The role of immunogenetic factors in the aetiology of pre-eclamptic toxaemia of human pregnancy

2 volume setThesis (M.D.) -- University of Adelaide, Dept. of Obstetrics and Gynaecology, 197

Density functional theory of the trapped Fermi gas in the unitary regime

We investigate a density-functional theory (DFT) approach for an unpolarized trapped dilute Fermi gas in the unitary limit . A reformulation of the recent work of T. Papenbrock [Phys. Rev. A, {\bf 72}, 041602(R) (2005)] in the language of fractional exclusion statistics allows us to obtain an estimate of the universal factor, $\xi_{3D}$, in three dimensions (3D), in addition to providing a systematic treatment of finite-$N$ corrections. We show that in 3D, finite-$N$ corrections lead to unphysical values for $\xi_{3D}$, thereby suggesting that a simple DFT applied to a small number of particles may not be suitable in 3D. We then perform an analogous calculation for the two-dimensional (2D) system in the infinite-scattering length regime, and obtain a value of $\xi_{2D}=1$. Owing to the unique properties of the Thomas-Fermi energy density-functional in 2D our result, in contrast to 3D, is {\em exact} and therefore requires no finite-$N$ corrections

Criminaliteitsbeleid: wat werkt?

In dit stuk beantwoorden we de vraag wat verstandig beleid met betrekking tot criminaliteitspreventie is, d.w.z. beleid dat wordt ondersteund door de meest recente wetenschappelijke inzichten. Ook voor lokale initiatieven is het essentieel om beleid met een adequaat onderzoek te begeleiden om de effecten en indien mogelijk de kosten/baten van de onderzochte maatregelen te evalueren. In dit verhaal gaan we in op enkele voorbeelden van beleid op het terrein van criminaliteit, en geven daarbij aan wat werkt en wat niet. We concluderen dat criminaliteitsbeleid niet alleen gericht moet zijn op potentiële daders, maar dat het belangrijker is om de context waarin criminaliteit wordt gepleegd in het beleid te betrekken. Allereerst wordt een aantal belangrijke feiten met betrekking tot criminaliteit uiteengezet. Daarna volgen de principes van criminaliteitsbestrijding. Vervolgens wordt uiteengezet waarom experimenteel onderzoek van groot belang is. We eindigen met een overzicht van waar de beste informatie te vinden is

Zich bekeren en wisselen van kerkgenootschap in Nederland

Conversion and switching between religious denominations in the Netherlands In this article, we examine why people in the Netherlands switch between religious denominations or become a convert. To do so, we use 21 representative surveys held between 1966 and 2003. We derive hypotheses from the integration theory, modernization theory (secularisation theory) and the supply side theory (version of rational choice theory). Becoming a convert or religious switching are rare phenomena in the Netherlands: 4.5 percent of the population switches between denominations and 2.6 percent becomes a convert. In line with secularisation theory, people who are raised nonreligious almost always stay non-religious while people who were raised in a certain denomination are more likely to leave the church or to switch denominations. Also in line with this theory is the finding that over time, less people convert to religion and more and more people leave the church of their parents. In line with the social capital hypotheses, we find that Protestants more often switch between denominations than Catholics. More specifically, orthodox Protestants switch more often than liberal Protestants. Of all factors that influence religious mobility, the denomination of the spouse is most important: people in a religiously mixed marriage switch significantly more often than people in a religiously homogeneous marriage. Switching and converting are almost all towards the denomination of the spouse.

Determine the User Country of a Tweet

In the widely used message platform Twitter, about 2% of the tweets contains the geographical location through exact GPS coordinates (latitude and longitude). Knowing the location of a tweet is useful for many data analytics questions. This research is looking at the determination of a location for tweets that do not contain GPS coordinates. An accuracy of 82% was achieved using a Naive Bayes model trained on features such as the users' timezone, the user's language, and the parsed user location. The classifier performs well on active Twitter countries such as the Netherlands and United Kingdom. An analysis of errors made by the classifier shows that mistakes were made due to limited information and shared properties between countries such as shared timezone. A feature analysis was performed in order to see the effect of different features. The features timezone and parsed user location were the most informative features.Comment: CTIT Technical Report, University of Twent