analysis was able to identify relevant variables. The results indicate that the market switching and delisting events can be predicted in some extent. The empirical results also support the usability of financial statement and market information in the prediction of market switching and delisting events.

Interoperability specifications and an automatic validation tool as a key factor for the support of a repository ecosystem

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014