Three groups of European badger (<i>Meles meles</i> L.) were studied during 1985 and 1986 on an area of mixed farmland in the Spey Valley, Scotland. The European badger is group territorial but individuals forage solitarily. Group size was 6 (Milton group), 3-5 (Sheilich group) and 2-4 (Little Loch group). Data were obtained by means of radio tracking on five of the Milton group, three of the Sheilich group, two of the Little Loch group plus two single males. The three group territories ranged in size from 75-146 ha. and each contained a unique habitat structure. Spatial autocorrelation and graphical analyses indicated that individuals within each group distributed their intensity of use of the group territory similarly; the three groups, however, differed from one another in this respect. When examined over the long-term, individuals' total ranges and core areas overlapped widely, however, overlap of 50x50 m grid cells was low between pairs of individuals and the individual and the rest of the group suggesting partial spatial separation of individuals within the group. Over three week intervals the Milton badgers showed a complex, shifting arrangement of activity centres with no association between particular group members. On a nightly basis, an individual's total range overlapped widely with the rest of the group, but spacing of observation points for all individuals suggested that each individual's movement was concentrated in relation to the movements of the rest of the group. Diet comparisons between groups, within groups between years and between seasons suggested that availability, as indicated by the differing vegetational composition of each group territory, affected diet. Initial evidence was that individual's diets were similar within groups. Individuals within the three groups had similar range composition, showed similar preferences for the vegetation zones within each group territory and appeared to use the zones similarly. Individuals within each group exploited the group territory similarly, at least within the sensitivity of the present data. Above surface activity was strictly nocturnal and individuals showed the same pattern of varying length activity bouts interspersed with periods of rest underground; there was no common schedule, however, between individuals. Overall activity budgets were similar between individuals within the group. Individuals used the same ongoing movements each night, often travelling 3-4km, returning occasionally only to those areas that had received light use earlier in the night, and avoiding previously used areas more than expected from models of random badger movement. Group members were seldom observed in close proximity and appeared to be either spacing themselves each night randomly or avoiding one another. The three groups differed in the distribution of communal defaecation sites (latrines). All group members visited latrines and latrine paths, behaviours associated with demarcation of the group range, at similar rates. It is suggested that the spatial organization of the three groups of badgers was non-competitive. At first glance, the data indicated a large potential for spatial competition, however, a detailed analysis suggests that group members intensively used a number of different parts of the group territory ('patches'), these were shared with only a part of the group, and individuals were seldom in close contact with one another on a given night as predicted by patch based models of Carnivore group territoriality. However, territory size and configuration were not determined by the location of key feeding areas, in contradiction to the patch based models. Possible advantages gained by individuals within the group by spatial non-competitiveness are discussed in light of possible territory inheritance by related individuals. Possible advantages to all individuals contributing to demarcation of the group territory are also discussed. Group formation in European badgers is also compared with a model of group formation in birds.

Do investment portfolios meet the needs and preferences of investors? Can the portfolio selection process be improved? Traditionally, investor preferences have been identified using risk tolerance questionnaires. These questionnaires have recently attracted a fair deal of criticism. However, there has been little focus as to whether the questionnaires are useful in predicting investors' risk-taking behaviour. In this thesis, an explanatory sequential mixed methods approach was employed to find answers to the primary research question: what factors determine risk-taking behaviour in investment decisions? This thesis looked at the risk-taking behaviour of investors in Canada (N=192) and the risk-taking advice provided by financial advisers in Canada (N=155), collectively risk-taking decisions. The results suggested that return expectations and demographic variables were important predictors of risk-taking decisions, whereas risk tolerance questionnaires were not. Further investigation suggested that investment literacy impacted risk-taking decisions while investment experience impacted both return expectations and risk-taking decisions. In a novel contribution by this thesis, additional perspective was provided by qualitative analysis using semi-structured interviews with investors and advisers. From the results of the qualitative analysis, the author suggests that discovery and self-discovery, a consistent approach and a focus on process versus outcome are key attributes valued by both investors and advisers. The thesis concluded with implications and recommendations for stakeholders, including a greater focus on return expectations, more training in discovery for advisers, simulating investment experience for prospective investors and including investment literacy in school curricula.

With the development of technologies, as well as the introduction of new regulations, the banking sector is facing increasing competition from Fintech startups and companies. This weakens the monopoly of banks on financial services, which can now be provided by various kinds of companies. This situation democratizes many financial areas that were previously inaccessible or inaccessible to the general public and drives financial inclusion. One such area is investment. As part of the ongoing product development and improvement path of Fintech, startups want to get deeper and better into their potential users in order to create products that meet their problems and needs. This study is devoted to a deep study of the habits and Paterno behavior of the Swedish Millennial of investment. In order to explore the most important aspects in the process of investment decision-making, the authors studied behavioral finance research and highlighted the most common factors that have the greatest weight in determining how people invest money. These are the following factors: behavior towards risk, financial literacy, knowledge and sources, sustainability and investment motives. Survey and in-depth interview research methods were used to collect data around the aforementioned factors. Some of the key findings define crucial investment behavior patterns among age group of 20-30. Slightly more than half of the people invest their money, while reason for non/investors is high complexity and lack of knowledge. Also, the majority pursues economic and emotional goals from investing money, and prefers low risk and long-term gain over short-term speculative investing. Moreover, the respondents showed a high level of financial literacy. As for the sustainability factor, for the majority sustainability is not the major driver of a stock choice. Also, when making choices, people appeared to trust offline communities more than online. / Banksektorn har som följd av teknikutveckling och introduktion av nya regleringar, under de senaste åren, ställts inför en ökad konkurrens från Fintech-startups och andra företag. Detta har försvagat bankernas monopol på ekonomisk tjänster, och du kan idag bli försedd av flera olika sorters företag för att komma åt samma tjänster. Denna utveckling har demokratiserat många finansiella områden som tidigare var otagbara eller otillgängliga för allmänheten och har drivit ekonomisk integration. Ett sådant område är investering. Som en del av den nuvarande produktframtagning och riktningen som utvecklingen Fintech sektorn är på, vill startups ha en djupare och bättre förståelse inför deras potentiella användare för att skapa produkter som kommer möta deras problem och behov. Denna avhandling ägnas åt en djupgående studie av vanorna och beteendet hos svenska i åldersgrupperna 20-30 år. För att utforska de viktigaste aspekterna i processen för investeringsbeslut, har författarna studerat beslutsfattning kopplat till investeringar och lyfter fram de vanligaste faktorerna när det kommer till att avgöra hur människor investerar pengar. Dessa faktorer är följande: beteende relaterat till risk, finansiell kompetens, kunskap och källor, hållbarhet och investeringsmotiv. Forskningsmetoder som frågeformulär och djupintervjuer användes för att samla in data kring tidigare nämnda faktorer. Nyckelfynden från denna rapport behandlar investeringsbeteendemönster i åldersgrupprna 20-30 år. I denna åldersgrupp ser vi att fler än hälften investerar sina besparingar. Bland de som inte investerade så var orsakerna kopplade till bristande kunskap och hög komplexitet. Dessutom sätter majoriteten upp ekonomiska och känslomässiga mål för sina investeringar, och föredrar låg risk och långsiktig vinst framför kortsiktiga spekulativa investeringar. När det gäller faktorer kopplade till hållbarhet visade det sig att majoriteten av investerarna inte har det som huvudsakliga drivkraften för ett aktieval. Vidare, visade studien på att denna åldersgrupp tenderar att fatta investeringsbeslut baserat på offline-gemenskaper mer än online.

Attendance at Neonatal Follow-up (NFU) programs is crucial for parents to gain access to timely diagnostic expertise, psychosocial support, and referral to needed services for their infants. Although NFU programs are considered beneficial, up to 50% of parents do not attend these programs with their infants. Non-attending infants have poorer outcomes (e.g., higher rates of disabilities and less access to required services) as compared to attenders. The purpose was to determine factors that predicted attendance at NFU. Naturally occurring attendance was monitored and maternal-infant factors including predisposing, enabling, and needs factors were investigated, guided by the Socio-Behavioral Model of Health Services Use. A prospective two-phase multi-site descriptive cohort study was conducted in 3 Canadian Neonatal Intensive Care Units that refer to 2 NFU programs. In Phase 1, standardized questionnaires were completed by 357 mothers (66% response rate) prior to their infant’s (N= 400 infants) NICU discharge. In Phase 2, attendance patterns at NFU were followed for 12 months. Higher maternal stress at the time of the infant’s NICU hospitalization was predictive of attendance at NFU. Parenting alone, more worry about maternal alcohol or drug use, and greater distance to NFU were predictive of non-attendance at NFU. Attendance at NFU decreased over time from 84% at the first appointment to 74% by 12 months. Two distinct attendance patterns emerged: no or minimal attendance (18.5%) and attendance at all or the majority of scheduled appointments (81.5%). The most frequent point of withdrawal from NFU occurred between NICU discharge and the first scheduled appointment; followed by drop-out following the first NFU appointment. These results provide new insight into patterns of attendance and the maternal-infant factors that characterize attenders/non-attenders at NFU and serve as the critical first step in developing interventions targeted at improving attendance, infant outcomes, and reporting of developmental sequelae.

Attendance at Neonatal Follow-up (NFU) programs is crucial for parents to gain access to timely diagnostic expertise, psychosocial support, and referral to needed services for their infants. Although NFU programs are considered beneficial, up to 50% of parents do not attend these programs with their infants. Non-attending infants have poorer outcomes (e.g., higher rates of disabilities and less access to required services) as compared to attenders. The purpose was to determine factors that predicted attendance at NFU. Naturally occurring attendance was monitored and maternal-infant factors including predisposing, enabling, and needs factors were investigated, guided by the Socio-Behavioral Model of Health Services Use. A prospective two-phase multi-site descriptive cohort study was conducted in 3 Canadian Neonatal Intensive Care Units that refer to 2 NFU programs. In Phase 1, standardized questionnaires were completed by 357 mothers (66% response rate) prior to their infant’s (N= 400 infants) NICU discharge. In Phase 2, attendance patterns at NFU were followed for 12 months. Higher maternal stress at the time of the infant’s NICU hospitalization was predictive of attendance at NFU. Parenting alone, more worry about maternal alcohol or drug use, and greater distance to NFU were predictive of non-attendance at NFU. Attendance at NFU decreased over time from 84% at the first appointment to 74% by 12 months. Two distinct attendance patterns emerged: no or minimal attendance (18.5%) and attendance at all or the majority of scheduled appointments (81.5%). The most frequent point of withdrawal from NFU occurred between NICU discharge and the first scheduled appointment; followed by drop-out following the first NFU appointment. These results provide new insight into patterns of attendance and the maternal-infant factors that characterize attenders/non-attenders at NFU and serve as the critical first step in developing interventions targeted at improving attendance, infant outcomes, and reporting of developmental sequelae.

<p>Klaster analiza ima dugu istoriju i mada se<br />primenjuje u mnogim oblastima i dalje ostaju<br />značajni izazovi. U disertaciji je prikazan uvod<br />u neglatki optimizacioni pristup u<br />klasterovanju, sa osvrtom na problem<br />klasterovanja velikih skupova podataka.<br />Međutim, ovi optimizacioni algoritmi bolje<br />funkcioni&scaron;u u radu sa neprekidnim podacima.<br />Jedan od glavnih izazova u klaster analizi je<br />rad sa velikim skupovima podataka sa<br />kategorijalnim i kombinovanim (numerički i<br />kategorijalni) tipovima promenljivih. Rad sa<br />velikim brojem instanci (objekata) i velikim<br />brojem dimenzija (promenljivih), može<br />predstavljati problem u klaster analizi, zbog<br />vremenske složenosti. Jedan od načina<br />re&scaron;avanja ovog problema je redukovanje broja<br />instanci, bez gubitka informacija.<br />Prvi cilj disertacije je bio upoređivanje<br />rezultata klasterovanja na celom skupu i<br />prostim slučajnim uzorcima sa kategorijalnim i<br />kombinovanim podacima, za različite veličine<br />uzorka i različit broj klastera. Nije utvrđena<br />značajna razlika (p&gt;0.05) u rezultatima<br />klasterovanja na uzorcima obima<br />0.03m,0.05m,0.1m,0.3m (gde je m obim<br />posmatranog skupa) i celom skupu.<br />Drugi cilj disertacije je bio konstrukcija<br />efikasnog postupka klasterovanja velikih<br />skupova podataka sa kategorijalnim i<br />kombinovanim tipovima promenljivih.<br />Predloženi postupak se sastoji iz sledećih<br />koraka: 1. klasterovanje na prostim slučajnim<br />uzorcima određene kardinalnosti; 2.<br />određivanje najboljeg klasterskog re&scaron;enja na<br />uzorku, primenom odgovarajućeg kriterijuma<br />validnosti; 3. dobijeni centri klastera iz ovog<br />uzorka služe za klasterovanje ostatka skupa.<br />Treći cilj disertacije predstavlja primenu<br />klaster analize u definisanju klastera<br />bihejvioralnih faktora rizika u populaciji<br />odraslog stanovni&scaron;tva Srbije, kao i analizu<br />sociodemografskih karakteristika dobijenih<br />klastera. Klaster analiza je primenjena na<br />velikom reprezentativnom uzorku odraslog<br />stanovni&scaron;tva Srbije, starosti 20 i vi&scaron;e godina.<br />Izdvojeno je pet jasno odvojenih klastera sa<br />karakterističnim kombinacijama bihejvioralnih<br />faktora rizika: Bez rizičnih faktora, &Scaron;tetna<br />upotreba alkohola i druge rizične navike,<br />Nepravilna ishrana i druge rizične navike,<br />Nedovoljna fizička aktivnost, Pu&scaron;enje. Rezultati<br />multinomnog logističkog regresionog modela<br />ukazuju da ispitanici koji nisu u braku, lo&scaron;ijeg<br />su materijalnog stanja, nižeg obrazovanja i žive<br />u Vojvodini imaju veću &scaron;ansu za prisustvo<br />vi&scaron;estrukih bihejvioralnih faktora rizika.</p> / <p>The cluster analysis has a long history and a<br />large number of clustering techniques have<br />been developed in many areas, however,<br />significant challenges still remain. In this<br />thesis we have provided a introduction to<br />nonsmooth optimization approach to clustering<br />with reference to clustering large datasets.<br />Nevertheless, these optimization clustering<br />algorithms work much better when a dataset<br />contains only vectors with continuous features.<br />One of the main challenges is clustering of large<br />datasets with categorical and mixed (numerical<br />and categorical) data. Clustering deals with a<br />large number of instances (objects) and a large<br />number of dimensions (variables) can be<br />problematic because of time complexity. One of<br />the ways to solve this problem is by reducing<br />the number of instances, without the loss of<br />information.<br />The first aim of this thesis was to compare<br />the results of cluster algorithms on the whole<br />dataset and on simple random samples with<br />categorical and mixed data, in terms of validity,<br />for different number of clusters and for<br />different sample sizes. There were no<br />significant differences (p&gt;0.05) between the<br />obtained results on the samples of the size of<br />0.03m,0.05m,0.1m,0.3m (where m is the size of<br />the dataset) and the whole dataset.<br />The second aim of this thesis was to<br />develop an efficient clustering procedure for<br />large datasets with categorical and mixed<br />(numeric and categorical) values. The proposed<br />procedure consists of the following steps: 1.<br />clustering on simple random samples of a given<br />cardinality; 2. finding the best cluster solution<br />on a sample (by appropriate validity measure);<br />3. using cluster centers from this sample for<br />clustering of the remaining data.<br />The third aim of this thesis was to<br />examine clustering of four lifestyle risk factors<br />and to examine the variation across different<br />socio-demographic groups in a Serbian adult<br />population. Cluster analysis was carried out on<br />a large representative sample of Serbian adults<br />aged 20 and over. We identified five<br />homogenous health behaviour clusters with<br />specific combination of risk factors: &#39;No Risk<br />Behaviours&#39;, &#39;Drinkers with Risk Behaviours&#39;,<br />&#39;Unhealthy diet with Risk Behaviours&#39;,<br />&#39;Smoking&#39;. Results of multinomial logistic<br />regression indicated that single adults, less<br />educated, with low socio-economic status and<br />living in the region of Vojvodina are most likely<br />to be a part of the clusters with a high-risk<br />profile.</p>