As the autonomous vehicles are getting clo-ser to commercial roll out, the challenges for the developersof the software are getting more complex. One challenge thedevelopers are facing is the interaction between humans andautonomous vehicles in traffic.Such situation requires a hugeamount of data to in order to design and proof test autonomoussystem than can handle complex interactions with humans.Such data can not be collected in real traffic situations withoutcompromising the safety of the human counterparts, thereforesimulations will be necessary. Since human driving behavior ishard to predict, these simulations need human interaction inorder to get valid data of human behaviour.The purpose of thisproject is to develop a driving interface and then evaluate theusers experience in an experiment. To do this we have designedand implemented steering,braking and acceleration on a userinterface for a simulator used in autonomous driving researchcalled Car Learning to Act (CARLA) at the Smart Mobility Lab(SML) at KTH. We have implemented two driving simulatoruser interfaces, with different levels of information feedbackto the user. To evaluate the developed user interface, a surveywas designed to measure how intuitive the driving experiencewas while also comparing it to the original setup at SML. Thesurvey showed that the driving experience was more intuitivewith the two developed user interfaces and that 60% would feelcomfortable using the new systems on a real vehicle in traffic. / Allteftersom autonoma bilar kommer närmare kommersiell lansering blir utmaningarna för utvecklarna av mjukvaran mer komplexa. En utmaning som utvecklarna står inför är interaktionen mellan autonoma bilar och människor i och utanför trafiken. Dessa situationer kommer kräva en stor mängd data för att säkerhetställa att autonoma bilar kommer kunna agera optimalt. För att inhämta sådan data utan att riskera säkerheten för alla ute i trafiken kommer simulatorer behövas. Eftersom vi inte kan förutspå mänskligt beteende kommer industrin behöva använda mänskliga förare i dessa simulatorer för att få realistiska resultat. Syftet med detta projekt är att utveckla ett förargränssnitt för människor och sedan utvärdera autenticiten av upplevelsen från ett mänskligt perspektiv. Genom att implementera olika bilmekanismer så som styrning, inbromsning, accelerationen och retardation i en simulator för autonom bil forskning, Car Learning To Act(CARLA) i Smart Mobility Lab(SML) på KTH. Vi implementerade två användargränssnitt med olika nivåer av informations återkoppling till användaren. För att utvärdera användargränssnitten utformades ett frågeformulär för att mäta hur intuitivt körupplevelsen var och samtidigt jämföra med det originella användargränssnittet i SML. Undersökningen visade att körupplevelsen var mer intuitiv med det två utvecklade användargränssnitten och att 60% skulle vara bekväma med att använda ett utav dessa system för att styra ett riktigt fordon i trafik. / Kandidatexjobb i elektroteknik 2020, KTH, Stockholm

Recent advances in electrical engineering have let the realization of small size electrical systems for in-body applications. Today’s hybrid implantable systems combine radio frequency and biosensor technologies. The biosensors are intended for wireless medical monitoring of the physiological parameters such as glucose, pressure, temperature etc. Enabling wireless communication with these biosensors is vital to allow continuous monitoring of the patients over a distance via radio frequency (RF) technology. Because the implantable antennas provide communication between the implanted device and the external environment, their efficient design is vital for overall system reliability. However, antenna design for implantable RF systems is a quite challenging problem due to antenna miniaturization, biocompatibility with the body’s physiology, high losses in the tissue, impedance matching, and low-power requirements. This dissertation presents design and measurement techniques of implantable antennas for medical wireless telemetry. A robust stochastic evolutionary optimization method, particle swarm optimization (PSO), is combined with an in-house finite-element boundary-integral (FE-BI) electromagnetic simulation code to design optimum implantable antennas using topology optimization. The antenna geometric parameters are optimized by PSO, and a fitness function is computed by FE-BI simulations to evaluate the performance of each candidate solution. For validating the robustness of the algorithm, in-vitro and in-vivo measurement techniques are also introduced. To illustrate this design methodology, two implantable antennas for wireless telemetry applications are considered. First, a small-size dual medical implant communications service (MICS) (402 MHz – 405 MHz) and industrial, scientific, and medical (ISM) (2.4 GHz – 2.48 GHz) band implantable antenna for human body is designed, followed by a dual band implantable antenna operating also in MICS and ISM bands for animal studies. In order to test the designed antennas in-vitro, materials mimicking the electrical properties of human and rat skins are developed. The optimized antennas are fabricated and measured in the materials. Moreover, the second antenna is in-vivo tested to observe the effects of the live tissue on the antenna performance. Simulation and measurement results regarding antenna parameters of the designed antennas such as return loss and radiation pattern are given and discussed in detail. The development details of the tissue-mimicking materials are also presented.

The extensive and sometimes incorrect and noncompliant use of various types of antimicrobial agents has accelerated the development of antimicrobial resistance (AMR). In fact, AMR has become one of the greatest global threat to human health in this era. The broad-spectrum antibiotics aminoglycosides (AGs) display excellent potency against most Gram-negative bacteria, mycobacteria, and some Gram-positive bacteria, such as Staphylococcus aureus. The AG antibiotics amikacin, gentamicin, kanamycin, and tobramycin are still commonly prescribed in the U.S.A. for the treatment of serious infections. Unfortunately, bacteria evolve to acquire resistance to AGs via four different mechanisms: i) changing in membrane permeability to resist drugs from entering, ii) upregulating efflux pumps for active removal of intracellular AGs, iii) modifying the antimicrobial target(s) to prevent drugs binding to their targets, and iv) acquiring resistance enzymes to chemically inactivate the compounds. Amongst all, the acquisition of resistance enzymes, AG-modifying enzymes (AMEs), is the most common resistance mechanism identified. Depending on the chemistry each enzyme catalyzes, AMEs can be further divided into AG N-acetyltransferases (AACs), AG O-phosphotransferases (APHs), and AG O-nucleotidyltransferases. To overcome AME-related resistance, we need to better understand these resistance enzymes and further seek ways to either escape or inhibit their actions. In this dissertation, I summarized my efforts to characterize the AAC(6') domain and its mutant enzymes from a bifunctional AME, AAC(6')-Ie/APH(2")-Ia as well as another common AME, APH(3')-IIa. I also explained my attempt to inhibit the action of various AAC enzymes using metal salts. In an effort to explore the current resistance epidemic, I evaluated the resistance against carbapenem and AG antibiotics and the correlation between the resistance profiles and the AME genes in a collection of 122 Pseudomonas aeruginosa clinical isolates obtained from the University of Kentucky Hospital System. Besides tackling the resistance mechanisms in bacteria, I have also attempted to explore a new antifungal option by repurposing an existing antipsychotic drug, bromperidol, and a panel of its derivatives into a combination therapy with the azole antifungals against a variety of pathogenic yeasts and filamentous fungi.

Aim: The aim of this work was to broaden the understating of the role of parental engagement and learning materials at home, in promoting high cognitive and social emotional development. The study assessed the connection between maternal and paternal engagement, having 3 or more books and 2 or more types of playthings, towards the cognitive and social-emotional development of children. Methods: Data from the Multiple Indicator Cluster Surveys (MICS) was used, involving 2517 children in Zimbabwe. Unadjusted logistic regression was conducted to assess the possible confounders. Logistic regression was performed between parental engagement, children having 3 or more books and 2 or more types of playthings, towards the outcome of interest. Results: The results indicate that 91% of the children acquired high cognitive development and 63.4% social emotional. There has not been a significant association between maternal engagement and children’s cognitive or social-emotional development. Similarly, no correlation was found between paternal engagement and children’s development. Nevertheless, households having 3 or more books, reported increased odds of children having high cognitive development and lower odds of social-emotional development. Similarly, children with 2 or more types of playthings, depicted a positive association for social-emotional growth, whereas cognitive development decreased further. Conclusion: The association between having 3 or more books and 2 or more types of playthings remained significant, although parental engagement was insignificant. Future research on parenting practices in different cultural contexts is suggested, concerning the developmental status of children. In addition, more developmental, age-related assessment items are needed.