Bedömning av kvaliteten är en av de viktigaste processerna som en lärare utför varje arbetsdag för att kunna relatera elevernas prestationer mot ett kulturellt och individuellt anpassat betygssystem. Med ambitionen att främja jämställdhet och reliabilitet av bedömningar tillhandahåller Skolverket bedömningskrav och kriterier för att skilja olika grader av kvalitet (Selghed 2011). Dessa kriterier förefaller emellertid ibland otydliga och inte lämpliga för att särskilja mellan kvalitativa nivåer, särskilt på högre nivåer, vilka därför kan uppfattas som delvis överlappande. Som följd finns det mycket utrymme för tolkning av den enskilda läraren när det slutliga bedömningssystemet konstrueras (Schreiber et al., 2012, Selghed 2011). En alternativ bedömningsmetod som är rekommenderad av t.ex. Hattie (2012), är den mindre komplexa SOLO-taxonomin vilken idag används i de högre utbildnings miljöer.För att uppskatta överlappningen mellan resultat som härrör från olika bedömningsmetoder analyserar denna studie kvalitetsnivåer av en skrivuppgift av andraårs-gymnasieelever med hjälp av det läroplanbaserade betygssystemet och SOLO-taxonomin. Med hjälp av principiell komponentanalys (PCA) och korrelationsanalys kunde man dra slutsatsen att de olika bedömningsmetoderna är lämpliga för att skilja högre från lägre komplexitet eller kvalitetsnivåer. Men SOLO-taxonomin kunde inte tydligt skilja de mer sofistikerade skillnaderna mellan högre betygsnivå A och B.Dessutom undersökte denna studie om en noggrant genomförd konstruktivistisk undervisningsdesign oundvikligen resulterar i högkvalitativa skriftliga arbeten. Detta analyserades med hjälp av PCA och korrelationsanalys av relationen mellan deltagarnas kunskapssyn och bedömningsresultatet. Inom detta sammanhang kunde det dras slutsatsen att (I) en mer sofistikerad syn på naturen av kunskap och kunskap och (II) heterogeniteten hos en studentgrupp med avseende på kunskapssynen verkar vara kopplad till högre kvalitativa prestationer. Bevis för en korrelation mellan elevernas individuella kunskapssyn och de valda inlärningsmetoderna diskuteras inom ramen för en generell lämplighet av konstruktivistiska undervisningsmetoder.

Le cancer de la prostate (PCa) est le deuxième cancer le plus courant chez les hommes au niveau mondial. Le suppresseur de la signalisation des cytokines 1 (SOCS1) est considéré comme un suppresseur de tumeur en raison de la fréquente répression épigénétique de ce gène dans de nombreux cancers. Il a été reporté que SOCS1 inhibait l’activation de STAT3 induite par l’IL-6, ainsi que les cyclines et les kinases dépendantes des cyclines dans les cellules malignes de la prostate. D’autre part, il a été montré que SOCS1 n’était pas essentiel lors du contrôle de la signalisation de l’IL-6 dans les hépatocytes dépourvus de cette protéine, cependant elle est essentielle pour atténuer la signalisation du facteur de croissance des hépatocytes (HGF) via son récepteur MET. MET est un récepteur de tyrosine kinases qui est surexprimé dans le PCa agressif et métastatique. Notre hypothèse de recherche propose que la répression de SOCS1 par méthylation du promoteur et la dérégulation de l’expression de MET et de sa signalisation, sont des mécanismes pathogéniques liés au développement et à la progression du PCa. Nous avons généré des lignées de cellules PC3 et DU145 stables exprimant SOCS1. Les cellules ont été stimulées avec HGF et l’activation des voies de signalisation a été évaluée par immunobuvardage. Des essais in vitro de migration, de prolifération et d’invasion ont été effectués en présence de HGF. Des gènes de transition épithélio-mésenchymateuse ont été évalués par PCR quantitatif en présence ou non du facteur de croissance. Les cellules du PCa transfectées ou pas avec SOCS1 ont été inoculées dans des souris NOD SCID gamma de façon sous-cutanée ou orthoptique afin d’évaluer respectivement la croissance tumorale et la formation de métastases. Les tumeurs reséquées ont été analysées histologiquement et biochimiquement. Nos résultats montrent que SOCS1 atténue l'activation de MET induite par HGF et la phosphorylation d’ERK dans les cellules PC3, ainsi que la phosphorylation d’ERK et d’AKT dans les cellules DU145. SOCS1 inhibe également la prolifération cellulaire induite par HGF, ainsi que la migration et l’invasion in vitro. De plus, SOCS1 réduit l’expression des gènes de transition épithélio-mésenchymateuse impliqués dans la dégradation des composants de la matrice extracellulaire dans les cellules DU145 mais pas dans les cellules PC3. La surexpression de SOCS1 a stimulé l’augmentation de déposition de collagène, in vivo. Les tumeurs formées par les cellules exprimant SOCS1 étaient de taille significativement plus petites avec une réduction de la prolifération comparé aux tumeurs provenant des cellules contrôles. En outre, SOCS1 a inhibé la formation de métastases à distance dans un modèle orthotopique. En conclusion, nous suggérons que SOCS1 est un suppresseur de tumeur indispensable de la prostate, et qu’au moins une partie de sa fonction a lieu via la régulation négative de la signalisation du récepteur MET. / Abstract : Prostate cancer (PCa) is the second most common cancer among men worldwide. Suppressor of cytokine signaling 1 (SOCS1) is considered a tumor suppressor due to frequent epigenetic repression of the SOCS1 gene in several human malignancies. Inactivation of SOCS1 also occurs in PCa by gene methylation and micro-RNA-mediated repression. SOCS1 has been reported to inhibit IL-6-induced STAT3 activation and down-regulates cyclins and cyclin-dependent kinases in PCa cells. It has been shown that SOCS1 is not required to control IL-6 signaling in SOCS1-deficient hepatocytes, but is essential to attenuate hepatocyte growth factor (HGF) signaling via its receptor MET. This protein is a receptor tyrosine kinase (RTK), overexpressed in aggressive and metastatic PCa. Thus we hypothesized that the repression of SOCS1 via promoter methylation and deregulated MET expression and signaling are inter-related pathogenic mechanisms in PCa development and progression. We generated stable SOCS1-expressing PCa cell lines (PC3 and DU145) using lentiviral transduction followed by clonal selection via limiting dilution. Cells were stimulated with HGF and downstream signaling events were assessed by Western blot. Proliferation, migration and invasion assays were also conducted in the presence of HGF in vitro. Epithelial mesenchymal transition genes were evaluated by qPCR in the presence or absence of the growth factor. The PCa cells transfected with SOCS1 and non-transfected controls were inoculated into NOD SCID gamma mice as xenografts or as orthotopic tumors to assess tumor growth and metastasis formation, respectively. Resected tumors were further analyzed histologically and biochemically. Our results showed that SOCS1 attenuates HGF-induced MET activation and ERK phosphorylation in PC3 and DU145 PCa cell lines. SOCS1 inhibited HGF induced cell proliferation, migration and invasion in vitro. Additionally, SOCS1 decreased epithelial mesenchymal transition genes involved in the degradation of extracellular matrix components in DU145 cells but not in PC3. In vivo, SOCS1 overexpression leads to an increase of collagen deposition. Tumors formed by SOCS1 expressing cells were significantly smaller in size with reduced cell proliferation compared to tumors arising from control cells. Furthermore, SOCS1 inhibited distant metastasis formation in the orthotopic model. Overall our results suggest that SOCS1 has a tumor suppressor role in PCa evolution and part of this function is mediated by the negative regulation of MET receptor signalling and down-regulation of genes supporting migration and invasion processes such as matrix metalloproteinases.

Lake volume and lake depth are important variables that defines a lake and its ecosystem. Sweden has around 100 000 lakes, but only around 8000 lakes has measured data for volume, max- and mean-depth. To collect data for the rest of the lakes is presently too time consuming and expensive, therefore a predictive method is needed. Previous studies by Sobek et al. (2011) have found a model predicting lake volume from map-derived parameters with high degrees of explanation for mean volume of 15 lakes or more. However, the predictions for one individual lake, as well as max- and mean-depth, were not accurate enough. The purpose with this study was to derive better models based on new map material with higher resolution. Variables used was derived using GIS-based calculations and then analyzed with multivariate statistical analysis with PCA, PLS-regression and multiple linear regression. A model predicting lake volume for one individual lake with better accuracy than previous studies was found. The variables best explaining the variations in lake volume was lake area and the median slope of an individual zone around each lake (R2=0.87, p<0.00001). Also, the model predicting max-depth from lake area, median slope of an individual zone around each lake and height differences in the closest area surrounding each lake, had higher degrees of explanation than in previous studies (R2=0.42). The mean-depth had no significant correlation with map-derived parameters, but showed strong correlation with max-depth. Reference Sobek, S., Nisell, J. & Fölster J. (2011). Predicting the volume and depths of lakes from map-derived parameters. Inland Waters, vol. 1, ss. 177-184.

A taxonomia vegetal atualmente exige um grande esforço dos botânicos, desde o processo de aquisição do espécime até a morosa comparação com as amostras já catalogadas em um herbário. Nesse contexto, o projeto TreeVis surge como uma ferramenta para a identificação de vegetais por meio da análise de atributos foliares. Este trabalho é uma ramificação do projeto TreeVis e tem o objetivo de identificar vegetais por meio da análise do corte transversal de uma folha ampliado por um microscópio. Para tanto, foram extraídas assinaturas da cutícula, epiderme superior, parênquima paliçádico e parênquima lacunoso. Cada assinatura foi avaliada isoladamente por uma rede neural pelo método leave-one-out para verificar a sua capacidade de discriminar as amostras. Uma vez selecionados os vetores de características mais importantes, os mesmos foram combinados de duas maneiras. A primeira abordagem foi a simples concatenação dos vetores selecionados; a segunda, mais elaborada, reduziu a dimensionalidade (três atributos apenas) de algumas das assinaturas componentes antes de fazer a concatenação. Os vetores finais obtidos pelas duas abordagens foram testados com rede neural via leave-one-out para medir a taxa de acertos alcançada pelo sinergismo das assinaturas das diferentes partes da folha. Os experimentos consitiram na identificação de oito espécies diferentes e na identificação da espécie Gochnatia polymorpha nos ambientes Cerrado e Mata Ciliar, nas estações Chuvosa e Seca, e sob condições de Sol e Sombra / Currently, taxonomy demands a great effort from the botanists, ranging from the process of acquisition of the sample to the comparison with the species already classified in the herbarium. For this reason, the TreeVis is a project created to identify vegetal species using leaf attributes. This work is a part of the TreeVis project and aims at identifying vegetal species by analysing cross-sections of leaves amplified by a microscope. Signatures were extract from cuticle, adaxial epiderm, palisade parenchyma and sponge parenchyma. Each signature was analysed by a neural network with the leave-one-out method to verify its ability to identify species. Once the most important feature vectors were selected, two different approachs were adopted. The first was a simple concatenation of the selected feature vectors. The second, and more elaborated approach, consisted of reducing the dimensionality (three attributes only) of some component signatures before the feature vector concatenation. The final vectors obtained by these two approaches were tested by a neural network with leave-one-out to measure the correctness rate reached by the synergism of the signatures of different leaf regions. The experiments resulted in the identification of eight different species and the identification of the Gochnatia polymorpha species in Cerradão and Gallery Forest environments, Wet and Dry seasons, and under Sun and Shadow constraints

Att hitta instrument för att efterlikna den mänskliga näsan har under en längre tid varit ett område som intresserar forskare. Dessa instrument kan potentiellt vara ett användbart verktyg för att uppnå FN:s uppsatta globala mål för att nå en hållbar utveckling, Agenda 2030. Projektet är en experimentell kvantitativ studie och syftet är att undersöka möjligheten att ta fram ett fristående mätsystem för detektering och identifiering av sur mjölk och ruttet kött i ett kylskåp. Ett trådlöst mätsystem med en serie gassensorer är framtaget tillsammans med ett gränssnitt för fjärrstyrning. Mätningar utfördes på kända mätobjekt under två veckor. Därefter utfördes mätningar på okända mätobjekt under lika lång tid. Resultatet från studien visade att det framtagna mätsystemet kan detektera och identifiera sur mjölk och ruttet kött utan extern programvara. Mätsystemet en tillförlitlighet på 89% när det gäller att klassificera okända mätobjekt. Denna studie visar att mätsystemet kan detektera och identifiera sur mjölk och ruttet kött via fjärrstyrning. / To find devices mimicking the human nose have under some time been an area of interest for researchers. These devices can potentially be a useful tool to achieve UN: s global goals for sustainable development, Agenda 2030. This project is an experimental quantitative study with the aim to investigate the possibility to create a stand-alone measuring system for detecting and identifying spoiled milk and rotten meat in a fridge. A wireless measuring system with an array of gas sensors was developed together with interface for remote control. Measurements was made from known measuring objects for two weeks. Thereafter measurements of unknown measuring objects were also done for two weeks. The result of the study showed that the developed measuring system can be remotely controlled to detect and identify spoiled milk and rotten meat without external software. The measuring system has an accuracy of 89% when it comes to classify unknown measurement objects. This study shows that the measuring system can detect and identify spoiled milk and rotten meat via remote control.

<p>U doktorskoj disertaciji evaluirani su interkorelacioni rezultati odnosa ključnih fizičko-hemijskih parametara i katjona metala u površinskoj vodi Dunava, Tise (na po tri selektovana reprezentativna lokaliteta) i kanala Dunav-Tisa-Dunav (na dva lokaliteta). U<br />Kanalu Dunav-Tisa-Dunav praćene su i rezidualne katjonske koncentracije metala u sedimentu. Na osnovu podataka prisutnosti katjona metala u heterogenom sistemu tečno/čvrsto izračunate su po prvi put konstante podeonih procesa za ispitivane katjone metala. Primenom multivarijantnih statističkih metoda analizirani su korelacioni odnosi između ključnih fizičko-hemijskih parametara i koncentracionih nivoa rezidula katjona teških, lakih i semimetala. Faktorskom analizom (PCA) i klaster analizom sa dendogramima tumačeni, analizirani i diskutovani su dobijeni rezultati. Za optimalnog uočavanja korelacionih odnosa primenjeno je unapređeno rangiranje određenih skupova podataka (interkorelacije ključnih fizičko-hemijskih parametara i rezidua katjona metala) i grafički prikazanih Haseovih dijagrama primenom DART softvera (Decision Analysis by Ranking Techniques) za definisani model procene uticaja raspodele katjona toksičnih metala u heterogenom sistemu tečno/čvrsto na kvalitet površinskih voda.</p> / <p>In the doctoral thesis are evaluated inter correlational results of key physicochemical parameters and metal cations in surface water of Danube, Tisa (on three selected representative sampling points) and canal Danube-Tisa-Danube (on two sampling sites). In the canal Danube-Tisa-Danube are also followed residual metal cations concentrations in sediment. Based on metal cations presence data in heterogeneous system liquid/solid for the first time partitioning processes constants are calculated for<br />selected metal cations. Appling multivariate statistical methods correlations between key physicochemical parameters and concentration levels of residual heavy, light and semimetals cations are analysed. Using factorial analyse (PCA) and cluster analyse with dendograms obtained results were interpreted, analysed and discussed. For optimal comprehension of correlations, advanced method ranking of finite order sets is applied (inter correlations key physicochemical parameters and residual metal cations) and graphically shown Hasse diagrams obtained by DART software (Decision Analysis by Ranking Techniques) for defined impact assessment model of toxic metal cations partitioning in heterogeneous system liquid/solid for surface water quality.</p>

Das erste gestellte Ziel war es, die histologischen Strukturen eines Gewebedünnschnittes anhand der aufgenommenen FT-IR-Spektren sichtbar zu machen und diese mit dem konventionell gefärbten Schnitt und der autoradiographischen Aufnahme zu vergleichen. Dazu wurde ein Messsystem bestehend aus einem FT-IR-Spektrometer mit Mikroskop und einem computergesteuerten XY-Tisch aufgebaut und die notwendige Steuer- und Auswerte-Software entwickelt. Es konnte gezeigt werden, dass sich die FT-IR-Spektren mit geeigneten Auswerteverfahren zur Darstellung der histologischen Strukturen nutzen lassen. Dazu wurden zwei verschiedene Methoden eingesetzt, die PCA und die Fuzzy-Clusterung (FCM). Im zweiten Teil dieser Arbeit sollte ein Klassifikations-Algorithmus gefunden werden, mit dessen Hilfe sich Spektren von unbekannten Gewebeproben vorher definierten Modellen zuordnen lassen. Dazu wurde eine Spektren-Datenbank aus mehr als einhundert Gewebeproben angelegt. Aus dieser Datenbank wurden einige zehntausend Spektren ausgewählt und zu Modell-Datensätzen für sechs verschiedene Gewebetypen zusammengefasst. Für die Zuordnung unbekannter Spektren zu diesen Modellen wurde ein SIMCA-Klassifikations-Algorithmus entwickelt sowie ein LDA-Algorithmus eingesetzt. Für beide Methoden wurde die Klassi-fikations-Leistung anhand der Spezifität und Sensitivität bestimmt. Beide Klassifikations-Algorithmen führten zu guten Ergebnissen. Der SIMCA-Algorithmus erreichte eine Spezifität zwischen 97 % und 100 %, sowie eine Sensitivität zwischen 62 % und 78 % (bei einem Vertrauensintervall von 97,5 %). Der LDA-Algorithmus ermöglichte eine etwas bessere Sensitivität von 72 % bis 90 %, auf Kosten der Spezifität, welche zwischen 90 % und 98 % lag. Zusammenfassend kann festgestellt werden, dass sich die FT-IR-Mikrospektroskopie und die vorgestellten Auswerte-Algorithmen sehr gut zur Klassifizierung von Gewebedünnschnitten eignen.

This work deals with fouling in the recovery boiler at Montes del Plata, Uruguay. Multivariate data analysis has been used to analyze the large amount of data that was available in order to investigate how different parameters affect the fouling problems. Principal Component Analysis (PCA) and Partial Least Square Projection (PLS) have in this work been used. PCA has been used to compare average values between time periods with high and low fouling problems while PLS has been used to study the correlation structures between the variables and consequently give an indication of which parameters that might be changed to improve the availability of the boiler. The results show that this recovery boiler tends to have problems with fouling that might depend on the distribution of air, the black liquor pressure or the dry solid content of the black liquor. The results also show that multivariate data analysis is a powerful tool for analyzing these types of fouling problems. / Detta arbete handlar om inkruster i sodapannan pa Montes del Plata, Uruguay. Multivariat dataanalys har anvands for att analysera den stora datamangd som fanns tillganglig for att undersoka hur olika parametrar paverkar inkrusterproblemen. Principal·· Component Analysis (PCA) och Partial Least Square Projection (PLS) har i detta jobb anvants. PCA har anvants for att jamfora medelvarden mellan tidsperioder med hoga och laga inkrusterproblem medan PLS har anvants for att studera korrelationen mellan variablema och darmed ge en indikation pa vilka parametrar som kan tankas att andras for att forbattra tillgangligheten pa sodapannan. Resultaten visar att sodapannan tenderar att ha problem med inkruster som kan hero pa fdrdelningen av luft, pa svartlutens tryck eller pa torrhalten i svartluten. Resultaten visar ocksa att multivariat dataanalys ar ett anvandbart verktyg for att analysera dessa typer av inkrusterproblem.

Through an analysis of the Swedish state budget, models have been developed to deepen the understanding of the effects that government expenditures have on reducing crime. This has been modeled by examining selected crime categories using the mathematical methods Ridge Regression, Lasso Regression and Principal Component Analysis. Combined with a qualitative study of previous research on the economic aspects of crime, an analysis has been conducted. The mathematical methods indicate that it may be more effective to invest in crime prevention measures, such as increased social protection and focus on vulnerable groups, rather than more direct efforts such as increased resources for the police force. However, the result contradicts some of the accepted economic conclusions on the subject, as these highlight the importance of increasing the number of police officers and harsher penalties. These do however also mention the importance of crime prevention measures such as reducing the gaps in society, which is in line with the results of this work. The conclusion should however be used with caution as the models are based on a number of assumptions and could be improved upon further analysis of these, together with more data points that would strengthen the validity of the analysis more. / Genom en analys av Sveriges statsbudget har modeller tagits fram för att försöka förstå de effekter olika samhällssatsningar har på brottslighet i Sverige. Detta har modellerats genom att undersöka utvalda brottskategorier med hjälp av de matematiska metoderna Ridge Regression, Lasso Regression samt Principal Component Analysis. Tillsammans med en kvalitativ undersökning av tidigare forskning gällande nationalekonomiska aspekter kring brottslighet har en analys sedan genomförts. De matematiska metoderna tyder på att det kan vara mer effektivt att satsa på brottsförebyggande åtgärder, såsom ökat socialt skydd och fokus på utsatta grupper, istället för mer direkta satsningar på brottsförhindrande åtgärder som exempelvis ökade resurser till polisväsendet. Däremot motsäger resultatet en del av de vedertagna nationalekonomiska slutsatserna om ämnet, då dessa belyser vikten av ökade antalet poliser och hårdare straff. De lyfter även fram vikten av brottsförebyggande åtgärder såsom att minska klyftorna i samhället, vilket går i linje med resultatet av detta arbete. Slutsatsen ska dock användas med försiktighet då modellerna bygger på flertalet antaganden och skulle kunna förbättras vid ytterligare analys utav dessa, tillsammans med fler datapunkter som skulle stärka validiteten.

Over the last years, due to the development of quieter engines and drivetrains, the importance of addressing the vehicle wind noise problem has significantly increased.In this thesis work, several existing Transfer Path Analysis methods have been applied on an experimental database acquired during a wind tunnel test on a passenger car with the objective of analyzing the distribution of the wind noise sources and their contribution to the target microphones located inside the vehicle. A major challenge for the Transfer Path Analysis (TPA) consists of the high complexity of the aerodynamic sources exciting the structure. Moreover, the existence of multiple incoherent source phenomena, and the presence of distributed coherent source regions of different correlation scales make the analysis very complex.The thesis work provides a solid and comprehensive analysis of the results obtained by different methods. The outcomes can be potentially useful for optimizing the vehicle NVH performance in future practical cases. / Under de senaste åren har vikten av att arbeta med vägfordons problem med aerodynamisk ljudgenerering ökat avsevärt på grund av utvecklingen av tystare motorer och drivlinor. I det här projektet har flera existerande metoder för Transfer Path Analysis (TPA) tillämpats på en databas med experimentella data som samlats in vid vindtunneltest på en personbil, med målet att analysera fördelningen av källorna orsakade av vindbruset och deras påverkan på ljudnivån vid de uppsatta målmikrofonerna inuti fordonet. En stor utmaning för TPA är den höga komplexiteten hos de aerodynamiska källorna som exciterar strukturen. Vidare gör förekomsten av flera okorrelerade källor, och närvaron av distribuerade koherenta källregioner med olika korrelationsskalor, analysen mycket komplex. Arbetet presenterar en solid och omfattande analys av resultat som erhållits med olika metoder. Resultaten är potentiellt användbara för att optimera fordonets NVH-prestanda i praktiktiken i framtiden.