Aposematic species of true bugs (Heteroptera) have multimodal signalization, which warns potential predators. This signalization consists of optical (coloration), chemical (unpalatable or repugnant substance) and acoustic (stridulation) warning signals. The aim of this thesis was to test whether the selected chemical substances have antipredatory function towards avian predators. Antipredatory function is anticipated in the chemical substances that form the majority in secretion in many taxa of true bugs (aldehydes and tridecane). In experiments with wild-caught great tits (Parus major) and blue tits (Cyanistes caeruleus) we tested if chemical substances and age of birds have influence on the latency related to the first manipulation with the prey. It was found that both species of tits reacted aversively to the mixture of aldehydes (2-decenal, 2-octenal, 2-hexenal) and to the total secretion of metathoracic glands of Graphosoma lineatum, whereas the mixture of the aldehydes with tridecane did not have any effect. The effect of age was not significant. We also tested the influence of immediate experience with striated shieldbug Graphosoma lineatum on naive great tits and their reactions to the prey with olfactoric signal of the shieldbug. Additionally, we investigated whether tested chemicals cause...

Using an early warning system (EWS) methodology, this thesis analyses the predictability of stock market crises from the perspective of behavioural fnance. Specifcally, in our EWS based on the multinomial logit model, we consider in- vestor sentiment as one of the potential crisis indicators. Identifcation of the relevant crisis indicators is based on Bayesian model averaging. The empir- ical results reveal that price-earnings ratio, short-term interest rate, current account, credit growth, as well as investor sentiment proxies are the most rele- vant indicators for anticipating stock market crises within a one-year horizon. Our thesis hence provides evidence that investor sentiment proxies should be a part of the routinely considered variables in the EWS literature. In general, the predictive power of our EWS model as evaluated by both in-sample and out-of-sample performance is promising. JEL Classifcation G01, G02, G17, G41 Keywords Stock market crises, Early warning system, In- vestor sentiment, Crisis prediction, Bayesian model averaging Title Predicting stock market crises using investor sentiment indicators

No description available.

In lane departure warning systems (LDWS) it is important that the auditory warning triggers a fast and appropriate reaction from the driver. The rumble strip noise is a suitable warning to alert the driver of an imminent lane departure. A short reaction time is important in lane departure scenarios, where a late response may have fatal consequences. For abstract sounds an increase in intensity can influence the perceived urgency level of the warning, which may also trigger a faster reaction from the listener. In this thesis, the effect of a rumble strip warning with looming (increasing) intensity was analyzed by letting test persons drive a driving simulator and measuring how quickly they reacted to the auditory warning. These results were compared with those for a rumble strip warning with a constant intensity, and two versions of an abstract warning; constant intensity and looming intensity. A survey regarding the perceived urgency, annoyance and acceptance of the warnings was also carried out. The results show no differences in reaction time between the four warning signals. This may be because the test persons expected the warnings, or because of their limited experience. The survey suggests that adding a looming intensity to the rumble strip warning results in a higher urgency, while keeping the annoyance low, which could be of importance to avoid unwanted reactions from the driver. / I varningssystem för personbilar används ofta ett system som signalerar ett stundande ofrivilligt lämnande av körfältet, s.k. lane departure warning systems (LDWS), genom att en varningssignal ljuder. Det är viktigt att en sådan akustisk varningssignal frammanar en snabb och lämplig reaktion från föraren. Ljudet av en bullerräffla är en lämplig varningssignal för detta ändamål. En kort reaktionstid är viktig när fordon är på väg att ofrivilligt lämna körfältet, då en långsam reaktion kan ha förödande konsekvenser. Studier på abstrakta akustiska varningssignaler har visat att en ökande intensitet kan få en varning att verka mer brådskande, vilket i sin tur kan leda till att lyssnaren reagerar snabbare. I denna rapport analyseras hur ett bullerräffleljuds ökande intensitet påverkar förarens reaktionstid. Analysen gjordes genom att mäta reaktionstiden hos testpersoner som körde en bilsimulator med fyra olika varningssignaler; en bullerräffleljudsvarning och en abstrakt varning, båda med konstant intensitet och ökande intensitet. Reaktionstiderna för de olika signalerna jämfördes, varpå en enkät utfärdades där testpersonerna uppgav hur brådskande och irriterande de uppfattade varningarna, samt till vilken grad de skulle acceptera varningarna i ett verkligt körscenario. Resultaten visar inga skillnader i reaktionstid mellan varningarna, vilket kan bero på att testpersonerna förutsåg när varningarna skulle komma, eller på grund av deras begränsade erfarenhet av bullerräffleljud. Enkätens utfall antyder att bullerräffleljudsvarningen med ökande intensitet är mer brådskande än versionen med konstant intensitet, men att irritationsnivån inte påverkas när intensiteten ökar, vilket kan vara viktigt för att inte framkalla oönskade reaktioner hos föraren.

The going concern warning and its consequences for auditors and companies have been studied from many different angles. However, the results are conflicting. A going concern warning is issued by an auditor when there is substantial doubt on the company’s ability to continue as a going concern. Studies have shown that most companies survive despite a going concern warning. There are also signs of short-term consequences for the companies. How the consequences unfold in the long run for companies that have received a going concern warning is not well studied. The purpose of this study is to investigate how companies are affected in the long run by the consequences that can arise due to a going concern warning. For this study, a quantitative method has been used. Legitimacy theory, Interest theory and Institutional theory, have the common factor that they all explain how organizations survive in the long run. The theories, together with scientific articles and other relevant literature, have been used to develop the hypotheses. Companies with a going concern warning have been compared with companies that have not received a going concern warning. Empirical data have been collected for 2010-2015 and by using multiple linear regressions the hypotheses of the study have been tested. The result of the study showed that a going concern warning did not adversely affect the company on a long-term basis. On the contrary, the study indicates that companies with a going concern warning improve compared to equivalent companies which did not receive a going concern warning.

This diploma thesis provides a fact-based examination of the relevance of assumptions concerning the relationship of human insecurity and the emergence of conflict. This is done with a quantitative analysis of cross-country data on human insecurity and conflict during the period of 1990 - 2010. The approach of the thesis steps beyond the prevailing discussions on human security focused on normative judgements on the nature, legitimacy or applicability of the concept. Through a statistical analysis, it challenges the use of uncontested and ungraspable, yet influential, narratives of human security that result in implementation of inadequately informed programs and policies aimed at prevention of conflict by the international community and other actors. The analysis finds that a random set of indicators of human security, rather than human security as a concept, are related to conflict emergence. As a result, the thesis suggests surpassing the preoccupation with the use and application of the concept and instead accentuates inductive approach to formulating evidence-based conflict-prevention programs inspired by the ideas of human security rather than reasoned by the concept of human security. Powered by TCPDF (www.tcpdf.org)

No description available.

Social capital — resources that are available as a result of social relationships and connections — has been shown to be an important component across the various stages of a natural disaster, such as a hurricane. Additionally, research has shown that the importance of the different types of social capital — bonding, bridging, and linking — can vary as the disaster progresses from preparation, to the immediate aftermath, to long-term recovery. Yet, findings are not consistent regarding the impact of social capital on taking protective action (e.g., evacuation, shelter in home or community) following a hurricane warning. In this paper, we leverage an original survey of 1450 residents living in coastal communities in the Southeast and Gulf Coast regions of the United States to examine the role of social capital in stated behaviors in response to a hurricane warning. Additionally, we examine the stated likelihood of evacuating if advised to by close contacts (friends, family, and co-workers) and elite sources (emergency management officials, elected officials, and the media). We find that bonding social capital is associated with an increased likelihood to evacuate and shelter in home as well as an increased likelihood to listen to close contacts that encourage evacuation. In addition, we find that linking social capital is associated with an increased likelihood of evacuation if encouraged to by elite sources.

En översvämning kan inträffa när som helst och var som helst i världen. En översvämning börjar när vattennivån ökar, särskilt i dagvattenbrunnar i stadsområden. Genom att utnyttja de olika moderna teknologier som Internet of Things (IoT), förluster som orsakas av en översvämning kan minskas. Därför behövs en IoT-lösning för att övervaka vattennivån i brunnarna.Syftet med denna avhandling är att undersöka hur man konstruerar och implementerar ett IoT-baserat system som övervakar vattennivån för att bygga en prototyp med LoRaWAN teknologi. Konstruktionen av prototypen utförs genom att följa stegen i en iterativ systemutvecklingsmetod. Prototypen använder ett offentligt Lora-nätverk, särskilt The Things Network (TTN). Prototypens funktioner är att mäta vattennivån med en ultraljudssensor, sända mätdata via LoRa till TTN och visualisera data på en visualiserings plattform "Cayenne" i realtid. Systemet är testad i en laboratoriemiljö. Resultaten av den konstruerade prototypen visar att den mäter vattennivån och skickar mätdata när vattennivåns tillstånd ändras. Dessutom visualiseras datan på visualiserings plattformen Cayenne. / A flood may occur anytime and anywhere in the world. A flood starts when the water level increases, especially, in the wells in the urban areas. By taking advantage of the modern technology, such as Internet of Things (IoT), the losses caused by the flood can be reduced. Therefore, an IoT-solution is needed for monitoring the water level in the wells.The aim of this thesis is to investigate how to design and implement an IoT-based system that monitors the water level to build a prototype using LoRaWAN technology. Building the prototype is done by following the steps of an iterative system development method. The prototype uses a Lora public network, specifically The Things Network (TTN). The functions of the prototype are measuring the water level by an ultrasound sensor, sending the measurement data through LoRa to TTN, and visualizing the data on the "Cayenne" dashboard in real-time. The system is tested in a lab environment. The results of the constructed prototype show that the prototype measures the water level and sends the measurement data whenever the state of the water level is changed. Additionally, the data is visualized on the Cayenne dashboard.

Indiana University-Purdue University Indianapolis (IUPUI) / Floods are one of the worst disasters in the United States. Each year, the government allocates a tremendous amount of manpower and money on flood prevention initiatives. As the first defense line, levees provide protection from temporary flooding (Makhdoom, 2013). These embankments are broadly classified according to the areas they protect, which could either be urban or agricultural levees within floodplains. In the U.S., most of the levees are handled by government agencies such as the U.S. Army Corps of Engineers and the Federal Emergency Management Services. On the other hand, non-levee embankments created by individual farmers (Olson & Morton, 2013) or naturally formed levee-like structures may not be in the government database. The initial purpose of this research was to assist Polis center on the “Mapping of Non-Levee Embankments in the Indiana” project. The non-levee embankments are not certified or engineered levee-like structures. They, therefore, impose lateral constraints on flood flows, reducing the floodplain storage capacity and increasing the flood velocity. These non-levee embankments can cause stream erosion and downstream flooding. Therefore, it is important to know the locations of these features. The first part of the proposed method adapted the Empirical Bayesian theorem and the low pass filter techniques to extract elevated linear features from LiDAR elevation data – Digital Elevation Model (DEM). The second part of the proposed methods combined the Minimum Bounding Circle (MBC) method and the Youden Index to locate the optimal threshold value that can be used to determine whether the extracted features are levee-like structures. The focus of this study is not only limited to artificial levee-like structures, but also takes the natural levees, or any potential levee-like structures into account because this study assumes all embankments play important roles during flood events.