Socioeconomic inequalities in childhood exposure to secondhand smoke before and after smoke-free legislation in three UK countries

Background: Secondhand smoke (SHS) exposure is higher among lower socioeconomic status (SES) children. Legislation restricting smoking in public places has been associated with reduced childhood SHS exposure and increased smoke-free homes. This paper examines socioeconomic patterning in these changes.<p></p> Methods: Repeated cross-sectional survey of 10 867 schoolchildren in 304 primary schools in Scotland, Wales and Northern Ireland. Children provided saliva for cotinine assay, completing questionnaires before and 12 months after legislation.<p></p> Results: SHS exposure was highest, and private smoking restrictions least frequently reported, among lower SES children. Proportions of saliva samples containing <0.1 ng/ml (i.e. undetectable) cotinine increased from 31.0 to 41.0%. Although across the whole SES spectrum, there was no evidence of displacement of smoking into the home or increased SHS exposure, socioeconomic inequality in the likelihood of samples containing detectable levels of cotinine increased. Among children from the poorest families, 96.9% of post-legislation samples contained detectable cotinine, compared with 38.2% among the most affluent. Socioeconomic gradients at higher exposure levels remained unchanged. Among children from the poorest families, one in three samples contained > 3 ng/ml cotinine. Smoking restrictions in homes and cars increased, although socioeconomic patterning remained.<p></p> Conclusions Urgent action is needed to reduce inequalities in SHS exposure. Such action should include emphasis on reducing smoking in cars and homes

Beyond the hybrid library : libraries in a Web 2.0 world

Considers the development of social networking and the concept of Web 2.0. Looks at the implications for libraries and how traditional competences remain relevant. Explores what libraries are doing and must do to remain relevan

Space-Time Clustering and Correlations of Major Earthquakes

Earthquake occurrence in nature is thought to result from correlated elastic stresses, leading to clustering in space and time. We show that occurrence of major earthquakes in California correlates with time intervals when fluctuations in small earthquakes are suppressed relative to the long term average. We estimate a probability of less than 1% that this coincidence is due to random clustering.Comment: 5 pages, 3 figures. Submitted to PR

Gas Sorption and Luminescence Properties of a Terbium(III)-Phosphine Oxide Coordination Material with Two-Dimensional Pore Topology

The structure, stability, gas sorption properties and luminescence behaviour of a new lanthanide-phosphine oxide coordination material are reported. The polymer PCM-15 is based on Tb(III) and tris(p-carboxylated) triphenylphosphine oxide and has a 5,5-connected net topology. It exhibits an infinite three-dimensional structure that incorporates an open, two-dimensional pore structure. The material is thermally robust and remains crystalline under high vacuum at 150 degrees C. When desolvated, the solid has a CO2 BET surface area of 1187 m(2) g(-1) and shows the highest reported uptake of both O-2 and H-2 at 77 K and 1 bar for a lanthanide-based coordination polymer. Isolated Tb(III) centres in the as-synthesized polymer exhibit moderate photoluminescence. However, upon removal of coordinated OH2 ligands, the luminescence intensity was found to approximately double; this process was reversible. Thus, the Tb(III) centre was used as a probe to detect directly the desolvation and resolvation of the polymer.Welch Foundation F-1738, F-1631National Science Foundation 0741973, CHE-0847763Chemistr

Educational Leadership Preparation: What Supervisors, Candidates, And Mentors Said

The findings of this study identified practicum areas that meet the educational demands of candidates while highlighting practicum areas that need improvement. The study contributes to the knowledge base of the field by drawing upon feedback from university supervisors, school mentors and program candidates to evaluate and improve the practicum experience in the educational leadership program. Program candidates are in the best position to discuss their recent experiences of exposure to the real world. Supervisors and mentors can witness from their first hand experience how effective practicum activities work. Responses from supervisors, mentors and candidates regarding leadership practicum experiences are valuable to program developers in their future program redesign effort. Practicum experiences expose candidates to real-world school leadership experiences. Unfortunately, because of all kinds of conditional limitations, such practicum experiences can only be offered in conjunction with candidates' regular work in school. However, leadership practicum experiences can be well planned with a high collaboration of supervisors, mentors and candidates who have an invested interest in school improvement. In this study, what we learn from the differences of perceptions among supervisors, mentors and candidates is a caution to all stakeholders that we need to do a better job to prepare the next generation of school leaders. Supervisors, mentors and candidates need to form a coalition to explore other options, especially out-of-the-box strategies, to deliver a highly effective practicum program for potential educational leaders.&nbsp

Pattern Informatics and its Application for Optimal Forecasting of Large Earthquakes in Japan

Pattern Informatics (PI) technique can be used to detect precursory seismic activation or quiescence and make an earthquake forecast. Here we apply the PI method for optimal forecasting of large earthquakes in Japan, using the data catalogue maintained by the Japan Meteorological Agency. The PI method is tested to forecast large (magnitude m ≥ 5) earthquakes spanning the time period 1995-2004 in the Kobe region. Visual inspection and statistical testing show that the optimized PI method has forecasting skill, relative to the seismic intensity data often used as a standard null hypothesis. Moreover, we find in a retrospective forecast that the 1995 Kobe earthquake (m = 7.2) falls in a seismically anomalous area. Another approach to test the forecasting algorithm is to create a future potential map for large (m ≥ 5) earthquake events. This is illustrated using the Kobe and Tokyo regions for the forecast period 2000-2009. Based on the resulting Kobe map we point out several forecasted areas: The epicentral area of the 1995 Kobe earthquake, the Wakayama area, the Mie area, and the Aichi area. The Tokyo forecast map was created prior to the occurrence of the Oct. 23, 2004 Niigata earthquake (m = 6.8) and the principal aftershocks with 5.0 ≤ m. We find that these events were close to in a forecasted area on the Tokyo map. The PI technique for regional seismicity observation substantiates an example showing considerable promise as an intermediate-term earthquake forecasting in Japa

Identification of diverse database subsets using property-based and fragment-based molecular descriptions

This paper reports a comparison of calculated molecular properties and of 2D fragment bit-strings when used for the selection of structurally diverse subsets of a file of 44295 compounds. MaxMin dissimilarity-based selection and k-means cluster-based selection are used to select subsets containing between 1% and 20% of the file. Investigation of the numbers of bioactive molecules in the selected subsets suggest: that the MaxMin subsets are noticeably superior to the k-means subsets; that the property-based descriptors are marginally superior to the fragment-based descriptors; and that both approaches are noticeably superior to random selection

Reducing smoking in adolescents: cost-effectiveness results from the cluster randomized ASSIST (A Stop Smoking In Schools Trial)

Introduction: School-based smoking prevention programmes can be effective, but evidence on cost-effectiveness is lacking. We conducted a cost-effectiveness analysis of a school-based “peer-led” intervention.<p></p> Methods: We evaluated the ASSIST (A Stop Smoking In Schools Trial) programme in a cluster randomized controlled trial. The ASSIST programme trained students to act as peer supporters during informal interactions to encourage their peers not to smoke. Fifty-nine secondary schools in England and Wales were randomized to receive the ASSIST programme or usual smoking education. Ten thousand seven hundred and thirty students aged 12–13 years attended participating schools. Previous work has demonstrated that the ASSIST programme achieved a 2.1% (95% CI = 0%–4.2%) reduction in smoking prevalence. We evaluated the public sector cost, prevalence of weekly smoking, and cost per additional student not smoking at 24 months.<p></p> Results: The ASSIST programme cost of £32 (95% CI = £29.70–£33.80) per student. The incremental cost per student not smoking at 2 years was £1,500 (95% CI = £669–£9,947). Students in intervention schools were less likely to believe that they would be a smoker at age 16 years (odds ratio [OR] = 0.80; 95% CI = 0.66–0.96).<p></p> Conclusions: A peer-led intervention reduced smoking among adolescents at a modest cost. The intervention is cost-effective under realistic assumptions regarding the extent to which reductions in adolescent smoking lead to lower smoking prevalence and/or earlier smoking cessation in adulthood. The annual cost of extending the intervention to Year 8 students in all U.K. schools would be in the region of £38 million and could result in 20,400 fewer adolescent smokers.<p></p&gt

Recognition of plants using a stochastic L-system model

Recognition of natural shapes like leaves, plants, and trees, has proven to be a challenging problem in computer vision. The members of a class of natural objects are not identical to each other. They are similar, have similar features, but are not exactly the same. Most existing techniques have not succeeded in effectively recognizing these objects. One of the main reasons is that the models used to represent them are inadequate themselves. In this research we use a fractal model, which has been very effective in modeling natural shapes, to represent and then guide the recognition of a class of natural objects, namely plants. Variation in plants is accommodated by using the stochastic L-systems. A learning system is then used to generate a decision tree that can be used for classification. Results show that the approach is successful for a large class of synthetic plants and provides the basis for further research into recognition of natural plants

Earthquake forecasting and its verification

No proven method is currently available for the reliable short time prediction of earthquakes (minutes to months). However, it is possible to make probabilistic hazard assessments for earthquake risk. In this paper we discuss a new approach to earthquake forecasting based on a pattern informatics (PI) method which quantifies temporal variations in seismicity. The output, which is based on an association of small earthquakes with future large earthquakes, is a map of areas in a seismogenic region ('hotspots'') where earthquakes are forecast to occur in a future 10-year time span. This approach has been successfully applied to California, to Japan, and on a worldwide basis. Because a sharp decision threshold is used, these forecasts are binary--an earthquake is forecast either to occur or to not occur. The standard approach to the evaluation of a binary forecast is the use of the relative (or receiver) operating characteristic (ROC) diagram, which is a more restrictive test and less subject to bias than maximum likelihood tests. To test our PI method, we made two types of retrospective forecasts for California. The first is the PI method and the second is a relative intensity (RI) forecast based on the hypothesis that future large earthquakes will occur where most smaller earthquakes have occurred in the recent past. While both retrospective forecasts are for the ten year period 1 January 2000 to 31 December 2009, we performed an interim analysis 5 years into the forecast. The PI method out performs the RI method under most circumstances