Why is it that we humans have a tendency to construct transcendental entities? That is one of the big questions the scientific discipline Cognitive Science of Religion is trying to answer. In order to gain validation for the concepts used by this discipline neural correlates are needed. The aim of the present work is to investigate the concepts Hypersensitive Agency Detection Device ((H)ADD) and Theory of Mind (ToM) both in psychological, cognitive and neural aspects to see if those concepts are enough to explain the human tendencies to construct transcendental entities. This work is developed as philosophical a literature study and uses literature from the scientific disciplines of cognitive neuroscience, cognitive science of religion, cognitive science, neurotheology, psychology of religion and philosophy of religion. This means that the present work is interdisciplinary and stands on a bridge between the theoretical and empirical sciences. A word of caution: Regardless the findings this work presents, the explanatory value is limited as it is a theoretical study in an empirical scientific field. It is when the findings in this work are tested empirically that the findings sustainability are decided.              What this work shows is that neural correlates for ToM already exist in the form of the Mirror Neuron-Theory (MNT), but it is problematic because it can not show how higher orders of representations are possible. No scientific data about neural correlates to (H)ADD has been found for this study, but here the amygdala may play a prominent role. Furthermore this work shows that (H)ADD and ToM is not enough to explain why humans have a tendency to construct transcendental entities. We are in need of peripheral cognitive mechanisms such as intuitive knowledge modules, ontological categories, teleological thinking, our drive to seek causal connections and our ability for pattern recognition.

The personalization of online advertising has now become a necessity for marketing agencies. The tracking technologies such as third-party cookies gives advertisers the ability to recognize internet users across different websites, to understand their behavior and to assess their needs and their tastes. The amount of created data and interactions leads to the creation of a large cross-device identity graph that links different identifiers such as emails to different devices used on different networks. Over time, strongly connected components appear in this graph, too large to represent only the identifiers or devices of only one person or household. The aims of this project is to partition these components according to the structure of the graph and the features associated to the edges without separating identifiers used by a same person. Subsequent to this, the size reduction of these components leads to the isolation of individuals and the identifiers associated to them. This thesis presents the design of a bipartite graph from the available data, the implementation of different community detection graphs adapted to this specific case and different validation methods designed to assess the quality of our partition. Different graph metrics are then used to compare the outputs of the algorithms and we will observe how the adaptation of the algorithm to the bipartite case can lead to better results. / Anpassningen av onlineannonsering har nu blivit en nödvändighet för marknadsföringsbyråer. Spårningstekniken som cookies från tredje part ger annonsörer möjlighet att känna igen internetanvändare på olika webbplatser, för att förstå deras beteende och för att bedöma deras behov och deras smak. Mängden skapade data och interaktioner leder till skapandet av en stor identitetsgrafik för flera enheter som länkar olika identifierare, t.ex. e-postmeddelanden till olika enheter som används i olika nätverk. Över tiden visas starkt anslutna komponenter i det här diagrammet, för stora för att endast representera identifierare eller enheter av endast en person eller hushåll. Syftet med detta projekt är att partitionera dessa komponenter enligt grafens struktur och de egenskaper som är knutna till kanterna utan att separera identifierare som används av samma person. Efter detta leder storleksreduktionen av dessa komponenter till isoleringen av individer och de identifierare som är associerade med dem. Denna avhandling presenterar utformningen av en bifogad graf från tillgängliga data, genomförandet av olika samhällsdetekteringskurvor anpassade till detta specifika fall och olika valideringsmetoder som är utformade för att bedöma kvaliteten på vår partition. Olika grafvärden används då för att jämföra algoritmens utgångar och vi kommer att observera hur anpassningen av algoritmen till tvåpartsfallet kan leda till bättre resultat.

The protection of the electrical device is provided to prevent the electric shocks, protect the equipment and prevent a damage caused by electrical faults. The current protection for a small fault currents need not always have an effect. At the serious faults the current protections never work. The new type of device to protect against damage caused by electrical failure is an arc protection. The arc protection switches off safely all types of fault arc in different sizes. This work verifies its correct functionality in the case of electric circuit with deceptive signals from LED light sources. The output of the work is the measurement of the switching current of the LED light sources. The work is remarkable thanks the number of measurement for individual angles of switching on which have statistical meaning.

<p>Swift recognition of disease-causing pathogens at the point-of-care enables life-saving treatment and infection control. However, current rapid diagnostic devices often fail to detect the low concentrations of pathogens present in the early stages of infection, causing delayed and even incorrect treatments. Rapid diagnostics that require multiple steps and/or elevated temperatures to perform have a number of barriers to use at the point-of-care and in the field, and despite efforts to simplify these platforms for ease of use, many still require diagnostic-specific training for the healthcare professionals who use them. Most nucleic acid amplification assays require hours to perform in a sterile laboratory setting that may be still more hours from a patient’s bedside or not at all feasible for transport in remote or low-resourced areas. The cold-chain storage of reagents, multistep sample preparation, and costly instrumentation required to analyze samples has prohibited many nucleic acid detection and antibody-based assays from reaching the point-of-care. There remains a critical need to bring rapid and accessible pathogen identification technologies that determine disease status and ensure effective treatment out of the laboratory.</p> <p>Paper-based diagnostics have emerged as a portable platform for antigen and nucleic acid detection of pathogens but are often limited by their imperfect control of reagent incubation, multiple complex steps, and inconsistent false positive results. Here, I have developed mechanisms to economically improve thermal incubations, automate dried reagent flow for multistep assays, and specifically detect pathogenic antigens while improving final output sensitivity on paper-based devices. First, I characterize miniaturized inkjet printed joule-heaters (microheaters) that enable thermal control for pathogen lysis and nucleic acid amplification incubation on a low-cost paper-based device. Next, I explore 2-Dimensional Paper Networks as a means to automate multistep visual enhancement reactions with dried reagents to increase the sensitivity and readability of nucleic acid detection with paper-based devices. Lastly, I aim to create a novel Reverse-Transcription Recombinase Polymerase Reaction mechanism to amplify and detect a specific region of the Spike protein domain of SARS-CoV-2. This will allow the rapid detection of SARS-CoV-2 infections to aid in managing the current COVID-19 pandemic. In the future, these tools could be integrated into a rapid diagnostic test for SARS-CoV-2 and other pathogens, ultimately improving the accessibility and sensitivity of rapid diagnostics on multiple fronts.</p>

This thesis is on Cognitive Science of Religion (CSR) and its relevance for the rationality of religious beliefs. An epistemical model for rationality is developed according to which: a person (or group of persons) is rational to hold a certain belief a) if this belief can be assumed to have been generated by one or more reliable cognitive mechanisms, b) applies whether or not she is aware of what these mechanisms are, but c) only as long as it does not exist or arise some reasons (defeaters) to question the belief; if they occur, she must d) reflect on it and find other reasons or grounds to hold the belief in question.      Two different positions are examined, namely: 1) negative relevance: the findings and theories in CSR undermines the rationality of religious beliefs; 2) positive relevance: religious beliefs need not be irrational in the light of CSR, in fact CSR may actually support the rationality of religious beliefs.      Two lines of argument can be distinguished among those who argue for a negative relevance: a) the natural explanations that are provided by CSR are preferable; and b) religious beliefs are irrational because they are caused by unreliable cognitive mechanisms.      Among those who argue for positive relevance two arguments can be distinguised: a) religious beliefs seem to come naturally to humans and therefore are probably true; and b) CSR confirms empirically that we are equipped with a "divine mechanism" that there are reasons to believe is reliable.      The conclusions are: CSR has negative relevance to beliefs in "finite supernatural agency", but not for the faith of "infinite supernatural agency". First, the first type of beliefs is easier to explain by being generated by unreliable cognitive mechanisms; secondly they are difficult to integrate with what we otherwise know about the world. A category that falls outside the scope of CSR and thus not even potentially can be affected, is beliefs in "supernatural non-agency". / The Impact of Religion – Challenges for Society, Law and Democracy

For unmanned aircraft systems to gain full access to the National Airspace System (NAS), they must have the capability to detect and avoid other aircraft. This research focuses on the development of a detect-and-avoid (DAA) system for small unmanned aircraft systems. To safely avoid another aircraft, an unmanned aircraft must detect the intruder aircraft with ample time and distance. Two analytical methods for finding the minimum detection range needed are described. The first method, time-based geometric velocity vectors (TGVV), includes the bank-angle dynamics of the ownship while the second, geometric velocity vectors (GVV), assumes an instantaneous bank-angle maneuver. The solution using the first method must be found numerically, while the second has a closed-form analytical solution. These methods are compared to two existing methods. Results show the time-based geometric velocity vectors approach is precise, and the geometric velocity vectors approach is a good approximation under many conditions. The DAA problem requires the use of a robust target detection and tracking algorithm for tracking multiple maneuvering aircraft in the presence of noisy, cluttered, and missed measurements. Additionally these algorithms needs to be able to detect overtaking intruders, which has been resolved by using multiple radar sensors around the aircraft. To achieve these goals the formulation of a nonlinear extension to R-RANSAC has been performed, known as extended recursive-RANSAC (ER-RANSAC). The primary modifications needed for this ER-RANSAC implementation include the use of an EKF, nonlinear inlier functions, and the Gauss-Newton method for model hypothesis and generation. A fully functional DAA system includes target detection and tracking, collision detection, and collision avoidance. In this research we demonstrate the integration of each of the DAA-system subcomponents into fully functional simulation and hardware implementations using a ground-based radar setup. This integration resulted in various modifications of the radar DSP, collision detection, and collision avoidance algorithms, to improve the performance of the fully integrated DAA system. Using these subcomponents we present flight results of a complete ground-based radar DAA system, using actual radar hardware.