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Climate change is likely to have an effect on global food production but to examine effects on food and nutrition security, an appreciation of the dimensions of food security is required. The 1996 World Food Summit defined food security as ‘when all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active healthy life’. Thus food security is largely multi-factorial and defined by context. Australia and New Zealand both have substantial agricultural profiles and there is a significant production in meat and livestock, dairy and grains from the region. Both countries are islands, surrounded by oceans with extensive fisheries, bearing in mind that the local ecology will reflect the type of fish that are available. Meeting dietary needs and food preferences in this context would mean taking into account the health profiles of the population and how these relate to the food that is available now and in the future. Layering in the effects of climate change means that the high prevalence of lifestyle related disease (obesity, heart disease, diabetes) and the vulnerability of at risk groups, particularly in remote communities in Australia, will require additional consideration. Disciplines Arts and Humanities | Life Sciences | Medicine and Health Sciences | Social and Behavioral Sciences Publication Details Tapsell, L. C., Probst, Y., Lawrence, M., Friel, S., Flood, V. M., McMahon, A. & Butler, R. (2011). Food and nutrition security in the Australia-New Zealand region: impact of climate change. World Review of Nutrition and Dietetics, 102 192-200. Authors Linda Tapsell, Yasmine Probst, Mark Lawrence, Sharon Friel, Victoria Flood, Anne McMahon, and Rosalind Butler This journal article is available at Research Online: http://ro.uow.edu.au/hbspapers/3554 Food and nutrition security Food and nutrition security in the Australia-New Zealand region: impact of climate change Linda C Tapsell, Yasmine Probst, Mark Lawrence, Sharon Friel, Victoria Flood, Anne McMahon, Rosalind Butler 1 1 University of Wollongong, Wollongong NSW Australia Australian National University, Canberra ACT Australia 3 Deakin University, Australia, Burwood VIC Australia * Corresponding author: Smart Foods Centre, University of Wollongong, Wollongong NSW 2522 Australia. P: +612 4221 3152, F: +612 4221 4844, E: ltapsell@uow.edu.au Food and nutrition security

Air pollution is a major issue all over the world because of its impacts on the environment and human beings. The present review discussed the sources and impacts of pollutants on environmental and human health and the current research status on environmental pollution forecasting techniques in detail; this study presents a detailed discussion of the Artificial Intelligence methodologies and Machine learning (ML) algorithms used in environmental pollution forecasting and early-warning systems; moreover, the present work emphasizes more on Artificial Intelligence techniques (particularly Hybrid models) used for forecasting various major pollutants (e.g., PM2.5, PM10, O3, CO, SO2, NO2, CO2) in detail; moreover, focus is given to AI and ML techniques in predicting chronic airway diseases and the prediction of climate changes and heat waves. The hybrid model has better performance than single AI models and it has greater accuracy in prediction and warning systems. The performance evaluation error indexes like R2, RMSE, MAE and MAPE were highlighted in this study based on the performance of various AI models.

Abstract Aims Minimum unit price (MUP) of 50 pence per unit of alcohol was introduced in Scotland on the 1 May 2018. We assessed alcohol-related liver disease (ArLD) discharges from Glasgow Royal Infirmary (GRI) before and after the introduction of MUP. Methods Medical records of all patients discharged from Gastroenterology wards at GRI in the fourth quarter (Q4) of the years 2015–2019 were reviewed. All patients with ArLD were identified, and detailed hospitalization data were collected retrospectively. Active drinking, severity scores, presence of alcoholic hepatitis (AH) and 90-day mortality and readmission rates were assessed. Results There were fewer ArLD discharges per quarter after MUP than before (mean 80.3 pre-MUP; mean 68 post-MUP), and the proportion of active drinkers was lower post-MUP (64.7 vs. 70.5%). There was a significant fall in the mean number of weekly discharges of individual patients who were actively drinking (4.0 ± 2.0 pre-MUP, 2.8 ± 1.5 post-MUP, P = 0.01). There were no differences in the proportion of patients presenting with ascites, encephalopathy or AH; however, there was a reduction in presentations with acute upper gastrointestinal bleeding from 15.8% pre-MUP to 7.4% post-MUP (P = 0.02; odds ratio 0.42). Severity of liver disease remained unchanged. The 90-day mortality and readmission rates were not significantly different. Conclusion Since the introduction of MUP there has been a reduction in the absolute numbers of patients discharged with ArLD and the number of individual patients involved at GRI. The pattern of clinical presentation was largely unaffected with overall ArLD severity, readmission rates and 90-day mortality similar pre- and post-MUP.

Abstract A high temperature polymer electrolyte membrane water electrolyser (PEMWE) was investigated at temperatures between 80 and 130 °C and pressures between 0.5 and 4 bar. Nanometer size Ru 0.7 Ir 0.3 O 2 and Pt/C were employed as anode and cathode catalysts respectively. The catalyst coated on membrane (CCM) method was used to fabricate the membrane electrode assemblies. The membrane, oxygen evolution catalysts and MEAs were characterized with SEM, XRD and TEM. The influence of high temperature and pressure was investigated using in situ electrochemical measurements. Increasing temperature and pressure produced higher current densities for oxygen evolution, and smaller terminal voltages. The high temperature PEMWE achieved a voltage of 1.51 V at a current density of 1 A cm −2 , at 130 °C and 4 bar pressure.

The relative biological effectiveness (RBE) varies along the treatment field. However, in clinical practice, a constant RBE of 1.1 is assumed, which can result in undesirable side effects. This study provides an accurate overview of current clinical practice for considering proton RBE in Europe.A survey was devised and sent to all proton therapy centres in Europe that treat patients. The online questionnaire consisted of 39 questions addressing various aspects of RBE consideration in clinical practice, including treatment planning, patient follow-up and future demands.All 25 proton therapy centres responded. All centres prescribed a constant RBE of 1.1, but also applied measures (except for one eye treatment centre) to counteract variable RBE effects such as avoiding beams stopping inside or in front of an organ at risk and putting restrictions on the minimum number and opening angle of incident beams for certain treatment sites. For the future, most centres (16) asked for more retrospective or prospective outcome studies investigating the potential effect of the effect of a variable RBE. To perform such studies, 18 centres asked for LET and RBE calculation and visualisation tools developed by treatment planning system vendors.All European proton centres are aware of RBE variability but comply with current guidelines of prescribing a constant RBE. However, they actively mitigate uncertainty and risk of side effects resulting from increased RBE by applying measures and restrictions during treatment planning. To change RBE-related clinical guidelines in the future more clinical data on RBE are explicitly demanded.

Background: Sodium oxybate (SMO) has been shown to be effective in the maintenance of abstinence (MoA) in alcohol-dependent patients in a series of small randomized controlled trials (RCTs). These results needed to be confirmed by a large trial investigating the treatment effect and its sustainability after medication discontinuation. Aims: To confirm the SMO effect on (sustained) MoA in detoxified alcohol-dependent patients. Methods: Large double-blind, randomized, placebo-controlled trial in detoxified adult alcohol-dependent outpatients (80% men) from 11 sites in four European countries. Patients were randomized to 6 months SMO (3.3–3.9 g/day) or placebo followed by a 6-month medication-free period. Primary outcome was the cumulative abstinence duration (CAD) during the 6-month treatment period defined as the number of days with no alcohol use. Secondary outcomes included CAD during the 12-month study period. Results: Of the 314 alcohol-dependent patients randomized, 154 received SMO and 160 received placebo. Based on the pre-specified fixed-effect two-way analysis of variance including the treatment-by-site interaction, SMO showed efficacy in CAD during the 6-month treatment period: mean difference +43.1 days, 95% confidence interval (17.6–68.5; p = 0.001). Since significant heterogeneity of effect across sites and unequal sample sizes among sites ( n = 3–66) were identified, a site-level random meta-analysis was performed with results supporting the pre-specified analysis: mean difference +32.4 days, p = 0.014. The SMO effect was sustained during the medication-free follow-up period. SMO was well-tolerated. Conclusions: Results of this large RCT in alcohol-dependent patients demonstrated a significant and clinically relevant sustained effect of SMO on CAD. Trial registration: ClinicalTrials.gov Identifier: NCT04648423

ABSTRACTObjectivesElectronic health records (EHRs) contain rich information for understanding health conditions and their treatment. A large proportion of clinical information in EHRs is stored in narrative free text. This text is currently under-utilised due to privacy concerns, as it is harder to remove patient identifiers from text than from structured data. Automated de-identification of clinical text is now possible using heuristic or machine-learning-based systems. We conducted a review of the literature on patient and public understanding and attitudes towards the use of patients’ medical data for research, particularly seeking views on free text. The aim was to inform and develop a governance framework for the de-identification and use of medical free text for research, and to instigate a wider discussion on the topic. ApproachWe undertook a systematic search in Web of Science and ScienceDirect with terms such as “public attitudes” and “electronic health records”. 3480 results were sifted by title, abstract and full text. Forty-two articles were retained for review, these reported on studies of patient and public perceptions, understanding and attitudes towards the use of patients’ medical data in research. ResultsResearch participants were positively inclined towards information in records being used in research “for the greater good”. However, no clear patterns by age, ethnicity, education level or SES emerged as to who was more favourable to data use. Participants generally trusted health care professionals and public sector researchers with de-identified medical data, whereas government health agencies and commercial entities were not trusted. No explicitly feared harms associated with data use were articulated. However the general objections appeared to be a dislike of personal data being exploited for commercial gain, and a dislike of personal data being moved around and used without personal knowledge or consent. Notably the use of EHR medical text for research did not emerge as a specific patient/public concern. De-identification was important to participants but text was not identified as a distinct privacy risk.ConclusionThis review demonstrates that transparency about data usage, and working “for the greater good” rather than financial gain, appear to be the most important public concerns to be addressed when using patients’ medical data. Governance frameworks for using EHRs must now be enhanced to provide for the use of medical text. This will involve informing both regulators and the public about the current capabilities of automated de-identification, and developing other assurances to safeguard patients’ privacy.

We assess the effect of the COVID-19 pandemic on global fossil fuel consumption and CO2 emissions over the two-year horizon 2020Q1-2021Q4. We apply a global vector autoregressive (GVAR) model, which captures complex spatial-temporal interdependencies across countries associated with the international propagation of economic impact due to the virus spread. The model makes use of a unique quarterly data set of coal, natural gas, and oil consumption, output, exchange rates and equity prices, including global fossil fuel prices for 32 major CO2 emitting countries spanning the period 1984Q1-2019Q4. We produce forecasts of coal, natural gas and oil consumption, conditional on GDP growth scenarios based on alternative IMF World Economic Outlook forecasts that were made before and after the outbreak. We also simulate the effect of a relative price change in fossil fuels, due to global scale carbon pricing, on consumption and output. Our results predict fossil fuel consumption and CO2 emissions to return to their pre-crisis levels, and even exceed them, within the two-year horizon despite the large reductions in the first quarter following the outbreak. Our forecasts anticipate more robust growth for emerging than for advanced economies. The model predicts recovery to the pre-crisis levels even if another wave of pandemic occurs within a year. Our counterfactual carbon pricing scenario indicates that an increase in coal prices is expected to have a smaller impact on GDP than on fossil fuel consumption. Thus, the COVID-19 pandemic would not provide countries with a strong reason to delay climate change mitigation efforts.