Crashes resulting from automobiles running a red light are typically severe in nature. One way to try to reduce the number and severity of these types of crashes is by increasing the red clearance interval of a traffic signal. In Portland, Oregon, eight intersections received a variety of treatments including red extensions. Determining which treatment had what effect can be difficult to weed out. Using a combination of crash analysis and a model simulating an intersection with red extensions, this paper describes the estimated impact of red light running intersection upgrades and red extensions on crashes. By performing a variety of before and after crash analysis, a reduction of angle crashes after treatments was detected, with a crash modification factor of 0.64 +/- 0.28 using the Empirical-Bayes method. Output from the simple simulation also suggest that red light running crashes can be reduced with red extension technology and confirms crash modification values determined from the Empirical-Bayes method.

Blood glucose (BG) prediction and classification plays big role in diabetic patients' daily lives. Based on International Diabetes Federation (IDF) in 2019, 463 million people are diabetic globally and the projection by 2045 is that the number will rise to 700 million people. Continuous glucose monitor (CGM) systems assist diabetic patients daily, by alerting them about their BG levels fluctuations continuously. The history of CGM systems started in 1999, when the Food and Drug Administration (FDA) approved the first CGM system, until nowadays where the developments of the system's accurate reading and delay on reporting are continuously improving. CGM systems are key elements in closed-loop systems, that are using BG monitoring in order to calculate and deliver with the patient's supervision the needed insulin to the patient automatically. Data quality and the feature variation are essential for CGM systems, therefore many studies are being conducted in order to support the developments and improvements of CGM systems and diabetics daily lives. This thesis aims to show that physiological signals retrieved from various sensors, can assist the classification and prediction of BG levels and more specifically that breathing rate can enhance the accuracy of CGM systems for diabetic patients and also healthy individuals. The results showed that physiological data can improve the accuracy of prediction and classification of BG levels and improve the performance of CGM systems during classification and prediction tasks. Finally, future improvements could include the use of predictive horizon (PH) regarding the data and also the selection and use of different models.

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Soil fauna provides processes of crucial importance for ecosystem functions, but our ability to observe their actions often depend on destructive methods where the integrity of the studied environment (the soil) is compromised. In this study, I develop and test a new generation of environmental monitoring tools that utilize vibrations made by soil macrofauna to inform about their performance and health. Three hypotheses were tested on forest ants (Formica sp.): (i) vibrations on a naturally occurring substrate can be used to measure the activity of ants, (ii) the vibrational signature of ants can inform us about the ants’ health, and (iii) behavior (locomotory activity, foraging etc.) of ants is correlated to specific vibrational signal characteristics. Vibrational signals from ant sub-populations (5 individuals/sample) were recorded on natural substrates (leaves) before and after exposure to sub-lethal levels of a contaminant with known negative effects on ants (imidacloprid). Activity was successfully detected from the inferred vibration oscillograms. However, neither the number of vibrational signals captured, or the signal characteristics changed after imidacloprid exposure, indicating that either the exposure was too low to generate a change in behavior or that the technique was unable to detect subtle changes in behavior. Signals of short duration and amplitude were generated by locomotory activity, but their intensity was dependent on the distance to the vibrometers laser focus point. Longer signal segments were either continuous, random, or rhythmic in their distribution. I suggest that these signals are a result of methodological artifacts, movement of multiple ants, and stridulation/drumming on the substrate, respectively. My findings suggest that this advanced monitoring tool is sensitive enough to capture activity from only a few ants, but the characteristics and number of captured signals are strongly affected by the measured substrate

Non-stationary signals, particularly frequency modulated (FM) signals which arecharacterized by their time-varying instantaneous frequencies (IFs), are fundamental to radar, sonar, radio astronomy, biomedical applications, image processing, speech processing, and wireless communications. Time-frequency (TF) analyses of such signals provide two-dimensional mapping of time-domain signals, and thus are regarded as the most preferred technique for detection, parameter estimation, analysis and utilization of such signals. In practice, these signals are often received with compressed measurements as a result of either missing samples, irregular samplings, or intentional under-sampling of the signals. These compressed measurements induce undesired noise-like artifacts in the TF representations (TFRs) of such signals. Compared to random missing data, burst missing samples present a more realistic, yet a more challenging, scenario for signal detection and parameter estimation through robust TFRs. In this dissertation, we investigated the effects of burst missing samples on different joint-variable domain representations in detail. Conventional TFRs are not designed to deal with such compressed observations. On the other hand, sparsity of such non-stationary signals in the TF domain facilitates utilization of sparse reconstruction-based methods. The limitations of conventional TF approaches and the sparsity of non-stationary signals in TF domain motivated us to develop effective TF analysis techniques that enable improved IF estimation of such signals with high resolution, mitigate undesired effects of cross terms and artifacts and achieve highly concentrated robust TFRs, which is the goal of this dissertation. In this dissertation, we developed several TF analysis techniques that achieved the aforementioned objectives. The developed methods are mainly classified into two three broad categories: iterative missing data recovery, adaptive local filtering based TF approach, and signal stationarization-based approaches. In the first category, we recovered the missing data in the instantaneous auto-correlation function (IAF) domain in conjunction with signal-adaptive TF kernels that are adopted to mitigate undesired cross-terms and preserve desired auto-terms. In these approaches, we took advantage of the fact that such non-stationary signals become stationary in the IAF domain at each time instant. In the second category, we developed a novel adaptive local filtering-based TF approach that involves local peak detection and filtering of TFRs within a window of a specified length at each time instant. The threshold for each local TF segment is adapted based on the local maximum values of the signal within that segment. This approach offers low-complexity, and is particularly useful for multi-component signals with distinct amplitude levels. Finally, we developed knowledge-based TFRs based on signal stationarization and demonstrated the effectiveness of the proposed TF techniques in high-resolution Doppler analysis of multipath over-the-horizon radar (OTHR) signals. This is an effective technique that enables improved target parameter estimation in OTHR operations. However, due to high proximity of these Doppler signatures in TF domain, their separation poses a challenging problem. By utilizing signal self-stationarization and ensuring IF continuity, the developed approaches show excellent performance to handle multiple signal components with variations in their amplitude levels. / Electrical and Computer Engineering

The potential for high spatio-temporal resolution microwave measurements has urged the adoption of the signals of opportunity (SoOp) passive radar technique for use in remote sensing. Recent trends in particular target highly complex remote sensing problems such as root-zone soil moisture and snow water equivalent. This dissertation explores the continued open-sourcing of the SoOp coherent bistatic scattering model (SCoBi) and its use in soil moisture sensing applications. Starting from ground-based applications, the feasibility of root-zone soil moisture remote sensing is assessed using available SoOp resources below L-band. A modularized, spaceborne model is then developed to simulate land-surface scattering and delay-Doppler maps over the available spectrum of SoOp resources. The simulation tools are intended to provide insights for future spaceborne modeling pursuits.

[pt] vidências de validade da Phone Screening Interview (PSI-TEA) para rastreio do Transtorno do Espectro Autista em um serviço de psiquiatria infanto-juvenil. O estudo teve como objetivo ampliar a validação da Phone Screening Interview (PSI-TEA), uma triagem telefônica para rastreio de sintomas de TEA. No primeiro estudo, foi verificada a confiabilidade comparando as médias da pontuação total da aplicação presencial (4,03) e telefônica (3,95), sem diferença significativa (t(59)= -0,52; p= .600). A análise de concordância entre os itens apontou três itens com valores muito baixos, levando à modificação de algumas perguntas. Diante desta discordância, foi verificado que a ordem de aplicação das entrevistas não impactaria nos resultados, com fortes correlações (r=.822 e r= .825). No segundo estudo, foi investigado o poder discriminativo da PSI para diferenciar crianças com e sem diagnóstico de TEA, apresentando sensibilidade de 1,00, especificidade 0,52. O instrumento mostrou-se confiável, podendo ser utilizado de forma remota, por diferentes avaliadores, sem impacto em sua eficiência na detecção de sintomas de TEA quando comparada a sua forma presencial. / [en] The study aimed to extend the validation of the Phone Screening Interview (PSI-TEA), a telephone screening for symptoms of ASD. In the first study, reliability was verified by comparing the mean total scores of the face-to-face (4.03) and telephone (3.95) application, with no significant difference (t(59)= -0.52; p= .600). . The agreement analysis between the items indicated three items with lower values, leading to the modification of some questions. In view of this disagreement, it was verified that the order in which the interviews were applied would not impact the results, with strong correlations (r=.822 and r= .825). In the second study, the discriminative power of the PSI to differentiate between children with and without a diagnosis of ASD was investigated, presenting a sensitivity of 0.91, specificity 0.73. The instrument proved to be reliable and can be used remotely, by different evaluators, with no impact on its efficiency in detecting ASD symptoms when compared to its face-to-face form.

Bakgrund - Den finansiella sektorn har en viktig funktion i omställningen mot ett merhållbart samhälle, där institutionella investerare genom hållbara investeringar kan ha storbetydelse för den hållbara utvecklingen. Samtidigt har hållbarhet också fått en störrebetydelse för institutionella investerare i deras beslut om investeringar. Att göra enhållbarhetsbedömning av potentiella investeringsobjekt har därför blivit en vanligtförekommande handling under institutionella investerares investeringsbeslutsprocess. Syfte - Syftet med rapporten är att skapa förståelse för hur investerare i svenskainvestmentbolag och riskkapitalbolag bedömer företagets hållbarhet inför investeringsbeslut. Metod - Studiens empiriska material har insamlats genom kvalitativa semistruktureradeintervjuer med investerare i svenska investmentbolag och riskkapitalbolag. Därefter har entematisk analysmetod tillämpats för att identifiera, beskriva och analysera teman i detinsamlade empiriska materialet. Resultat - Studiens resultat har visat att det finns ett flertal hållbarhetsrelaterade faktorer somtas i beaktande vid investerares hållbarhetsbedömning av företag. Dessa faktorer är (1) Hållbarhetsengagemang hos portföljföretagets företrädare, (2) Portföljföretagets medvetenhetinom hållbarhetsområdet, (3) Portföljföretagets strategi kopplat till hållbarhet, (4) Portföljföretagets hållbarhetsrelaterade kommunikation, (5) Portföljföretagets internakompetens inom hållbarhetsområdet, (6) Hållbarhetsfunktionens placering i portföljföretaget, (7) Portföljföretagets egen riskbedömning med avseende på hållbarhet och (8) Efterföljandeav hållbarhetsrelaterade regleringar, internationella riktlinjer och certifieringar. Vidare harframkommit att investerare vid bedömningen av företagets hållbarhet tar hänsyn till olikaobjekts- och kontextberoende faktorer, såsom företagets ålder, mognad, storlek, land,branschtillhörighet och företagets riskfylldhet. Slutligen har studiens resultat visat attbetydelsen av hållbarhet i investerares investeringsbeslutsprocess i hög utsträckning skiljersig beroende på investerarens investeringshorisont, investeringsstrategi och tillvägagångssättför hållbara investeringar. Forskningsbegränsningar - Att den empiriska studien endast innefattar investerare i svenskainvestmentbolag och riskkapitalbolag, kan ses som en begränsning. Författarna gjorde dockett aktivt val att inrikta studien mot den svenska kontexten, vilket därmed innebär att deegenskaper som kännetecknar den svenska finansmarknaden, måste tas i beaktande i studiensresultat. Nyckelord - Institutionella investerare, Investeringsbeslutsprocess, Hållbara Investeringar,Signalering, Hållbarhetssignaler / Background - The financial sector has an important function in the transition towards a moresustainable society, where institutional investors through sustainable investments can have agreat impact on sustainable development. Sustainability has also become more important forinstitutional investors in their investment decisions. Making a sustainability assessment ofpotential investment objects has therefore become a common act during institutionalinvestors’ investment decision-making process. Purpose - The purpose of the report is to create an understanding of how investors in Swedish investment companies and venture capital companies assess the company’ssustainability before investment decisions. Method - The study’s empirical material has been collected through qualitativesemi-structured interviews with investors in Swedish investment companies and venturecapital companies. Further, a thematic analysis method has been applied to identify, describeand analyze themes in the collected empirical material. Findings - The results of the study have shown that there are several sustainability-relatedfactors that are taken into account when investors assess the sustainability of companies.These factors are (1) Sustainability commitment of the portfolio company’s representatives,(2) The awareness in the area of sustainability within the portfolio company, (3) The strategylinked to sustainability within the portfolio company, (4) The sustainability-relatedcommunication within the portfolio company, (5) The internal competence in the area ofsustainability within the portfolio company, (6) The location of the sustainability in theportfolio company, (7) The portfolio company’s own risk assessment with regard tosustainability and (8) Following sustainability-related regulations, international guidelinesand certifications. Furthermore, it has emerged that when assessing the company’ssustainability, investors take into account various object- and context-dependent factors, suchas the company’s age, maturity, size, country, industry and the company’s riskiness. Finally,the results of the study have shown that the importance of sustainability in investors’investment decision-making process differs to a large extent depending on the investor’sinvestment horizon, investment strategy and approach to sustainable investment. Research limitations - The fact that the empirical study only includes investors in Swedishinvestment companies and venture capital companies can be seen as a limitation. However,the authors made an active choice to focus the study on the Swedish context, which thusmeans that the characteristics that characterize the Swedish financial market must be takeninto account in the study's results. Keywords - Institutional Investors, Investment Decision Process, Sustainable Investments,Signaling, Sustainability Signals

Metacognitive therapy (MCT) has been shown to be a promising treatment approach for obsessive-compulsive disorder (OCD). The changeability of metacognitions by (metacognitive) treatment and its relevance to treatment outcome is, however, still unclear. The current study investigates, (1) if treatment with MCT or exposure and response prevention (ERP) in a randomized-controlled pilot trial (n = 24 patients with OCD) changes OCD-specific metacognitions of thought fusion beliefs, beliefs about rituals and stop signals, and (2) if these changes are relevant for the treatment outcome in terms of patient- and therapist-rated OCD symptoms. ANOVA with pretest, posttest and follow-up scores could show that all three metacognitions significantly decreased during both treatments. Regarding thought fusion beliefs, a significant interaction effect indicated a higher decrease after MCT than ERP treatment. In hierarchical regression analyses, changes in stop signals from pre- to post-treatment significantly predicted patient-rating OCD symptoms at post-treatment and follow-up at 3 months after treatment. These changes were even predictive of post-treatment outcome after controlling for general metacognitions and dysfunctional cognitive beliefs. These findings support the assumption thatmetacognitions can change during both treatments and that changes in stop signals might be relevant for the treatment outcome on the symptom level in OCD.