Sammanfattning Syfte: Syftet med detta examensarbete är att skapa ett ramverk för att underlätta valet av automatisk identifieringsteknik för tillverkningsföretag med tillhörande lagerhanteringsprocesser. Syftet är också att identifiera brister i Emballator Lagan Plasts nutida spårbarhetslösning, tillämpa ramverket för att välja en lämplig automatisk identifieringsteknik och utforma en bättre framtida spårbarhetslösning.  Metod: Denna studie är baserad i kvalitativ forskningsmetod och inkluderar en systematisk litteraturstudie, en intervjustudie och en fallstudie. Data till första forskningsfrågan insamlades genom en systematisk litteraturstudie och en intervjustudie med expert inom automatiska identifieringstekniker. Data till forskningsfråga två insamlades genom intervjuer med anställda hos Emballator Lagan Plast tillsammans med vetenskapliga artiklar.  Resultat: Genom att analysera data från den systematiska litteraturstudien gentemot data från intervjustudien sammanställdes ramverket för val av automatisk identifieringsteknik. Baserat på intervjuer med anställda identifierades brister i den nuvarande spårbarhetslösningen hos Emballator Lagan Plast. Ramverket tillämpades sedan för att välja automatisk identiferingsteknik som en del av den framtida spårbarhetslösningen. Den framtida spårbarhetslösningen baseras på 2D-streckkoder, förändringar i lagerhanteringsprocesserna samt mer utnyttjande av det tillgängliga lagerhanteringsystemet. / Abstract Purpose: The purpose of this thesis is to create a framework for manufacturing companies to facilitate the choice of auto-id technology. The purpose is also to identify faults in the current traceability solution at Emballator Lagan Plast, apply the framework to choose an auto-id technology and to suggest the future traceability solution.  Method: This thesis is based on qualitative method and includes a systematic literature review, an interview study and a case study. For research question one data was gathered through a systematic literature review and through an interview with an expert in the field of auto-id technologies. For research question two data was gathered through interviews with employees at Emballator Lagan Plast together with scientific articles.  Results: By analysing data from the systematic literature review and the interview the framework for choosing an auto-id technology was established. Based on interviews with employees’ faults in the current traceability solution at Emballator Lagan Plast was identified. The framework was applied to choose an auto-id technology as a part of the future traceability solution. The future traceability solution consists of 2D-barcodes, changes in warehouse processes and increased utilization of the warehouse management system.

[pt] A deposição de parafina é um dos principais problemas quando se trata de garantia de escoamento. O fluido que sai quente dos reservatórios é transportado por dutos que trocam calor com o ambiente frio. Quando o fluido atinge temperaturas abaixo da TIAC (Temperatura Inicial de Aparecimento de Cristais), partículas de sólido se precipitam. Isto causa não só aumento da viscosidade, mas também a formação de depósito nas paredes dos dutos, diminuindo a seção livre de escoamento e consequentemente a produção, ou até mesmo obstruindo totalmente o duto, resultando em um grande esforço de manutenção e causando grandes perdas de capital. Este problema é bastante recorrente, sendo assim, prever a deposição da parafina é crucial para projetos e operações de dutos, sendo preciso desenvolver modelos numéricos que forneçam resultados de forma acurada e eficiente. Considerando que os dutos são muito longos, o presente trabalho propõe um modelo hidrodinâmico unidimensional, com um modelo bidimensional de transferência de calor obtido através de um processo de marcha ao longo do duto. Todas as propriedades e fração volumétrica de sólido são determinadas em função da composição do fluido, pressão e temperatura, a partir de interpolações de tabelas criadas com um modelo termodinâmico em uma etapa de pré-processamento. O modelo considera a existência de depósito na parede do duto quando a fração de volume de sólido é igual ou maior do que 2 por cento. A modelagem proposta foi avaliada em diferentes situações, em escala laboratorial e de campo, apresentando dados de temperatura, pressão e espessura do depósito com concordância razoável com dados da literatura, mostrando que a modelagem implementada reproduz satisfatoriamente o comportamento físico do fenômeno de deposição de parafina. / [en] Wax deposition is one of the main problems when it comes to flow assurance. The hot fluid which leaves the reservoirs is transported by pipelines that exchange heat with the cold environment. Solid particles precipitate when the fluid reaches temperatures below the WAT (Wax Appearance Temperature). It causes not only an increase in viscosity, but also the formation of deposits on the pipe walls, reducing the cross-flow area and the production, or even totally obstructing the pipe, resulting in a significant maintenance effort and causing large capital losses. This problem is quite recurrent, therefore, predicting of wax deposition is crucial for pipeline projects and operations, and it is necessary to develop numerical models that provide accurate and efficient results. Considering that pipelines are very long, the present work proposes a one-dimensional hydrodynamic model with a two-dimensional heat transfer model being obtained through a marching process along the pipeline. All properties and solid volumetric fraction are determined as a function of fluid composition, pressure and temperature, from tables interpolation created with a thermodynamic model in a pre-processing step. The model considers the deposit existence on the pipe wall when the solid volume fraction is equal to or greater than 2 percent. The proposed model was evaluated in different situations, in a laboratory and field scale, presenting temperature, pressure and deposit thickness data in reasonable agreement with literature data, showing that the implemented model reproduces satisfactorily the physical behavior of the wax deposition phenomenon.

[pt] O modelo de Dois-Fluidos 1D vem sendo usado de forma abrangente em simulações industriais para prever escoamentos bifásicos em dutos. Avanços recentes na metodologia de Regime Capturing permitem a detecção das transições entre padrões de escoamento através do crescimento de instabilidades interfaciais. Contudo, devido aos procedimentos de média necessários para a redução da dimensionalidade do problema, perdas de informação tornam o modelo mal posto, i.e., perturbações de comprimentos de onda curtos são amplificados a taxas ilimitadas e soluções não físicas são obtidas. Relações de fechamento possuem um papel chave nesse problema, uma vez que estas são necessárias para fechar o sistema 1D e reintroduzem os mecanismos físicos perdidos que podem estabilizar o escoamento e tornar o modelo bem-posto. O presente trabalho propõe um modelo para o parâmetro de fluxo de quantidade de movimento da fase líquida (ou fator de forma), baseado na distribuição da velocidade do filme, que depende das grandezas locais do escoamento. A Teoria de Estabilidade Linear (LST) pode ser usada para avaliar a influência dos parâmetros de fechamento no crescimento de perturbações e na hiperbolicidade do modelo. A abordagem viscosa da análise de estabilidade diferencial de Kelvin-Helmholtz e a análise discreta de von Neumann são realizadas para avaliar relações de fechamento comumente utilizadas na literatura, bem como as formulações propostas para o parâmetro de fluxo. Simulações numéricas são realizadas, e relações de dispersão numéricas são extraídas dos resultados para verificar as previsões com os dados da LST. Uma avaliação numérica rigorosa dos novos modelos do parâmetro de fluxo com um grande banco de dados experimental é realizada. Os resultados mostraram que as correlações propostas superam os valores padrão constantes de fator de forma para avaliações de gradiente de pressão e espessura do filme de líquido. Os modelos também mostraram melhor consistência ao longo do extenso banco de dados. / [en] The 1D Two-Fluid model has been widely used in industrial simulations to predict two-phase flows in pipelines. Recent advances of the Regime Capturing methodology allow for the detection of flow pattern transitions from the onset and development of interfacial instabilities. However, due to the averaging processes required to reduce the dimensionality of the problem, the loss of information renders the model ill-posed, i.e., short wavelengths disturbances are amplified at an unbounded rate and unphysical solutions are obtained. Closure relations play a key role in this problem, since they are required to close the 1D system. Further, the reintroduction of the missing physics may stabilize the flow and render the model well-posed. The present work proposes a model for the liquid momentum flux parameter based on the liquid film velocity profile that is dependent on the local flow quantities. Linear Stability Theory (LST) can be used to assess the influence of closure parameters in the growth of disturbances and to evaluate the hyperbolicity of the model. A viscous approach of the differential Kelvin-Helmholtz and a discrete von Neumann stability analyses are performed to evaluate commonly employed closure models and the proposed formulations for the liquid momentum flux parameter. Numerical simulations are performed, and numerical dispersion relations are extracted from the results to verify the predictions against LST data. A rigorous numerical evaluation of the novel momentum flux parameter models against a large experimental database taken from the literature is carried out. Results show that the proposed models outperform the standard constant 𝐶𝐿 values for both pressure drop and liquid film thickness. The models also showed better overall consistency throughout the extensive experimental database.

Begreppet översvämningar har länge varit ett väl diskuterat ämne inom den akademiska världen och har även nu på senare år uppmärksammats alltmer i nyheter samt av allmänheten i sin helhet. Översvämningar är inte längre ett naturfenomen som kan anses inträffa vid sällsynta tillfällen. Den ökade globala uppvärmningen och det förändrade klimatet spås ge en ökning av extrema nederbördstillfällen. Så sent som 17–18 augusti 2021 drabbades stora delar av Gävle av översvämningar till följd av ett extremt skyfall. Kunskap om och förmågan att kunna hantera dessa extremfenomen är väsentligt för framtidens samhälle. Med detta i åtanke har denna studie undersökt hur översvämningsutbredningen och utbredningen på tillhörande osäkerhetszoner skiljer sig beroende på framställningssätt. Med hjälp av HEC-RAS har både endimensionell (1D) och tvådimensionell (2D) hydrauliska modeller använts för att simulera den översvämning som drabbade Gävle. Studien har utförts som en fallstudie över Västra Kungsbäckens vattendrag. Global Navigation Satellite Systems (GNSS) har använts för att skaffa noggrannare batymetrisk data. Genom en korrigerad höjdmodell och fotografier från översvämningen från den 18 augusti 2021 kunde modellerna kalibreras. Därefter utfördes flödesmodellering och vidare framställdes översvämningskartor och översvämningskartor med osäkerhetszoner. Resultatet visar att den utbredning översvämningen fick beroende på modell var mycket lika. Viss skillnad föreligger i geometrin men den procentuella utbredningen (2,3 %, 5 837 m2) är minimal. När det kommer till osäkerhetszonsutbredningen framgår den totala ytan väldigt lika mellan modellerna men däremot förekommer en större skillnad i geometrin för de två områdena; säkert att översvämmas och osäkert att översvämmas mellan modellerna. Utifrån studiens förutsättningar har ett tillförlitligt resultat tagits fram där fältstudien med mätningen har förbättrat tillförlitligheten på höjddata och kalibreringen av modellen har gjorts utifrån väl beprövade metoder i litteraturen. Ytterligare validering har gjorts mot en tidigare studies resultat och slutsatsen som kan dras är att modellerna är tillförlitliga. Likt all framställning av kartor förekommer det även osäkerheter i denna studie och fler studier över andra områden krävs för att fastställa hur en endimensionell modell skiljer sig mot en tvådimensionell ur ett utbredningsperspektiv. För osäkerhetsutbredningen krävs det fler studier med 2D-data för att kunna bekräfta de antaganden som gjorts. / The concept of floods has long been a well discussed topic in the academic world and has even now in recent years received increasing attention in the news and also by the general public. Floods are no longer a natural phenomenon that can be considered to occur on rare occasions. The increased global warming and the changing climate are predicted to result in an increase in extreme cloudbursts. As recently as 17–18 August 2021, large parts of Gävle were affected by floods as a result of an extreme downpour. Knowledge of and the ability to deal with these extreme phenomena is essential for cities of the future. With this in mind, this study has examined how the prevalence of flooding and the prevalence of associated zones of uncertainty differ depending on the method of production for flood maps. With the help of HEC-RAS, both one-dimensional (1D) and two-dimensional (2D) hydraulic models were used to simulate the flood that affected Gävle. The study has been carried out as a case study of the western part of the stream Kungsbäcken. Global Navigation Satellite Systems (GNSS) has been used to get more accurate bathymetric data. Through a corrected elevation model and photographs from the flood of 18 August 2021, the models could be calibrated. Subsequently, flow modeling was performed and further flood maps and flood maps with uncertainty zones were produced. The results show that the extent of the flood depending on the model was very similar. There are some differences in the geometry, but percentage wise, the extent difference (2,3 %, 5 837 m2) is minimal. When it comes to the uncertainty zones produced, the total areal extent is very similar between the models, but there is a greater difference in the geometry for the two areas; certain to be flooded areas and uncertain to be flooded areas between the models. Based on the study’s conditions, a result has been achieved where the field study with the measurements has improved the reliability of elevation data and the calibration of the model has been based on well-proven methods in the literature. Further validation has been done against the result of a previous study and it can be concluded that the models are reliable. Like all map production, there are also uncertainties in this study and more studies on other areas are required to determine how a one-dimensional model differs from a two-dimensional one from a distribution perspective. For the prevalence of uncertainty, more studies with 2D data are required to be able to confirm the assumptions made.

As modern systems are becoming increasingly complex, they are also becoming more and more cumbersome to diagnose and fix when things go wrong. One domain where it is very important for machinery and equipment to stay functional is in the world of medical IT, where technology is used to improve healthcare for people all over the world. This thesis aims to help with reducing downtime on critical life-saving equipment by implementing automatic analysis of system logs that without any domain experts involved can give an indication of the state that the system is in. First, a literature study was performed where three potential candidates of suitable neural network architectures was found. Next, the networks were implemented and a data pipeline for collecting and labeling training data was set up. After training the networks and testing them on a separate data set, the best performing model out of the three was based on GRU (Gated Recurrent Unit). Lastly, this model was tested on some real world system logs from two different sites, one without known issues and one with slow image import due to network issues. The results showed that it was feasible to build such a system that can give indications on external parameters such as network speed, latency and packet loss percentage using only raw system logs as input data. GRU, 1D-CNN (1-Dimensional Convolutional Neural Network) and Transformer's Encoder are the three models that were tested, and the best performing model was shown to produce correct patterns even on the real world system logs. / I takt med att moderna system ökar i komplexitet så blir de även svårare att felsöka och reparera när det uppstår problem. Ett område där det är mycket viktigt att maskiner och utrustning fungerar korrekt är inom medicinsk IT, där teknik används för att förbättra hälso- och sjukvården för människor över hela världen. Syftet med denna avhandling är att bidra till att minska tiden som kritisk livräddande utrustning inte fungerar genom att implementera automatisk analys av systemloggarna som utan hjälp av experter inom området kan ge en indikation på vilket tillstånd som systemet befinner sig i. Först genomfördes en litteraturstudie där tre lovande typer av neurala nätverk valdes ut. Sedan implementerades dessa nätverk och det sattes upp en datapipeline för insamling och märkning av träningsdata. Efter att ha tränat nätverken och testat dem på en separat datamängd så visade det sig att den bäst presterande modellen av de tre var baserad på GRU (Gated Recurrent Unit). Slutligen testades denna modell på riktiga systemloggar från två olika sjukhus, ett utan kända problem och ett där bilder importerades långsamt på grund av nätverksproblem. Resultaten visade på att det är möjligt att konstruera ett system som kan ge indikationer på externa parametrar såsom nätverkshastighet, latens och paketförlust i procent genom att enbart använda systemloggar som indata.  De tre modeller som testades var GRU, 1D-CNN (1-Dimensional Convolutional Neural Network) och Transformer's Encoder. Den bäst presterande modellen visade sig kunna producera korrekta mönster även för loggdata från verkliga system.

Syftet med fallstudien var att undersöka möjligheterna och nyttan med att implementera en höjdmodell med högre upplösning i SMHI:s översvämningsmodellering som tillämpar den hydrauliska modellen LISFLOOD-FP. SMHI utfärdar översvämningsvarningar och det är därför av vikt att översvämningsmodelleringen håller hög kvalitet. Samtidigt kräver modelleringen tid och resurser från Nationellt Superdatorcentrum i Linköping, NSC. Därför vägdes de potentiella fördelarna med högre upplösning mot förlängd körtid. Fallstudien bestod av två delar där en höjdmodell på två meters upplösning i xy-planet implementerades och jämfördes med den i dagsläget uppställda modellen på fem meters upplösning. Detta gjordes genom att återskapa översvämningstillfällen med dess flöden från S-HYPE och mätningar. I studiens första del hämtades satellitdata från Copernicus från två tidigare översvämningstillfällen för validering av över-svämningsmodelleringen. De tidigare översvämningstillfällena var dels i Emån i Småland år 2012 och dels i Västerdalälven i Dalarna år 2018. Ett index för passning beräknades mellan översvämningskartorna producerade med två respektive fem meters upplösning gentemot satellitbilderna för att kvantifiera överlappande ytor. Därtill beräknades vattendragens lutning för att undersöka om det fanns indikationer på något samband med förändring i index med ökad upplösning på höjdmodellen. Studiens andra del bestod i att undersöka hur höjdmodellens upplösning påverkar vattnets spridning kring översvämningsvallar i modellen. I undersökningen återskapades ett översvämningstillfälle från 2020 i Helige å i Småland. Ett antal delavrinningsområden visade sig instabila för den högre upplösta höjdmodellen och kunde därför endast simuleras med lägre flöden. Erhållna resultat visade dock på att översvämningskarteringen förbättrades med upplösningen två meter vid jämförelse med data från Copernicus. Körtiden ökade dock med över 12 gånger vid simulering av högre upplösning. Vidare visades tröskeleffekter i studiens resultat, då översvämnings-vallen stoppade vattnet i den högre upplösta höjdmodellen men inte i den med lägre upplösning. På grund av stabilitetsproblemet och studiens begränsade omfattning, kunde slutsats inte dras om huruvida SMHI bör implementera en höjdmodell med två meters upplösning i systemet för översvämningsvarningar. Däremot kunde konstateras att stabiliteten i modellen måste öka för att det ska vara möjligt. Slutligen drogs slutsatsen att det förekommer tröskeleffekter mellan de två höjdmodellerna och att prestandan ökar generellt för den högre upplösningen när det kommer till precisionen i översvämningsmodelleringen. / The purpose of this case study was to examine the possibilities and advantages of implementing a DEM with higher resolution in inundation modelling at SMHI, the Swedish Meteorological and Hydrological Institute, which uses the hydraulic model LISFLOOD-FP. The institute issues flood warnings and therefore it is of high importance that the innundation modelling gives adequate results. On the other hand, running the models at a higher spatial resolution takes more time and resources. Therefore, potentially improved modelling results were discussed in a context of prolonged runtime. The case study consisted of two parts where a Digital Elevation Model, DEM of two meter resolution was implemented and compared to the five meter DEM that is currently in use. This was done by recreating previous flooding events by using discharge data from S-HYPE. In the first part, satellite data from Copernicus from two previous flooding events in Sweden were used for model validation in comparison with the results from inundation models of SMHI for the different DEM:s. An index was calculated to quantify the overlapping inundation areas. The events were at the river Emån in 2012 and at Västerdalälven in 2018. Moreover, the slope of the rivers within each study area was calculated to investigate correlation between improved flood modelling results for higher DEM resolution and slope of the rivers. The second part of the study investigated flood embankments for the two different DEM:s around Helige å river. A flooding event which took place in 2020 was recreated and the water flow around the built embankments was compared for the two resolutions.  Running the models, it turned out that simulations of several subcatchment areas were unstable with the two meter DEM, and could only be run with lower flow. The obtained results, however, revealed an improved inundation modelling for the DEM with a resolution of 2 m for all study areas in comparison to the data from Copernicus; however the runtime was increased by over 12 times. Moreover, the results also showed threshold effects, where the flooding was impeded by the flooding embankment with the two meter DEM but not at the lower resolution. Due to the stability issue and the limited scope of this study, it cannot be concluded whether SMHI should implement the two meter DEM in their flood warnings system. However, it was concluded that the stability has to be increased to make it feasible. It was also concluded that there are threshold effects between the two DEM:s and that the performance seems to increase overall for the higher resolution when it comes to precision of the modelling.

Focusing on the problem of Drone vs. Unknown classification based on radar frequency-amplitude spectra using Deep Learning (DL), especially 1-Dimensional Convolutional Neural Networks (1D-CNNs), this thesis aims at reducing the current gap in the research related to adequate pre-processing techniques for hardware deployment. The primary challenge tackled in this work is determining a pipeline that facilitates industrial deployment while maintaining high classification metrics. After presenting a comprehensive review of existing research on radar signal classification and the application of DL techniques in this domain, the technical background of signal processing is described to provide a practical scenario where the solutions could be implemented. A thorough description of technical constraints, such as Field Programmable Gate Array (FPGA) data type requirements, follows the entire project justifying the necessity of a learning-based pre-processing technique for highly skewed distributions. The results demonstrate that data-adaptive preprocessing eases hardware deployment and maintains high classification metrics, while other techniques contribute to noise and information loss. In conclusion, this thesis contributes to the field of radar frequency-amplitude spectra classification by identifying effective methods to support efficient hardware deployment of 1D-CNNs, without sacrificing performance. This work lays the foundation for future studies in the field of DL for real-world signal processing applications. / Med fokus på problemet med klassificering av drönare kontra okänt baserat på radarfrekvens-amplitudspektra med Deep Learning (DL), särskilt 1-Dimensional Convolutional Neural Networks (1D-CNNs), syftar denna avhandling till att minska det nuvarande gapet i forskningen relaterad till adekvata förbehandlingstekniker för hårdvarudistribution. Den främsta utmaningen i detta arbete är att fastställa en pipeline som underlättar industriell driftsättning samtidigt som höga klassificeringsmått bibehålls. Efter en omfattande genomgång av befintlig forskning om klassificering av radarsignaler och tillämpningen av DL-tekniker inom detta område, beskrivs den tekniska bakgrunden för signalbehandling för att ge ett praktiskt scenario där lösningarna kan implementeras. En grundlig beskrivning av tekniska begränsningar, såsom krav på datatyper för FPGA (Field Programmable Gate Array), följer hela projektet och motiverar nödvändigheten av en inlärningsbaserad förbehandlingsteknik för mycket skeva fördelningar. Resultaten visar att dataanpassad förbehandling underlättar hårdvaruimplementering och bibehåller höga klassificeringsmått, medan andra tekniker bidrar till brus och informationsförlust. Sammanfattningsvis bidrar denna avhandling till området klassificering av radarfrekvens-amplitudspektra genom att identifiera effektiva metoder för att stödja effektiv hårdvarudistribution av 1D-CNN, utan att offra prestanda. Detta arbete lägger grunden för framtida studier inom området DL för verkliga signalbehandlingstillämpningar.

Numerical simulations of current-voltage characteristics of nanowire CdS/CdTe solar cells are performed as a function of temperature using SCAPS-1D. This research compares the experimental current-voltage (I-V) characteristics with the numerical (I-V) simulations obtained from SCAPS-1D at various temperatures. Various device parameters were studied which can affect the efficiency of the nanowire-CdS/CdTe solar cell. It was observed that the present simulated model explains the important effects of these solar cell devices, such as the crossover and the rollover effect. It was shown that the removal of defect in i-SnO2 is responsible for producing the crossover effect. In the past, the rollover effect has been explained by using back to back diode model in the literature. In this work, simulations were performed in order to validate this theory. At the back electrode, the majority carrier barrier height was varied from 0.4 to 0.5 eV, the curve corresponding to the 0.5 eV barrier showed a strong rollover effect, while this effect disappeared when the barrier was reduced to 0.4 eV. Thus, it was shown that the change of barrier height at the contact is a critical parameter in the rollover effect.

Alors que le protéome de l'ovocyte isolé, aux stades VG et MII a déjà été étudié, celui du follicule en croissance n'a jamais été décrit.Dans cette étude, nous avons cherché à identifier, comparer et caractériser les profils protéiques de follicules ovariens de souris à trois stades de leur développement in vitro distincts morphologiquement : follicules secondaires en début de culture - stade initial (IS), follicules avec une rupture complète de la membrane de Slavjanski (RMS) et follicules avec une cavité similaire à l'antrum (FA).Après un préfractionnement par IEF et une analyse LC-MS/MS en deux configurations (1D et 2D), 1403 protéines ont pu être identifiées dans le follicule ovarien de souris. 43,4 % (609) des protéines identifiées étaient communes aux trois stades et d'autres ont été identifiées uniquement à un stade : 71 au stade IS, 182 au stade RMS et 193 au stade FA. De plus, on a identifié 365 protéines qui n'avaient pas été décrites antérieurement dans le protéome de l'ovocyte ce qui pourrais indiquer qu'elles sont exprimées dans les cellules somatiques du follicule. Des analyses qualitatives et quantitatives complémentaires ont démontré une surreprésentation pour 44 fonctions biologiques par rapport aux fonctions biologiques des gènes constituant le génome de Mus musculus et mis en évidence des différences d'expression et d'abondance des protéines liées au cycle cellulaire, à la fixation des ions de calcium et à la glycolyse selon le stade de développement. Ces résultats représentent un point de départ pour beaucoup d'autres études de caractérisation moléculaire du développement folliculaire. / Until now only the proteome of isolated oocyte from fully grown follicle were described with the aim of oocyte maturation characterization. However the ability of oocyte to mature is acquired during its development within the follicle. Thus in this study we proposed a protein identification and characterization of whole mice ovarian follicle at three morphological stages during in vitro development: early secondary stage, described as initial stage (IS), follicles with a complete Slavjanski membrane rupture (RMS) and follicles with an antrum like cavity formation (FA). Using an IEF pre fractionation before protein digestion and two configurations of LC-MS/MS analysis (1D and 2D), 1403 proteins were successfully identified in the murine ovarian follicle. From those, 43.4 % (609) were commonly identified in the three stages and some were identified only at one single stage: 71 at IS stage, 182 at RMS stage and 193 at FA stage. Compared to the proteomes of isolated oocyte previously described, 365 proteins were only identified in our samples indicating that those ones were probably expressed in the somatic cells of the follicle. Additional qualitative and quantitative analysis highlighted 44 biological processes over represented in our samples when compared to Mus musculus gene database and different expressions and protein abundance implicated in cell cycle, calcium ion binding and glycolysis, throughout in vitro follicle development. This report represents so far the most complete catalogue of follicle proteins and could be an important milestone in the proteomic study of the follicle metabolism throughout in vitro development.

Groundwater is a crucial part of the hydrological cycle and is an important source for drinking water, irrigation and industry, particularly during droughts. With climate change, the hydrological variability is predicted to increase, making predictions for recharge and groundwater storage even more important to implement and to maintain sustainable water use. This study examines the importance of model spin-up in simulating recharge using the Hydrus-1D computer model. The focus is on two previously made Hydrus-1D models that represent end members in climate and hydrology; one which is a natural grassland in a semi-arid climate, while the other is a low impact development (LID) bioswale site in a Mediterranean climate. The main goal of this study is to characterize the range and causes of spin-up behavior as well as to analyze the extent of the effects that the spin-up process has on the recharge simulations. Although there has been some research on spin-up behavior for surface-water models, there is still a knowledge gap regarding the effects of model spin-up on vadose zone models simulating recharge. The initial conditions varied using three parameters for each of the two models: time (3, 15 and 30 years), initial moisture (θ = 0.1, 0.2 and 0.3) and precipitation (25% drier than historical data, historical 30-year data, 25% wetter than historical data). The output from these spin-ups were then used as initial conditions in simulating recharge using the 15-year models. The study found that the impact of spin-up is significant in the natural grassland site where there is a slow response between atmospheric forcings and recharge and where there is a relatively thick vadose zone. Especially spin-up time showed great variability and there is an inverse relationship between spin-up time and magnitude of recharge, where the longer spin-ups had lower recharge rates. Initial water content and precipitation did not result in different recharge amounts for the LID model. Length of spin-up only had very small differences in recharge for the LID models, indicating they are less sensitive to changes in initial spin-up parameters.