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BackgroundMental health policy makers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable.AimsTo develop and validate a population-level prediction model for need for early intervention in psychosis (EIP) care for first-episode psychosis (FEP) in England up to 2025, based on epidemiological evidence and demographic projections.MethodWe used Bayesian Poisson regression to model small-area-level variation in FEP incidence for people aged 16–64 years. We compared six candidate models, validated against observed National Health Service FEP data in 2017. Our best-fitting model predicted annual incidence case-loads for EIP services in England up to 2025, for probable FEP, treatment in EIP services, initial assessment by EIP services and referral to EIP services for ‘suspected psychosis’. Forecasts were stratified by gender, age and ethnicity, at national and Clinical Commissioning Group levels.ResultsA model with age, gender, ethnicity, small-area-level deprivation, social fragmentation and regional cannabis use provided best fit to observed new FEP cases at national and Clinical Commissioning Group levels in 2017 (predicted 8112, 95% CI 7623–8597; observed 8038, difference of 74 [0.92%]). By 2025, the model forecasted 11 067 new treated cases per annum (95% CI 10 383–11 740). For every 10 new treated cases, 21 and 23 people would be assessed by and referred to EIP services for suspected psychosis, respectively.ConclusionsOur evidence-based methodology provides an accurate, validated tool to inform clinical provision of EIP services about future population need for care, based on local variation of major social determinants of psychosis.

Forecast-based drought early warning/early action has been hampered by both inadequate decision-making frameworks and a lack of appropriate funding mechanisms. Rural communities in Nicaragua and Ethiopia that have participated in resilience-building interventions of varying durations demonstrate the value of community-based actions informed by early warning, forecasts and drought management advice, both before and during the agricultural season. While drought affected all crops negatively, participants were better able to mitigate impacts, were more organised in accessing relief and recovered more effectively. These results are consistent with other research on the cost/benefit of anticipatory actions, use of climate services and appropriate drought management advice. They also confirm the importance of embedding short-term early action in long-term resilience-building. Despite this, formal systems, national and local, remain essentially unimplemented. Systems being developed at global level now need to be operationalised and translated into effective local drought management standard operating procedures for the most vulnerable.

This paper reflects on contemporary studies of and responses to disasters, highlighting the importance of historical, spatial, and intersectional modes of analysis, and draws on the author's ongoing research on Southern‐led and local community responses to displacement in the Middle East. Acknowledging the plurality of ‘international communities of response’, it begins by critiquing the depiction of selected responses to disasters as ‘positive’ ‘paradigm shifts’, including in reference to the ‘localisation of aid, and the United Nations’ Regional Refugee and Resilience Plan for Syria. Next it turns to three key themes that are central to disasters studies: migration; forced displacement; and Southern‐led responses to disasters. Among other things, the paper argues that exploring the principles and modalities of South–South cooperation, rather than promoting the incorporation of Southern actors into the ‘international humanitarian system’ via the localisation agenda, presents a critical opportunity for studies of and responses to disasters.

This paper revisits and reiterates the needs, purposes and requirements of biodosimetric assays for long-term dose and health risk assessments. While the most crucial need for biodosimetric assays is to guide medical response for radiation accidents, the value of such techniques for improving our understanding of radiation health risk by supporting epidemiological (long-term health risk) studies is significant. As new cohorts of exposed persons are identified and new health risk studies are undertaken with the hopes that studying the exposed will result in a deeper understanding of radiation risk, the value of reliable dose reconstruction is underscored. The ultimate application of biodosimetry in long-term health risk studies would be to completely replace model-based dose reconstruction-a complex suite of methods for retrospectively estimating dose that is commonly fraught with large uncertainties due to the absence of important exposure-related information, as well as imperfect models. While biodosimetry could potentially supplant model-based doses, there are numerous limitations of presently available techniques that constrain their widespread application in health risk research, including limited ability to assess doses received far in the past, high cost, great inter-individual variability, invasiveness, higher than preferred detection limits and the inability to assess internal dose (for the most part). These limitations prevent the extensive application of biodosimetry to large cohorts and should be considered a challenge to researchers to develop new and more flexible techniques that meet the demands of long-term health risk research. Events in recent years, e.g. the Fukushima reactor accident and the increased threat of nuclear terrorism, underscore that any event that results in significant radiation exposures of a group of people will also produce a much larger population, exposed at lower levels, but that likewise needs (or demands) an exposure assessment. Hence, the needs for retrospective dose estimation are likely to be greater in the future. The value of biodosimetry can be considerably enhanced with the development of new or improved methods, particularly with suitability for application at long periods of time after exposure.

The historical development of multiphoton microscopy is described, starting with a review of two-photon absorption, and including two- and three-photon fluorescence microscopies, and second- and third-harmonic generation microscopies. The effects of pulse length on signal strength and breakdown are considered. Different contrast mechanisms, including use of nanoparticles, are discussed. Two new promising techniques that can be applied to multiphoton microscopy are described.

Background The aims of this study were to review and update previous projections of the number of proximal femoral fractures in the Northern Ireland population and to ascertain if the trend of increasing age-specific fracture incidence was continuing. Methods Data from 1985 to 1997 was obtained from hospital theatre records to ascertain the number of surgical procedures for proximal femoral fracture. Data for the years 2005 and 2010 was obtained from Northern Ireland's Fracture Outcomes Research Database (FORD) and locally held records in one region not then using FORD. Demographic details were obtained from data published by the Northern Ireland Statistics and Research Agency. Age-specific fracture rates were calculated for males and females in 5 year age brackets and for populations aged 50+ and 65+. Updated projections for the number of proximal femoral fractures by 2020 were made assuming the continuation of the same age-specific fracture rates observed in 2010. Results From 1997 to 2010 the age-specific fracture incidence has fallen or plateaued across most observed age and sex subgroups. Over the period 2010 to 2020, male and female fracture numbers are projected to increase by 23% and 21% respectively which equates to approximately 400 extra proximal femoral fractures. Conclusion Over the next decade there will be an increasing burden on Northern Irish healthcare resources attributed to a rise in the number of proximal femoral fractures. The age-specific fracture rates in this population are no longer rising and hence the expected increase in healthcare costs is primarily a consequence of the anticipated changing demographic trends.

Pulping production process produces a large amount of wastewater and pollutant emitted, which has become one of the main pollution sources in pulp and paper industry. To solve this problem, it is necessary to implement cleaner production by using modeling and optimization technology. This paper studies the modeling and multi-objective genetic algorithms for continuous digester process. First, model is established, in which environmental pollution and saving energy factors are considered. Then hybrid genetic algorithm based on Pareto stratum-nichecount is designed for finding near-Pareto or Pareto optimal solutions in the problem and a new genetic evaluation and selection mechanism is proposed. Finally using the real data from a pulp mill shows the results of computer simulation. Through comparing with the practical curve of digester, this method can reduce the pollutant effectively and increase the profit while keeping the pulp quality unchanged.

Objectives: To accurately establish the incidence of falls in Parkinson9s disease (PD) and to investigate predictive risk factors for fallers from baseline data. Methods: 109 subjects with idiopathic PD diagnosed according to the brain bank criteria underwent a multidisciplinary baseline assessment comprising demographic and historical data, disease specific rating scales, physiotherapy assessment, tests of visual, cardiovascular and autonomic function, and bone densitometry. Patients were then prospectively followed up for one year using weekly prepaid postcards along with telephone follow up. Results: Falls occurred in 68.3% of the subjects. Previous falls, disease duration, dementia, and loss of arm swing were independent predictors of falling. There were also significant associations between disease severity, balance impairment, depression, and falling. Conclusions: Falls are a common problem in PD and some of the major risk factors are potentially modifiable. There is a need for future studies to look at interventions to prevent falls in PD.