High-Performance Nanostructured Palladium-Based Hydrogen Sensors-Current Limitations and Strategies for Their Mitigation.

Hydrogen gas is rapidly approaching a global breakthrough as a carbon-free energy vector. In such a hydrogen economy, safety sensors for hydrogen leak detection will be an indispensable element along the entire value chain, from the site of hydrogen production to the point of consumption, due to the high flammability of hydrogen-air mixtures. To stimulate and guide the development of such sensors, industrial and governmental stakeholders have defined sets of strict performance targets, which are yet to be entirely fulfilled. In this Perspective, we summarize recent efforts and discuss research strategies for the development of hydrogen sensors that aim at meeting the set performance goals. In the first part, we describe the state-of-the-art for fast and selective hydrogen sensors at the research level, and we identify nanostructured Pd transducer materials as the common denominator in the best performing solutions. As a consequence, in the second part, we introduce the fundamentals of the Pd-hydrogen interaction to lay the foundation for a detailed discussion of key strategies and Pd-based material design rules necessary for the development of next generation high-performance nanostructured Pd-based hydrogen sensors that are on par with even the most stringent and challenging performance targets.

Addressing and reducing parameter uncertainty in quantitative microbial risk assessment by incorporating external information via Bayesian hierarchical modeling.

Probabilistic quantitative microbial risk assessment (QMRA) studies define model inputs as random variables and use Monte-Carlo simulation to generate distributions of potential risk outcomes. If local information on important QMRA model inputs is missing, it is widely accepted to justify assumptions about these model inputs by using external literature information. A question, which remains unexplored, is the extent to which previously published external information should influence local estimates in cases of nonexistent, scarce, and moderate local data. This question can be addressed by employing Bayesian hierarchical modeling (BHM). Thus, we study the effects and potential benefits of BHM on risk and performance target calculations at three wastewater treatment plants (WWTP) in comparison to alternative statistical modeling approaches (separate modeling, no-pooling, complete pooling). The treated wastewater from the WWTPs is used for restricted irrigation, potable reuse, or influences recreational waters, respectively. We quantify the extent to which external data affects local risk estimations in each case depending on the statistical modeling approach applied. Modeling approaches are compared by calculating the pointwise expected log-predictive density for each model. As reference pathogens and example data, we use locally collected Norovirus genogroup II data with varying sample sizes (n = 4, n = 7, n = 27), and complement local information with external information from 44 other WWTPs (n = 307). Results indicate that BHM shows the highest predictive accuracy and improves estimates by reducing parameter uncertainty when data are scarce. In such situations, it may affect risk and performance target calculations by orders of magnitude in comparison to using local data alone. Furthermore, it allows making generalizable inferences about new WWTPs, while providing the necessary flexibility to adjust for different levels of information contained in the local data. Applying this flexible technique more widely may contribute to improving methods and the evidence base for decision-making in future QMRA studies.

Impact of the SIGN head injury guidelines and NHS 4-hour emergency target on hospital admissions for head injury in Scotland: an interrupted times series.

OBJECTIVES: Head injury is a common reason for emergency department (ED) attendance. Around 1% of patients have life-threatening injuries, while 80% of patients are discharged. National guidelines (Scottish Intercollegiate Guidelines Network (SIGN)) were introduced in Scotland with the aim of achieving early identification of those with acute intracranial lesions yet safely reducing hospital admissions.This study aims to assess the impact of these guidelines and any effect the national 4-hour ED performance target had on hospital admissions for head injury. SETTING: All Scottish hospitals between April 1998 and March 2016. PARTICIPANTS: Patients admitted to hospital for head injury or traumatic brain injury (TBI) diagnosed by CT imaging identified using administrative Scottish Information Services Division data. There are 275 hospitals in Scotland. In 2015/2016, there were 571 221 emergency hospital admissions in Scotland. INTERVENTIONS: The SIGN head injury guidelines introduced in 2000 and 2009. The 4-hour ED target introduced in 2004. OUTCOMES: The monthly rate of hospital admissions for head injury and traumatic brain injury. STUDY DESIGN: An interrupted time series analysis. RESULTS: The first guideline was associated with a reduction in monthly admissions of 0.14 (95% CI 0.09 to 4.83) per 100 000 population. The 4-hour target was associated with a monthly increase in admissions of 0.13 (95% CI 0.06 to 0.20) per 100 000 population. The second guideline reduced monthly admissions by 0.09 (95% CI-0.13 to -0.05) per 100 000 population. These effects varied between age groups.The guidelines were associated with increased admissions for patients with injuries identified by CT imaging-guideline 1: 0.06 (95% CI 0.004 to 0.12); guideline 2: 0.05 (95% CI 0.04 to 0.06) per 100 000 population. CONCLUSION: Increased CT imaging of head injured patients recommended by SIGN guidelines reduced hospital admissions. The 4-hour ED target and the increased identification of TBI by CT imaging acted to undermine this effect.

Exploring emergency department 4-hour target performance and cancelled elective operations: a regression analysis of routinely collected and openly reported NHS trust data.

OBJECTIVE: To quantify the effect of intrahospital patient flow on emergency department (ED) performance targets and indicate if the expectations set by the National Health Service (NHS) England 5-year forward review are realistic in returning emergency services to previous performance levels. DESIGN: Linear regression analysis of routinely reported trust activity and performance data using a series of cross-sectional studies. SETTING: NHS trusts in England submitting routine nationally reported measures to NHS England. PARTICIPANTS: 142 acute non-specialist trusts operating in England between 2012 and 2016. MAIN OUTCOME MEASURES: The primary outcome measures were proportion of 4-hour waiting time breaches and cancelled elective operations. METHODS: Univariate and multivariate linear regression models were used to show relationships between the outcome measures and various measures of trust activity including empty day beds, empty night beds, day bed to night bed ratio, ED conversion ratio and delayed transfers of care. RESULTS: Univariate regression results using the outcome of 4-hour breaches showed clear relationships with empty night beds and ED conversion ratio between 2012 and 2016. The day bed to night bed ratio showed an increasing ability to explain variation in performance between 2015 and 2016. Delayed transfers of care showed little evidence of an association. Multivariate model results indicated that the ability of patient flow variables to explain 4-hour target performance had reduced between 2012 and 2016 (19% to 12%), and had increased in explaining cancelled elective operations (7% to 17%). CONCLUSIONS: The flow of patients through trusts is shown to influence ED performance; however, performance has become less explainable by intratrust patient flow between 2012 and 2016. Some commonly stated explanatory factors such as delayed transfers of care showed limited evidence of being related. The results indicate some of the measures proposed by NHS England to reduce pressure on EDs may not have the desired impact on returning services to previous performance levels.

Target virus log10 reduction values determined for two reclaimed wastewater irrigation scenarios in Japan based on tolerable annual disease burden.

Multiple-barriers are widely employed for managing microbial risks in water reuse, in which different types of wastewater treatment units (biological treatment, disinfection, etc.) and health protection measures (use of personal protective gear, vegetable washing, etc.) are combined to achieve a performance target value of log10 reduction (LR) of viruses. The LR virus target value needs to be calculated based on the data obtained from monitoring the viruses of concern and the water reuse scheme in the context of the countries/regions where water reuse is implemented. In this study, we calculated the virus LR target values under two exposure scenarios for reclaimed wastewater irrigation in Japan, using the concentrations of indigenous viruses in untreated wastewater and a defined tolerable annual disease burden (10-4 or 10-6 disability-adjusted life years per person per year (DALYpppy)). Three genogroups of norovirus (norovirus genogroup I (NoV GI), geogroup II (NoV GII), and genogroup IV (NoV GIV)) in untreated wastewater were quantified as model viruses using reverse transcription-microfluidic quantitative PCR, and only NoV GII was present in quantifiable concentration. The probabilistic distribution of NoV GII concentration in untreated wastewater was then estimated from its concentration dataset, and used to calculate the LR target values of NoV GII for wastewater treatment. When an accidental ingestion of reclaimed wastewater by Japanese farmers was assumed, the NoV GII LR target values corresponding to the tolerable annual disease burden of 10-6 DALYpppy were 3.2, 4.4, and 5.7 at 95, 99, and 99.9%tile, respectively. These percentile values, defined as "reliability," represent the cumulative probability of NoV GII concentration distribution in untreated wastewater below the corresponding tolerable annual disease burden after wastewater reclamation. An approximate 1-log10 difference of LR target values was observed between 10-4 and 10-6 DALYpppy. The LR target values were influenced mostly by the change in the logarithmic standard deviation (SD) values of NoV GII concentration in untreated wastewater and the reliability values, which highlights the importance of accurately determining the probabilistic distribution of reference virus concentrations in source water for water reuse.

Incidence Rate of Acute Encephalitis Syndrome without Specific Treatment in India and Nepal.

BACKGROUND: A performance target (PT) for the incidence rate (IR) of acute encephalitis syndrome (AES) was not defined by the World Health Organization (WHO) due to lack of data. There is no specific treatment for ~90% of the AES cases. OBJECTIVES: (1) To determine the IR of AES not having specific treatment (AESn) in two countries, India and Nepal. (2) To suggest the PT. SUBJECTS AND METHODS: This was a record-based study of the entire population of India and Nepal from 1978 to 2011. The WHO definition was used for inclusion of cases. Cases that had specific treatment were excluded. IR was calculated per 100,000 population per annum. Forecast IR was generated from 2010 to 2013 using time-series analysis. RESULTS: There were 165,461 cases from 1978 to 2011, of which 125,030 cases were from India and 40,431 were from Nepal. The mean IR of India was 0.42 (s 0.24) and that of Nepal was 5.23 (σ 3.03). IRs of 2010 and 2011 of India and that of 2011 of Nepal were closer to the mean IR rather than the forecast IR. IR of 2010 of Nepal was closer to the forecast IR. The forecast IR for India for 2012 was 0.49 (0.19-1.06), for 2013 was 0.42 (0.15-0.97) and for Nepal for both 2012 and 2013 was 5.62 (1.53-15.05). CONCLUSIONS: IRs were considerably different for India and Nepal. Using the current mean IR as PT for the next year was simple and practical. Using forecasting was complex and, less frequently, useful.