Greening pharmacy - going green

In its report for World Health Day 2008 entitled ‘Protecting Health from Climate Change’, the World Health Organization urged health sectors to lead by example in undertaking sustainability initiatives to protect people from the effects of climate change. This report suggested actions which included ensuring the health sector was involved in key policy making around sustainable development, and also, that it should work towards reducing its carbon footprint through better management of energy use, transport and procurement. However, healthcare professionals need to understand the negative effects on health of unsustainable development in order to accept that they need to change the way they deliver healthcare services...

Dual compressible hybrid quantum secret sharing schemes based on extended unitary operations

A crucial issue with hybrid quantum secret sharing schemes is the amount of data that is allocated to the participants. The smaller the amount of allocated data, the better the performance of a scheme. Moreover, quantum data is very hard and expensive to deal with, therefore, it is desirable to use as little quantum data as possible. To achieve this goal, we first construct extended unitary operations by the tensor product of n, n ≥ 2, basic unitary operations, and then by using those extended operations, we design two quantum secret sharing schemes. The resulting dual compressible hybrid quantum secret sharing schemes, in which classical data play a complementary role to quantum data, range from threshold to access structure. Compared with the existing hybrid quantum secret sharing schemes, our proposed schemes not only reduce the number of quantum participants, but also the number of particles and the size of classical shares. To be exact, the number of particles that are used to carry quantum data is reduced to 1 while the size of classical secret shares also is also reduced to l−2 m−1 based on ((m+1, n′)) threshold and to l−2 r2 (where r2 is the number of maximal unqualified sets) based on adversary structure. Consequently, our proposed schemes can greatly reduce the cost and difficulty of generating and storing EPR pairs and lower the risk of transmitting encoded particles.

Risk factors associated with an outbreak of dengue fever/dengue haemorrhagic fever in Hanoi, Vietnam

Dengue fever/dengue haemorrhagic fever (DF/DHF) appears to be emerging in Hanoi in recent years. A case-control study was performed to investigate risk factors for the development of DF/DHF in Hanoi. A total of 73 patients with DF/DHF and 73 control patients were included in the study. The risk factor analysis indicated that living in rented housing, living near uncovered sewers, and living in a house discharging sewage directly into to ponds were all significantly associated with DF/DHF. People living in rented houses were 2·2 times more at risk of DF/DHF than those living in their own homes [adjusted odds ratio (aOR) 2·2, 95% confidence interval (CI) 1·1–4·6]. People living in an unhygienic house, or in a house discharging sewage directly to the ponds were 3·4 times and 4·3 times, respectively, more likely to be associated with DF/DHF (aOR 3·4, 95% CI 1–11·7; aOR 4·3, 95% CI 1·1–16·9). These results contribute to the understanding of the dynamics of dengue transmission in Hanoi, which is needed to implement dengue prevention and control programmes effectively and efficiently.

Improving fluid registration through white matter segmentation in a twin study design

Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.