One of the biggest challenges in healthcare is Emergency Department (ED)crowding which creates high constraints on the whole healthcare system aswell as the resources within and can be the cause of many adverse events.Is is a well known problem were a lot of research has been done and a lotof solutions has been proposed, yet the problem still stands unsolved. Byanalysing Real-World Data (RWD), complex problems like ED crowding couldbe better understood. Currently very few applications of survival analysis hasbeen adopted for the use of production data in order to analyze the complexityof logistical problems. The aims for this thesis was to apply survival analysisthrough advanced Machine Learning (ML) models to RWD collected at aSwedish hospital too see how the Length Of Stay (LOS) until admission ordischarge were affected by different factors. This was done by formulating thecrowding in the ED for survival analysis through the use of the LOS as thetime and the decision regarding admission or discharge as the event in order tounfold the clinical complexity of the system and help impact clinical practiceand decision making.By formulating the research as time-to-event in combination with ML, thecomplexity and non linearity of the logistics in the ED is viewed from a timeperspective with the LOS acting as a Key Performance Indicator (KPI). Thisenables the researcher to look at the problem from a system perspective andshows how different features affect the time that the patient are processedin the ED, highlighting eventual problems and can therefore be useful forimproving clinical decision making. Five models: Cox Proportional Hazards(CPH), Random Survival Forests (RSF), Gradient Boosting (GB), ExtremeGradient Boosting (XGB) and DeepSurv were used and evaluated using theConcordance index (C-index) were GB were the best performing model witha C-index of 0.7825 showing that the ML models can perform better than thecommonly used CPH model. The models were then explained using SHapleyAdaptive exPlanations (SHAP) values were the importance of the featureswere shown together with how the different features impacted the LOS. TheSHAP also showed how the GB handled the non linearity of the features betterthan the CPH model. The five most important features impacting the LOS wereif the patient received a scan at the ED, if the visited and emergency room,age, triage level and the label indicating what type of medical team seemsmost fit for the patient. This is clinical information that could be implementedto reduce the crowding through correct decision making. These results show that ML based survival analysis models can be used for further investigationregarding the logistic challenges that healthcare faces and could be furtherused for data analysis with production data in similar cases. The ML survivalanalysis pipeline can also be used for further analysis and can act as a first stepin order to pinpoint important information in the data that could be interestingfor deeper data analysis, making the process more efficient. / En av de största utmaningarna inom vården är trängsel på akuten som skaparstora ansträngninar inom vårdsystemet samt på dess resurser och kan varaorsaken till många negativa händelser. Det är ett välkänt problem där mycketforskning har gjorts och många lösningar har föreslagits men problemetär fortfarande olöst. Genom att analysera verklig data så kan komplexaproblem som trängsel på akuten bli bättre förklarade. För närvarande harfå tillämpningar av överlevnadsanalys applicerats på produktionsdata för attanalysera komplexiteten av logistiska problem. Syftet med denna avhandlingvar att tillämpa överlevnadsanalys genom avancerade maskininlärningsmetoderpå verklig data insamlat på ett svenskt sjukhust för att se hur vistelsens längdför patienten fram till inläggning påverkades av olika faktorer. Detta gjordesgenom att applicera överlevnadsnanalys på trängsel på akuten genom attanvända vistelsens längd som tid och beslutet om intagning eller utskrivningsom händelsen. Detta för att kunna analysera systemets kliniska komplexitetoch bidra till att påverka klinisk praxis och beslutsfattande.Genom att formulera forskningsfrågan som en överlevnadsanalys i kombinationmed maskininlärning kan den komplexitet och icke-linjäritet som logistikenpå akuten innebär studeras genom ett tidsperspektiv där vistelsens längdfungerar som ett nyckeltal. Detta gör det möjligt för forskaren att ävenstudera problemet från ett systemperspektiv och visar hur olika egenskaperoch situationer påverkar den tid som patienten bearbetas på akuten. Detta uppmärksammar eventuella problem och kan därför vara användbart för attförbättra det kliniska beslutsfattandet. Fem olika modeller: CPH, RSF, GB,XGB och DeepSurv användes och utvärderades med hjälp av C-index där GBvar den bäst presterande modellen med ett C-index på 0.7825 vilket visar attmaskininlärningsmetoderna kan prestera bättre än den klassiska och vanligtförekommande CPH modellen. Modellerna förklarades sedan med hjälp utavSHAP värden där vikten utav de olika variablerna visades tillsammmans med deras påverkan. SHAP visade även att GB modellen hanterade icke-linjäriteten bättre än CPH modellen. De fem viktigaste variablerna som påverkade vistelsens längd till intagning var om patienten blev scannad påakutmottagningen, om de blev mottagna i ett akutrum, ålder, triagenivå ochvilket medicinskt team som ansågs bäst lämpat för patienten. Detta är kliniskinformation som skulle kunna implementeras genom beslutsfattande för attminska trängseln på akuten. Dessa resultat visar att maskininlärningsmetoderför överlevnadsanalys kan användas för vidare undersökning angående de logistiska utmaningar som sjukvården står inför och kan även användas ytterligareför datanalys med produktionsdata i liknande fall. Processen med överlevnadsanalys och ML kan även användas för vidare analys och kan agera som ett förstasteg för att framhäva viktig information i datan som skulle vara intressant fördjupare data analys. Detta skulle kunna göra processen mer effektiv.

Denna studie undersöker samhällskunskapslärares professionella och didaktiska förhållningssätt till artificiell intelligens (AI) som verktyg i samhällskunskapsundervisningen. Fokus ligger på verktyget ChatGPT och hur detta kan användas i undervisningskontext. Syftet med studien är att öka kunskapen kring AI-verktyg i undervisningssammanhang och samla data om lärares åsikter kring dess användbarhet i utvecklingen av elevers förmågor och i relation till måluppfyllelse enligt läroplanen. En systematisk litteraturgenomgång genomfördes för att identifiera relevant tidigare forskning och utveckla inklusions- och exklusionskriterier. Gruppintervjuer genom ett informerande och utforskande seminarium genomfördes för att förstå lärares problemområden i relation till AI i undervisning. Detta ledde till teman av begrepp och problemområden som utgjorde grunden för en analys. Slutsatsen presenterar att ChatGPT har potential att användas som ett verktyg i undervisningen i samhällskunskap i svenska gymnasieskolor. Lärare kan använda verktyget för att effektivisera sitt arbete med att konstruera lektionsinnehåll, planera undervisning, anpassa kunskapsinnehåll till enskilda elever och på så vis stödja elevers måluppfyllelse i samhällskunskap. Verktygets funktionalitet förstås vara flexibelt och samtidigt visa förmåga att förstå innehållet i användarens budskap, generera text som är språkligt korrekt i sin struktur, erbjuda relevant information och besitta ett pedagogiskt värde baserat på användarens syfte. / This study examines social science teachers' pedagogical and didactic approaches to artificial intelligence (AI) as a tool in teaching civics. The focus is on ChatGPT and how it can be used in educational contexts. The purpose of the study is to increase knowledge about AI tools in teaching and to gather data on teachers' opinions on their usefulness in developing students' abilities and meeting curriculum goals. A systematic literature review was conducted to identify relevant the researchbase. Group interviews through an informative and exploratory seminar were conducted to understand teachers' problem areas in relation to AI in education. This led to themes of concepts and problem areas that formed the basis for an analysis. The conclusion presents that ChatGPT has the potential to be used as a tool in the teaching of social studies in Swedish high schools. Teachers can utilize the tool to streamline their work in constructing lesson content, planning instruction, adapting knowledge to individual students, and thus support students' achievement of goals in social studies. The tool's functionality is understood to be flexible while also demonstrating the ability to comprehend the content of the user's message, generate text that is linguistically correct in structure, provide relevant information, and possess educational value based on the user's purpose.

This PhD thesis provides design strategies to control changes produced in mountains places and landscapes following constructions of roads. Strategies are based on the activation of unexpressed potentialities in places, although compromised, characterized by presence of roads. With the term unexpressed potentialities we refer to functions, attitudes, uses which, during the process of road realization, have not found an appropriate design solution. Topic of the thesis is to demonstrate that these design gaps can be properly addressed by an architecture project, obtaining two results: create a link between places, landscapes and roads and consolidate the participation of architecture discipline in a field (roads production) in which, today in Italy, it is less integrated than others. Changes in mountain landscapes are characterized by morphology and orography of the territory crossed: the factor that most influences in this direction is the verticality of the space. This specificity is discussed in the thesis through the analysis of road segments, infrastructure nodes or other specific situations, divided according to the topography in which there are: high gradients, slope or bottom of valleys. Specific characteristics which correspond to the three different orographic situations are explained by an interpretative study of the cross section, highlighting the potentiality of the space related with its vertical dimension. Most study cases belong to the geographical area of Trentino Alto Adige, an Italian region characterized by mountain landscapes. Some study cases are taken from other Italian regions or known experiences of the international context. The proposed strategies are developed through study of architectural projects, joined by devices that interpret the vertical (overlapping, slope and difference in altitude) of the spaces, reproposable in cases of mountain road. All strategies can be applied at any step of road production, from concept to design to construction. In addition, and we assume that this is the most frequent case, can be applied ex post, when the road is built, intervening to change situations already in place.

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År 2024 upplevde Sverige längre väntetider och sämre tillgänglighet inom både primär- och specialiserad vård jämfört med andra länder. Detta ledde till ökat tryck på akutmottagningar då många patienter sökte sig dit för vård som annars kunde hanterats på ordinära mottagningar om tillräcklig personal funnits tillgänglig. Denna studie fokuserar på att undersöka patientflöden vid Danderyds sjukhus genom att identifiera flaskhalsar inom akutmottagningen. Studiens syfte var att hitta flaskhalsar som kan åtgärdas för att minska väntetiderna och förbättra resursanvändningen genom att använda matematiska modeller och diskret händelsesimulering. Analysen baseras på data insamlad under det första kvartalet för åren 2022, 2023 och 2024. Resultaten från simuleringarna visar kritiska statistiska mått som är avgörande för att förstå systemets kapacitet och prestanda under varierande belastningar. Dessa resultat belyser även nödvändigheten av resursallokering och förväntade väntetider för patienter. Studien bidrar inte bara till en bra förståelse av de nuvarande processerna utan presenterar även strategier för att effektivt hantera de utmaningar akutmottagningarna står inför. Slutsatserna diskuterar de teoretiska och praktiska implikationerna med betoning på hur simuleringarna kan användas för att utforska nya arbetsmetoder för akutmottagningar framöver. Denna forskning lägger grunden för framtida innovationer inom sjukvårdens arbetsflöden och resursallokering, vilket kan leda till förbättrad patientvård och effektivare sjukhusdrift. / In 2024, Sweden experienced longer wait times and reduced accessibility in both primary and specialized care compared to other countries. This led to increased pressure on emergency departments, as many patients sought care there that could have been managed at regular clinics if sufficient staff were available. This study focuses on examining patient flows at Danderyd Hospital by identifying bottlenecks within the emergency department. The aim of the study was to find bottlenecks that can be addressed to reduce wait times and improve resource utilization through the use of mathematical models and discrete event simulation. The analysis is based on data collected during the first quarter of the years 2022, 2023, and 2024. The results from the simulations reveal critical statistical measures that are essential for understanding the system's capacity and performance under varying loads. These results also highlight the need for resource allocation and expected wait times for patients. The study not only contributes to a better understanding of the current processes but also presents strategies for effectively addressing the challenges faced by emergency departments. The conclusions discuss the theoretical and practical implications, emphasizing how the simulations can be used to explore new working methods for emergency departments in the future. This research lays the foundation for future innovations in healthcare workflows and resource allocation, which can lead to improved patient care and more efficient hospital operations.

Photoelectrodes and photovoltaic devices have been prepared via multiple thin film deposition methods. Aerosol assisted chemical vapour deposition (AACVD), electrodeposition (ED), chemical bath deposition (CBD) and doctor blade technique (DB) have been used to deposit binary and ternary metal oxide films on FTO glass substrates. The prepared thin films were characterised by a combination of SEM (Scanning Electron Microscopy), powder X-ray diffraction, mechanical strength tests and photochemical measurements. Nickel oxide (NiO) thin films prepared by AACVD were determined to have good mechanical strength . with a photocurrent of 7.6 μA cm-2 at 0 V and an onset potential of about 0.10 V. This contrasted with the dark current density of 0.3 μA cm-2 at 0 V. These NiO samples have very high porosity with crystalline columns evidenced by SEM. In comparison with the AACVD methodology, NiO films prepared using a combination of ED and DB show good mechanical strength but a higher photocurrent of 24 μA cm-2 at 0 V and an onset potential of about 0.10 V with a significantly greater dark current density of 7 μA cm-2 at 0 V. The characteristic features shown in the SEM are smaller pores compared to the AACVD method. Copper (II) oxide (CuO) and copper (I) oxide (Cu2O) films were fabricated by AACVD by varying the annealing temperature between 100-325°C in air using a fixed annealing time of 30 min. It was shown by photocurrent density (J-V) measurements that CuO produced at 325 °C was most stable and provided the highest photocurrent of 173 μA cm-2 at 0 V with an onset potential of about 0.23 V. The alignment of zinc oxide (ZnO) nano-rods and nano-tubes fabricated by CBD have been shown to be strongly affected by the seed layer on the FTO substrate. SEM images showed that AACVD provided the best seed layer for aligning the growth of the nano-rods perpendicular to the surface. Nano-rods were successfully altered into nano-tubes using a potassium chloride bath etching method. NiO prepared by both AACVD and the combined ED/DB method were sensitized to absorb more of the solar spectrum using AACVD to deposit CuO over the NiO. A large increase in the photocurrent was observed for the p-type photoelectrode. These p-type photoelectrode showed a photocurrent density of approximately 100 μA cm-2 at 0 V and an onset potential of 0.3 V. This photocathode was then used as a base to produce a solid state p-type solar cell. For the construction of the solid state solar cells several n-type semiconductors were used, these were ZnO, WO3 and BiVO4. WO3 and BiVO4 were successfully produced with BiVO4 proving to be the optimum choice. This cell was then studied more in depth and optimised by controlling the thickness of each layer and annealing temperatures. The best solid state solar cell produced had a Jsc of 0.541 μA cm-2 (541 nA) and a Voc of 0.14 V, TX146 made up of NiO 20 min, CuFe2O4 50 min, CuO 10 min, BiVO4 27 min, using AACVD and then annealed for 30 min at 600°C.

Dans le cadre d’une étude comparatiste, ce travail vise à analyser, en les rapprochant pour la première fois, les univers créatifs de l’écrivain italien Dino Buzzati (1906 – 1972) et de son confrère français Claude Louis-Combet (1932 –), selon la dualité chair et âme, qui est une constante de leur oeuvre respective. Les deux auteurs, par le biais de l’autobiographie romancée, de la réélaboration mythique, comme d’une vision originale de l’art figuratif, ont exprimé une sensibilité et un imaginaire étonnamment proches. Ils auront été accompagnés par des figures légendaires et des amis artistes, afin de guider le lecteur vers la dimension fantasmatique et mystique de son inconscient. / As part of a comparative study, this work aims to analyze, by bringing them together for the first time, the creative worlds of the Italian writer Dino Buzzati (1906 – 1972) and his French colleague Claude Louis-Combet (1932 –), according to the flesh and soul duality, which is a constant in their works. Both authors, through the fictionalized autobiography, the mythology reworking, as an original vision of figurative art, expressed sensitivity and imagination surprisingly close. They have been accompanied by legendary figures and fellow artists, to guide the reader into the mystical and fantasy dimension of his unconscious.

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Orientador: Rubén Augusto Romero Lázaro / Resumo: A análise de sistemas altamente complexos quando e analizado o problema de planejamento de expansão de redes de transmissão de longo prazo, é o foco principal deste trabalho. Os modelos e metodos propostos são aplicados ao problema de planejamento estático tradicional, que é um problema de otimização matemática classificado como NP-completo, não-linear inteiro misto. O qual envolve no investimento, variáveis operacionais contínuas e variáveis inteiras. O comportamento normal de cada sistema pode conter informação essencial para a criação de novos métodos, como os planos de corte baseados em cortes de diferença de ângulos para problemas de grande escala, o que é a base é o ponto de partida deste trabalho, derivando em desigualdades válidas é ciclos críticos. Os cortes angulares básicos reduzem o espaço de busca do problema e o tempo total de cálculo deste problema, enquanto ao método de inequações válidas que pode ser usado para fornecer limites inferiores sólidos no investimento ótimo do planejamento de transmissão, já que a diferença entre o modelo DC (modelo exato) e o modelo de transporte (modelo mais relaxado) são as restrições angulares. Os ciclos críticos têm sido desenvolvidos para melhoraralguns dos modelos tradicionais do problemas de planejamento da expansão da rede de transmissão de longo prazo. A razão por trás disso é a ausência da segunda lei de Kirchhoff, que completa a representação do sistema, mas aumenta a complexidade. Para resolver os problemas resultantes... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The analysis of highly complex systems when solving the long-term transmission network expansion planning problem is the main focus of this work. The proposed improved models and methodology are applied to the traditionalstatic planning problem, which is a mathematical optimization problem classified as NP-complete and mixed-integer nonlinear problem. It involves continuousoperating variables and integer investment variables. The normal behavior of each system can be shown essential information to the creation of new methods, as the cutting-planes based in bus-angle difference cuts for large-scale problems which were the starting point of this work, deriving in valid inequalities and critic cycles. The angular cuts aim to reduce the search space of the problem and the total computation time of this NP-hard problem as for the valid inequalities methodthat can be used to provide strong lower bounds on the optimal investment of the transmissionplanning, since the difference between the DC model (exact model) and the transport model (more relaxed model) are the angular constraints. Critic cycles has been develop in order to improve some of the traditional long-term transmission network expansion planning problem models. The reason behind it is the absence of second Kirchhoff’s law which completes the representationof the system, but increase the complexity. In order to solve the resulting problems, this work uses the modeling language AMPL with the solver CPLEX. In test systems w... (Complete abstract click electronic access below) / Doutor