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Police forces are constantly competing to provide adequate service whilst faced with major funding cuts. The funding cuts result in limited resources hence methods of improving resource efficiency are vital to public safety. One area where improving the efficiency could drastically improve service is the planning of patrol routes for incident response officers. Current methods of patrolling lack direction and do not consider response demand. Police patrols have the potential to deter crime when directed to the right areas. Patrols also have the ability to position officers with access to high demand areas by pre-empting where response demand will arise. The algorithm developed in this work directs patrol routes in real-time by targeting high crime areas whilst maximising demand coverage. Methods used include kernel density estimation for hotspot identification and maximum coverage location problems for positioning. These methods result in more effective daily patrolling which reduces response times and accurately targets problem areas. Though applied in this instance to daily patrol operations, the methodology could help to reduce the need for disaster relief operations whilst also positioning proactively to allow quick response when disaster relief operations are required.

Exposing Zostera marina to fertilized porewater has been shown to increase vegetative shoot density and leaf growth rates, and affect shoot morphology. However, aside from changes in shoot density, records of morphological changes to reproductive shoots are lacking. To address this, five replicate ambient and nutrient enriched patches, each between 0.5 and 2.0 m 2 , were selected within a developing Z. marina meadow in Shinnecock Bay, NY. Fertilizer stakes, with a N:P:K of 15:3:3, were used to amend the sediments of a subset of patches in the late fall and early spring. In June, morphological measurements of reproductive shoots and stages of anthesis were recorded. We found significantly increased reproductive shoot height, number of rhipidia, and number of spathes on each rhipidium in response to fertilization. Nutrient enrichment also advanced the stage of ovary development in the first spathes at the time of sampling, indicating that the rate of development had been accelerated or the reproductive shoot had flowered earlier. Additionally, the number of normally developing ovaries, as determined by the size of the seed embryo, was significantly greater in enriched patches. We estimated that these changes acted to increase seed output per reproductive shoot, and may have enhanced pollen access by elevating receptive stigma above the local vegetative canopy.

Automated guided vehicles (AGVs) are being extensively used for intelligent transportation and distribution of materials in warehouses and autoproduction lines due to their attributes of high efficiency and low costs. Such vehicles travel along a predefined route to deliver desired tasks without the supervision of an operator. Much effort in this area has focused primarily on route optimisation and traffic management of these AGVs. However, the health management of these vehicles and their optimal mission configuration have received little attention. To assure their added value, taking a typical AGV transport system as an example, the capability to evaluate reliability issues in AGVs are investigated in this paper. Following a failure modes effects and criticality analysis (FMECA), the reliability of the AGV system is analysed via fault tree analysis (FTA) and the vehicles mission reliability is evaluated using the Petri net (PN) method. By performing the analysis, the acceptability of failure of the mission can be analysed, and hence the service capability and potential profit of the AGV system can be reviewed and the mission altered where performance is unacceptable. The PN method could easily be extended to have the capability to deal with fleet AGV mission reliability assessment.

Seven to ten days after a first dose of a measles-containing vaccine (MCV; i.e., MMR or MMRV), children have elevated fever risk which can be associated with febrile seizures. This study investigated individual and familial factors associated with fever 7-10days after MCV.Retrospective cohort study among children who were36months of age at receipt of MCV in six sites of the Vaccine Safety Datalink from 1/1/2000 to 12/31/2012. We evaluated medically-attended clinic or emergency department visits with a code for fever 7-10days after any MCV ("MCV- associated"). We evaluated factors associated with MCV-associated fever using χAmong 946,806 children vaccinated with MCV, we identified 7480 (0.8%) MCV-associated fever visits. Compared with children without fever after MCV, children with MCV-associated fever were more likely to have received MMRV than MMR (OR 1.3 95% CI 1.2, 1.5), have had medically attended fever both following previous vaccines (OR 1.3 95% CI 1.1, 1.6) and at any other previous time (OR 1.7 95% CI 1.6, 1.8), have had at least 1 prior seizure (OR 2.2 95% CI 1.7, 2.7), and have had3 medical visits within the 6months before MCV (OR 1.7 95% CI 1.6, 1.8). In families with multiple MCV-immunized children, after adjusting for healthcare seeking behavior care for fever, those whose siblings had MCV-associated fever were more likely to also have MCV-associated fever (OR 3.5 95% CI 2.5, 4.8).Children who received MMRV vaccine or who had prior medically-attended fevers and seizures during the first year of life had increased risk of fever after a first dose of measles vaccine. After adjusting for familial propensity to seek care, MCV-associated fever still clustered within families, suggesting a possible genetic basis for susceptibility to developing fever due to measles vaccines.

In the United States, annual vaccination against seasonal influenza is recommended for all persons aged ≥6 months (1). Each influenza season since 2004-05, CDC has estimated the effectiveness of seasonal influenza vaccine to prevent influenza-associated, medically attended, acute respiratory illness (ARI). This report uses data, as of February 4, 2017, from 3,144 children and adults enrolled in the U.S. Influenza Vaccine Effectiveness Network (U.S. Flu VE Network) during November 28, 2016-February 4, 2017, to estimate an interim adjusted effectiveness of seasonal influenza vaccine for preventing laboratory-confirmed influenza virus infection associated with medically attended ARI. During this period, overall vaccine effectiveness (VE) (adjusted for study site, age group, sex, race/ethnicity, self-rated general health, and days from illness onset to enrollment) against influenza A and influenza B virus infection associated with medically attended ARI was 48% (95% confidence interval [CI] = 37%-57%). Most influenza infections were caused by A (H3N2) viruses. VE was estimated to be 43% (CI = 29%-54%) against illness caused by influenza A (H3N2) virus and 73% (CI = 54%-84%) against influenza B virus. These interim VE estimates indicate that influenza vaccination reduced the risk for outpatient medical visits by almost half. Because influenza activity remains elevated (2), CDC and the Advisory Committee on Immunization Practices recommend that annual influenza vaccination efforts continue as long as influenza viruses are circulating (1). Vaccination with 2016-17 influenza vaccines will reduce the number of infections with most currently circulating influenza viruses. Persons aged ≥6 months who have not yet been vaccinated this season should be vaccinated as soon as possible.

Clonal foraging in response to heterogeneously distributed water, light or mineral resources has been demonstrated for a number of terrestrial plant species. The existence of similar behavior in seagrasses and the cross-scale effects of clonal foraging on patch development, however, have not fully been explored. Our objective was to test whether spatial exploration by independent ramet clusters could generate emergent patch behavior consistent with clonal foraging theory. We also examined the effect of nutrient amendment on reproductive effort and seedling recruitment. Working in Shinnecock Bay, New York, USA, with the clonal marine angiosperm, Zostera marina, we attempted to stimulate directional growth along ten patch edges over a two-year period using subterranean fertilizer. Changes in ramet demography, patch expansion, seedling emergence and reproductive effort were quantified through repeated shoot censusing. We found that nutrient addition accelerated patch expansion. Enriched edges exhibited significantly higher shoot densities, indicating that a ramet proliferation, selective ramet placement or a combination of the two responses had occurred. The seasonality of this effect was different between treatments and consistent among years, representing a fundamental shift in the pattern and phenology of seagrass growth. Within patches, no detectable differences in per capita branching rates or reproductive effort were observed. This study provides the first evidence of foraging behavior by patches of Z. marina, and offers new insight into its seasonal growth patterns during the as yet poorly understood colonization period.

In this paper, data-driven approaches are applied to identify faults of a practical polymer electrolyte membrane (PEM) fuel cell system. Signal processing approaches are selected and employed to multiple sensor measurements, including methodologies reducing the dimension of the original dataset, and techniques extracting features. Both supervised and unsupervised techniques are applied in this study to investigate the robustness of the diagnostic procedure. Moreover, due to the fact that a series of features can be extracted from these sensors, the singular value decomposition (SVD) technique is applied to select features providing better diagnostic performance. Results demonstrate that with features selected from SVD, fuel cell system faults can be detected more effectively, and various fuel cell faults can also be discriminated with good quality. From the findings, conclusions are made and further work is suggested.

We study variants of a recently introduced hybrid system model, called a Hierarchical Piecewise Constant Derivative (HPCD). These variants (loosely called Restricted HPCDs) form a class of natural models with similarities to many other well known hybrid system models in the literature such as Stopwatch Automata, Rectangular Automata and PCDs. We study the complexity of reachability and mortality problems for variants of RHPCDs and show a variety of results, depending upon the allowed powers. These models form a useful tool for the study of the complexity of such problems for hybrid systems, due to their connections with existing models.\ud We show that the reachability problem and the mortality problem are co-NP-hard for bounded 3-dimensional RHPCDs (3-RHPCDs). Reachability is shown to be in PSPACE, even for n-dimensional RHPCDs. We show that for an unbounded 3-RHPCD, the reachability and mortality problems become undecidable. For a nondeterministic variant of 2-RHPCDs, the reachability problem is shown to be PSPACE-complete.

Background Since 2013, quadrivalent influenza vaccines containing 2 B viruses gradually replaced trivalent vaccines in the United States. We compared the vaccine effectiveness of quadrivalent to trivalent inactivated vaccines (IIV4 to IIV3, respectively) against illness due to influenza B during the transition, when IIV4 use increased rapidly. Methods The US Influenza Vaccine Effectiveness (Flu VE) Network analyzed 25 019 of 42 600 outpatients aged ≥6 months who enrolled within 7 days of illness onset during 6 seasons from 2011–2012. Upper respiratory specimens were tested for the influenza virus type and B lineage. Using logistic regression, we estimated IIV4 or IIV3 effectiveness by comparing the odds of an influenza B infection overall and the odds of B lineage among vaccinated versus unvaccinated participants. Over 4 seasons from 2013–2014, we compared the relative odds of an influenza B infection among IIV4 versus IIV3 recipients. Results Trivalent vaccines included the predominantly circulating B lineage in 4 of 6 seasons. During 4 influenza seasons when both IIV4 and IIV3 were widely used, the overall effectiveness against any influenza B was 53% (95% confidence interval [CI], 45–59) for IIV4 versus 45% (95% CI, 34–54) for IIV3. IIV4 was more effective than IIV3 against the B lineage not included in IIV3, but comparative effectiveness against illnesses related to any influenza B favored neither vaccine valency. Conclusions The uptake of quadrivalent inactivated influenza vaccines was not associated with increased protection against any influenza B illness, despite the higher effectiveness of quadrivalent vaccines against the added B virus lineage. Public health impact and cost-benefit analyses are needed globally., During the 4 influenza seasons beginning in 2013–2014, trivalent and quadrivalent inactivated influenza vaccines provided equivalent protection against any influenza B illness in the United States, while quadrivalent vaccines provided better protection against the added B virus lineage.

Background Increased illness due to antigenically drifted A(H3N2) clade 3C.3a influenza viruses prompted concerns about vaccine effectiveness (VE) and vaccine strain selection. We used US virologic surveillance and US Influenza Vaccine Effectiveness (Flu VE) Network data to evaluate consequences of this clade. Methods Distribution of influenza viruses was described using virologic surveillance data. The Flu VE Network enrolled ambulatory care patients aged ≥6 months with acute respiratory illness at 5 sites. Respiratory specimens were tested for influenza by means of reverse-transcriptase polymerase chain reaction and were sequenced. Using a test-negative design, we estimated VE, comparing the odds of influenza among vaccinated versus unvaccinated participants. Results During the 2018–2019 influenza season, A(H3N2) clade 3C.3a viruses caused an increasing proportion of influenza cases. Among 2763 Flu VE Network case patients, 1325 (48%) were infected with A(H1N1)pdm09 and 1350 (49%) with A(H3N2); clade 3C.3a accounted for 977 (93%) of 1054 sequenced A(H3N2) viruses. VE was 44% (95% confidence interval, 37%–51%) against A(H1N1)pdm09 and 9% (−4% to 20%) against A(H3N2); VE was 5% (−10% to 19%) against A(H3N2) clade 3C.3a viruses. Conclusions The predominance of A(H3N2) clade 3C.3a viruses during the latter part of the 2018–2019 season was associated with decreased VE, supporting the A(H3N2) vaccine component update for 2019–2020 northern hemisphere influenza vaccines.

Diagnostics and health management of fuel cells are key aspects for improvement of reliability and durability. To achieve performance and lifetime targets it is necessary for fuel cell operating conditions to be optimally managed. An improved fuzzy inference system, utilizing multiple high priority health sensors, for diagnostics and health management of polymer electrolyte fuel cells is presented in this paper. Due to membrane chemical degradation having a critical impact on fuel cell health; the investigation focuses on diagnosing this degradation. The fuzzy inference system enables connections between the intricate relationships of fuel cell operating conditions and consequential degradation modes. A database of inference rules for diagnostics is developed through the literature and experimental testing. Experimental testing was conducted on two fuel cells with differing cell areas. Results support the diagnosis of membrane chemical degradation and therefore support the validation of the fuzzy inference system. The approach has shown the capability of providing diagnostics for different fuel cell designs. The diagnostic fuzzy inference system enables proactive decision making as part of an improved health management system to increase availability and lifetime of fuel cells.

The home is a key environment for geriatric care. Research has demonstrated patients discharged to their homes are at a high risk of readmission of transitioning to homecare. The ability for care providers to predict and mitigate risk is limited in this environment. Significant observational requirements hinder continued diagnosis which limits timely interventions before a readmission event. Technology is used to resolve this issue and provide enhanced risk assessments by gathering data, however these technologies present a wide variety of challenges including barriers to use and ethical considerations which hinder an effective solution. This paper seeks to examine the necessary observations homecare providers require to form effective risk assessments and interventions in the home. This is achieved by remote monitoring through Bluetooth low energy (BLE) sensors for the common causes of hospital readmissions including observed difficulties in activities of daily living (ADL), heart rate fluctuations and falls. Risk is assessed by examining these factors as events to deduce behaviour or apparent reduction in capacity to function in daily life. Results obtained when using BLE sensors, heart rate monitors and fall detectors show it is possible to observe and record events of interest to health care providers in the provision of geriatric homecare. Patterns within sensor data could be used in the home environment to form an effective patient risk analysis given remote monitoring access to a patient and prescribed care plan to evaluate outcomes and possibility of readmission. Further experiments will test and validate the risk assessment analysis formed in this paper.

Automated guided vehicles (AGV's) have been adopted in many industrial applications since their introduction in the 1950’s. Although still primarily used for the movement of materials around manufacturing facilities and warehouses they are also used in such applications as hospitals and transportation. Such driverless vehicles generally travel along a predefined route performing set tasks and they have been widely adopted due to their efficiency and economic benefits, Le-Anh and De Koster (2006). The availability of the vehicles is crucial to ensure that these benefits are maintained. As the complexity of industrial processes increases and fleets of AGV’s are commonly employed, maintenance and reliability issues are of increasing concern. In order to ensure that the benefits of AGV’s are utilised efficiently it is crucial that efficient maintenance strategies are employed. Hence in this work research has been undertaken into determining the optimal maintenance strategy for a complex multi AGV system.

Operational Research (OR) techniques in sport have primarily focused on fixture timetabling, officials scheduling, and result forecasting. Emerging novel approaches to micro-level analysis of sport participation data is vital in providing sport management and the public health sector with evidence to make informed decisions about sport participation strategies and policy. The paper aims to identify factors facilitating effective decision making on increasing participation using logistic regression analysis. 24,678 records from the Active People Survey were used to determine factors that could be used to predict swimming participation for different demographic groups in England. Results show that the current country level approach covering all sports masks too much detail and the micro level approach to understanding relationships between the regressed variable (swimming participation) and the explanatory variables adopted in this paper is required to enable more effective policy recommendations to be made on increasing swimming, or any sport, participation.

Homecare systems are a focus of research due to shifting care requirements of the elderly. Activity has become a vital metric when monitoring vulnerable patients. Activity monitoring however is contextual and difficult to capture. In this paper the implementation of a Bluetooth low energy monitoring system which incorporates the interoperability of Internet of Things (IoT) to create a sustainable homecare approach is explored. Monitored patient health is evaluated using activities of daily living standards. Data captured is evaluated to determine movement, motion and location which contribute to the activity based, sensor driven care models. Activity is captured by occupants interacting with 'unique' objects of interest (OOI). Interactions captured are evaluated using activities of daily living by aligning room positioning, transference within the home and OOI use.

BACKGROUND: Annual influenza vaccination has been recommended for persons with high-risk conditions since the 1960s. However, few estimates of influenza vaccine effectiveness (VE) for persons with high-risk conditions are available. METHODS: Data from the U.S. Influenza Vaccine Effectiveness Network from 2012‒2016 were analyzed to compare VE of standard-dose inactivated vaccines against medically-attended influenza among patients aged ≥6 months with and without high-risk medical conditions. Patients with acute respiratory illness were tested for influenza by RT-PCR. Presence of high-risk conditions and vaccination status were obtained from medical records. VE by influenza virus type/subtype and age group was calculated for patients with and without high-risk conditions using the test-negative design. Interaction terms were used to test for differences in VE by high-risk conditions. RESULTS: Overall, 9,643 (38%) of 25,369 patients enrolled during four influenza seasons had high-risk conditions; 2,213 (23%) tested positive for influenza infection. For all ages, VE against any influenza was lower among patients with high-risk conditions (41%, 95% CI: 35%‒47%) than those without (48%, 95% CI: 43%‒52%; P-for-interaction = 0.02). For children aged

Polymer electrolyte membrane fuel cells (PEMFC) are a promising technology for economic and environmentally friendly energy production. However, they haven’t reached their full potential in the market yet as only few reliable PEMFC systems have successfully passed the prototyping face. A drawback of the current diagnostic tools is that only a select few are of high genericity, reliability and can perform efficiently on-line at the same time. Furthermore, there is only limited research identifying both PEMFC stack faults and ancillary system faults simultaneously. While none of the existing tools can be interrogated by the end-user. In this research, we develop novel artificial intelligence-based technologies to overcome these existing barriers, i.e., (i) a semantically enriched integrating schema (ontology) of the overall operation and structure of the PEMFC that allows automatic inference engines to automatically deduce fault detection; (ii) a knowledge-based, light-weight, on-line fuel cell system diagnosis (FuCSyDi) platform. FuCSyDi detects and provides the location of failures by considering only the data from the reliable sensors. Additionally, it provides the reasons underpinning any forthcoming failures and enables the end-user to interrogate the platform for further information regarding its operation and structure. Our platform is validated by performing tests against common automotive stress conditions. This innovative approach enhances the reliability of the fuel cell system diagnosis and, hence, its lifetime performance.

This paper proposes a novel approach for fault diagnosis of polymer electrolyte membrane fuel cell (PEMFC) with two-dimension (2D) image data, and investigates its effectiveness of identifying faults at different PEMFCs in terms of discrimination capacity and robustness. In the analysis, one-dimension (1D) voltage data from single cell is converted to corresponding 2D image using signal-to-image conversion technique. Various features are then extracted from the 2D image data, and optimal features are determined using Fisher discriminant analysis (FDA). Test data from PEMFC at different faulty states, including flooding and dehydration states, is collected for the analysis, and the effectiveness of optimal features in discriminating various states is investigated using K-means clustering method. Moreover, diagnostic performance with 2D image data is compared to those using 1D voltage signals, such that its effectiveness can be better highlighted. Furthermore, with test data collected from two different single cells, robustness of proposed method can be illustrated.

Child and adolescent trauma exposure is prevalent, with trauma exposure-related symptoms, including posttraumatic stress, depressive, and anxiety symptoms often causing substantial impairment. This article updates the evidence base on psychosocial treatments for child and adolescent trauma exposure completed for this journal by Silverman et al. (2008). For this review, we focus on 37 studies conducted during the seven years since the last review. Treatments are grouped by overall treatment family (e.g., cognitive behavioral therapy), treatment modality (e.g., individual vs. group), and treatment participants (e.g., child only vs. child and parent). All studies were evaluated for methodological rigor according to Journal of Clinical Child & Adolescent Psychology evidence-based treatment evaluation criteria (Southam-Gerow & Prinstein, 2014), with cumulative designations for level of support for each treatment family. Individual CBT with parent involvement, individual CBT, and group CBT were deemed well-established; group CBT with parent involvement and eye movement desensitization and reprocessing (EMDR) were deemed probably efficacious; individual integrated therapy for complex trauma and group mind–body skills were deemed possibly efficacious; individual client-centered play therapy, individual mind–body skills, and individual psychoanalysis were deemed experimental; and group creative expressive + CBT was deemed questionable efficacy. Advances in the evidence base, with comparisons to the state of the science at the time of the Silverman et al. (2008) review, are discussed. Finally, we present dissemination and implementation challenges and areas for future research.

Zostera marina is a cosmopolitan, temperate seagrass species capable of both sexual and asexual (i.e., clonal) reproduction. Until recently, the importance of sexual reproduction has been largely dismissed, and clonal growth has dominated our understanding of space acquisition by Z. marina. This model of Z. marina growth was developed in locations where reproductive effort falls on the lower end of a wide range in sexual productivity. This study assessed Z. marina seed production as a function of patch size in a landscape where sexual reproduction has played a significant role in meadow expansion. Additionally, a landscape-scale analysis of seagrass proximity was performed to determine whether relationships between seed production and percent seagrass coverage exist. Reproductive shoots were collected from 58 seagrass patches of four different size classes: 2.5, 5, 10, and 20 m2 over a two-year period. Seeds were harvested, enumerated, and scored for viability. Viable seed density was significantly related to patch size, but no statistically significant difference was found for non-viable seed densities between patch sizes. Larger patches, with both an edge and center region, were evaluated by region; no difference was found between seed production at the edge vs. center for these size classes. Finally, seed densities were not positively correlated with the amount of proximate seagrass in the landscape. The results of this study suggest that more explicit regional studies of sexual reproduction dynamics must be undertaken to fully understand the complex reproductive ecology of this angiosperm.

Background. During the 2014–2015 US influenza season, expanded genetic characterization of circulating influenza A(H3N2) viruses was used to assess the impact of the genetic variability of influenza A(H3N2) viruses on influenza vaccine effectiveness (VE). Methods. A novel pyrosequencing assay was used to determine genetic group, based on hemagglutinin (HA) gene sequences, of influenza A(H3N2) viruses from patients enrolled at US Influenza Vaccine Effectiveness Network sites. VE was estimated using a test-negative design comparing vaccination among patients infected with influenza A(H3N2) viruses and uninfected patients. Results. Among 9710 enrollees, 1868 (19%) tested positive for influenza A(H3N2) virus; genetic characterization of 1397 viruses showed that 1134 (81%) belonged to 1 HA genetic group (3C.2a) of antigenically drifted influenza A(H3N2) viruses. Effectiveness of 2014–2015 influenza vaccination varied by influenza A(H3N2) virus genetic group from 1% (95% confidence interval [CI], −14% to 14%) against illness caused by antigenically drifted influenza A(H3N2) virus group 3C.2a viruses versus 44% (95% CI, 16%–63%) against illness caused by vaccine-like influenza A(H3N2) virus group 3C.3b viruses. Conclusions. Effectiveness of 2014–2015 influenza vaccination varied by genetic group of influenza A(H3N2) virus. Changes in HA genes related to antigenic drift were associated with reduced VE.

Introduction Pregnant women are at risk for influenza-related complications and have been recommended for vaccination by the Advisory Committee on Immunization Practices (ACIP) since 1990. Annual rates of influenza coverage of pregnant women have been consistently low. The Vaccine Safety Datalink was used to assess influenza vaccine coverage over 10 consecutive years (2002–2012); assess patterns related to changes in ACIP recommendations; identify predictors of vaccination; and compare the results with those published by national U.S. surveys. Methods Retrospective cohort study of 721,898 pregnancies conducted in 2014. Coverage rates were assessed for all pregnancies and for live births only. Multivariate regression analysis identified predictors associated with vaccination. Results Coverage increased from 8.8% to 50.9% in 2002–2012. Seasonal coverage rates increased slowly following the 2004 ACIP influenza vaccine recommendation (to remove the first trimester restriction), but spiked significantly during the 2009 H1N1 influenza pandemic. Significant predictors of vaccination during pregnancy included older age; vaccination in a previous season; high-risk conditions in addition to pregnancy; pregnancy during either the 2004–2005 or 2009–2010 seasons; entering the influenza season after the first trimester of pregnancy; and a pregnancy with longer overlap with the influenza season ( p Conclusions Influenza vaccination coverage among pregnant women increased between the 2002–2003 and 2011–2012 seasons, although it was still below the developmental Healthy People 2020 goal of 80%. The 2004 ACIP language change positively impacted first-trimester vaccination uptake. Vaccine Safety Datalink data estimates were consistent with U.S. estimates.

Hydrogen fuel cells have the potential to dramatically reduce emissions from the energy sector, particularly when integrated into an automotive application. However there are three main hurdles to the commercialisation of this promising technology; one of which is reliability. Current standards require an automotive fuel cell to last around 5000 h of operation (equivalent to around 150,000 miles), which has proven difficult to achieve to date. This hurdle can be overcome through in-depth reliability analysis including techniques such as Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) amongst others. Research has found that the reliability field regarding hydrogen fuel cells is still in its infancy, and needs development, if the current standards are to be achieved. In this work, a detailed reliability study of a Polymer Electrolyte Membrane Fuel Cell (PEMFC) is undertaken. The results of which are a qualitative and quantitative analysis of a PEMFC. The FMEA and FTA are the most up to date assessments of failure in fuel cells made using a comprehensive literature review and expert opinion.

Background Some parents, especially those of children with autism spectrum disorders (ASD), are uncertain about the safety of childhood immunization. We compared rates of fever, febrile seizure and emergency room (ER) visits following measles and pertussis-containing vaccines recommended between ages 4–6 years among children with and without ASD. Methods The study included children who were born between 1995–2012, aged 4–7 years at vaccination, and members of six integrated healthcare delivery systems within the Vaccine Safety Datalink. Children with ASD were defined based on receipt of two separate International Classification of Diseases (ICD)-9 or 10 codes. Outcomes (fever, febrile seizures, and ER visits) were identified in electronic health records. To minimize confounding by unmeasured factors related both to avoidance of vaccination and to outcomes of interest, we compared rates of each outcome between children with and without ASD, in risk and control intervals, by estimating the difference-in-differences on a log scale (i.e. the ratio of rate ratios) using logistic regressions. We also conducted risk interval analyses comparing rates of outcomes in risk intervals and control intervals within each group. Results The study included 14,947 children with ASD and 1,650,041 children without ASD. After measles or pertussis-containing vaccination, there were no differences in association between the two groups for fever or ER visits (Table). There were no febrile seizures identified among children with ASD. Within the ASD group, rates of fever, seizure or ER visits did not differ significantly between the risk and control intervals after vaccination. However, among the non-ASD group, measles and pertussis-containing vaccines were associated with higher rates of fever and seizure in risk intervals compared to controls intervals. Pertussis-containing vaccines were associated with increased risk of ER visits in risk interval compared to control interval (Table). Conclusion We found no difference in the risk of fever, and ER visits comparing children with autism to children without autism after measles or pertussis-containing vaccines. The study provides some reassurance that these vaccines are not less safe in children with ASD. Disclosures Lei Qian, PhD, GlaxoSmithKlein (Research Grant or Support) Nicola P. Klein, MD, PhD, GSK group of companies (Research Grant or Support)Merck (Grant/Research Support)Pfizer (Grant/Research Support)Protein Science (now SP) (Grant/Research Support)Sanofi Pasteur (Grant/Research Support)

Objective This study investigated synergy of commonly co-occurring pairs of childhood traumas/adversities to determine: 1) if synergistic pairings differ by gender and/or age grouping; and 2) if some traumas/adversities were more synergistically reactive. Methods A sample of 10,355 clinic-referred youth (1.5–18 years) from the National Child Traumatic Stress Network Core Data Set was divided by gender and categorized into salient age groups (1.5−5 years, 6−12 years, and 13−18 years). Attributable Proportion (AP), a biomedically relevant metric, was calculated to assess additive synergy for behavior problems on the CBCL. Results Overall, only four pairs of adversities were synergistic. Three involved sexual abuse with physical abuse, parental loss, and domestic violence. When the sample was analyzed by Gender X Age group, however, a more complicated picture emerges. Twelve of the twenty-one possible pairings (57 %) show additive synergy in one or more categories. The mean AP accounted for approximately 40 % of outcome variance. Males had more synergistic pairings (16) than females (7). The average synergistic effect was higher for males (42 % of variance) than females (36 % of variance). The vast majority of synergy occurs in the 6−12 and 13−18 age groups. Sexual abuse was the most synergistically reactive trauma, pairing most frequently (16) followed by physical abuse (10) or neglect (9). Conclusion Sexual abuse was malignantly synergistic, frequently pairing with other adversities, followed by physical abuse, neglect, and domestic violence. The findings underscore that all ACEs are not equal in their contributions to commonly assessed outcomes. The findings also have considerable implications for prevention, intervention, and future research.

Establishing accurate predictions for the reliability of fuel cell operation is critical for comparative performance evaluation of these new with existing power generation mechanisms. Fuel cells, in particular polymer electrolyte fuel cells (PEMFCs), are an emerging technology to potential replace internal combustion engines with the benefits of reducing carbon emissions. Current issues relate to modelling of the degradation mechanisms limiting subsequent accurate reliability prediction. Though common reliability techniques such as Failure Mode and Effect Analysis (FMEA) have been used to further the understanding of the failure modes within the fuel cell system and Fault Tree Analysis (FTA) used to quantify the likelihood of a reduction in performance via voltage drop due to failures, modelling system level reliability and degradation still needs more research. The inherent complexity of a PEMFC system assembly, harbouring dependencies between multiple failure modes, limits the accuracy of FTA. This paper presents a comprehensive Petri-Net model integrated with a 0-D fuel cell performance model of the fuel cell system to develop a more accurate degradation model. The results show the applicability of this novel hybrid method for reliability analysis, in this instance with application to PEMFCs, but with merit for application in other degradation domains.

In this study, a sensor selection technique is proposed to identify various system faults including polymer electrolyte membrane (PEM) fuel cell stack faults and faults of ancillary systems, thus improving system reliability and durability. With proposed technique, the information in sensors could be investigated without fuel cell numerical model, and sensors more sensitive to the fuel cell system performance change could be identified for reliable fault diagnosis. Moreover, the reliability of sensors can be evaluated during the system operation with proposed technique. The performance of selected sensors with proposed technique in identifying fuel cell system faults is investigated using test data from a PEM fuel cell system, where the data-driven fault diagnostic framework is applied. Results demonstrate that with the selected sensors, different levels of fuel cell stack faults can be distinguished with good quality, and the sensor faults can also be identified during the fuel cell operation. Therefore, the proposed sensor selection technique can be beneficial in practical PEM fuel cell systems for the identification of various system faults, from which mitigation strategies could be taken to improve the system reliability and durability, while the maintenance cost could be reduced by avoiding unnecessary system stop and maintenance actions.

Families experience multiple stressors as a result of military service. The purpose of this study was to investigate the associations among service member deployment experiences, family and military factors, and children's mental health using baseline data from the Millennium Cohort Family Study, a study designed to evaluate the health and mental health effects of military service on families, including children.This study examined administrative data on deployment status (combat, noncombat, and no deployments), as well as service member- and spouse-reported data on deployment experiences and family functioning in relation to the mental health of children in the family who were aged 9 to 17 years.Most children were not reported to have mental health, emotional, or behavioral difficulties regardless of parental deployment status. For an important minority of children, however, parental deployments with combat, compared with those with no deployment, were associated with a parental report of attention-deficit disorder/attention-deficit hyperactivity disorder and depression as diagnosed by a clinical provider, after accounting for demographics, psychosocial context, and military factors. Children's odds of a parental report of depression were significantly higher in both the combat and the noncombat deployment groups than in the no deployment group.These findings extend our understanding of the association between parental deployments and children's mental health, with implications for services and training mental health providers serving military families.

Automated Guided Vehicles (AGVs) are playing increasingly vital roles in a variety of applications in modern society, such as intelligent transportation in warehouses and material distribution in automated production lines. They improve production efficiency, save labour cost, and bring significant economic benefit to end users. However, to utilise these potential benefits is highly dependent on the reliability and availability of the AGVs. In other words, an effective maintenance strategy is critical in the application of AGVs. The research activity reported in this paper is to realise an effective maintenance strategy for a multi-AGV system by the approach of Genetic Algorithms (GA). To facilitate the research, an automated material distribution system consisting of three AGVs is considered in this paper for methodology development. The movement of every AGV in the multi-AGV system, and the corrective and periodic preventive maintenances of failed AGVs are modelled using the approach of Coloured Petri Nets (CPNs). Then, a GA is adopted for optimising the maintenance and associated design and operation of the multi-AGV system. From this research, it is disclosed that both the location selection of the maintenance site and the maintenance strategies that are adopted for AGV maintenance have significant influences on the efficiency, cost, and productivity of a multi-AGV system.

© 2018 Taylor & Francis Group, London. Tool wear in machining processes can have a detrimental impact upon the surface finish of a machined part, increase the energy consumption during manufacture and potentially, if the tool fails completely, damage incurred may require the part to be scrapped. Monitoring of the tools condition can therefore lead to preventative steps being taken to avoid excessively worn tools being used during machining, which could cause a part becoming damaged. Several studies have been devoted to condition monitoring of the machining process, including the evaluation of cutting tool condition. However, these methods are either impractical for a production environment due to lengthy monitoring time, or require knowledge of cutting parameters (e.g. spindle speed, feed rate, material, tool) which can be difficult to obtain. In this study, we aim to investigate if tool wear can be directly identified using features extracted from the electrical power signal of the entire Computer Numerical Control (CNC) machine (three phase voltage and current) captured at 50 KHz, for different cutting parameters. Wavelet packet transform is applied to extract the feature from the raw measurement under different conditions. By analyzing the energy and entropy of reconstructed signals at different frequency sub-bands, the tool wear level can be evaluated. Results demonstrate that with the selected features, the effects due to cutting parameter variation and tool wear level change can be discriminated with good quality, which paves the way for using this technique to monitor the machining process in practical applications.

In light of waning immunity to pertussis following receipt of tetanus toxoid, reduced diphtheria toxoid and acellular pertussis (Tdap) vaccine, maintaining protection may require repeated Tdap vaccination. We evaluated the safety of repeated doses of tetanus-containing vaccine in 68 915 nonpregnant adolescents and adults in the Vaccine Safety Datalink population who had received an initial dose of Tdap. Compared with 7521 subjects who received a subsequent dose of tetanus toxoid, reduced diphtheria (Td) vaccine, the 61 394 subjects who received a subsequent dose of Tdap did not have significantly elevated risk of medical visits for seizure, cranial nerve disorders, limb swelling, pain in limb, cellulitis, paralytic syndromes, or encephalopathy/encephalitis/meningitis. These results suggest that repeated Tdap vaccination has acceptable safety relative to Tdap vaccination followed by Td vaccination.

Background Statin medications have immunomodulatory effects. Several recent studies suggest that statins may reduce influenza vaccine response and reduce influenza vaccine effectiveness (VE). Methods We compared influenza VE in statin users and nonusers aged ≥45 years enrolled in the US Vaccine Effectiveness Network study over 6 influenza seasons (2011-2012 through 2016-2017). All enrollees presented to outpatients clinics with acute respiratory illness and were tested for influenza. Information on vaccination status, medical history, and statin use at the time of vaccination were collected by medical and pharmacy records. Using a test-negative design, we estimated VE as (1 - OR) × 100, in which OR is the odds ratio for testing positive for influenza virus among vaccinated vs unvaccinated participants. Results Among 11692 eligible participants, 3359 (30%) were statin users and 2806 (24%) tested positive for influenza virus infection; 78% of statin users and 60% of nonusers had received influenza vaccine. After adjusting for potential confounders, influenza VE was 36% (95% confidence interval [CI], 22%-47%) among statin users and 39% (95% CI, 32%-45%) among nonusers. We observed no significant modification of VE by statin use. VE against influenza A(H1N1)pdm09, A(H3N2), and B viruses were similar among statin users and nonusers. Conclusions In this large observational study, influenza VE against laboratory-confirmed influenza illness was not affected by current statin use among persons aged ≥45 years. Statin use did not modify the effect of vaccination on influenza when analyzed by type and subtype.

Introduction Infection with hepatitis A virus (HAV) during pregnancy, although uncommon, is associated with gestational complications and pre-term labor. Hepatitis A vaccine (HepA) is recommended for anyone at increased risk for contracting hepatitis A, including women at risk who are also pregnant. Limited data are available on the safety of maternal HepA vaccination. Objectives Assess the frequency of maternal HepA receipt and evaluate the potential association between maternal vaccination and pre-specified maternal and infant safety outcomes. Methods A retrospective cohort of pregnancies in the Vaccine Safety Datalink (VSD) resulting in live births from 2004 through 2015 was included. Pregnancies with HepA exposure were compared to those with other vaccine exposures, and to those with no vaccine exposures. Risk factors for contracting hepatitis A were identified up to one-year prior to or during the pregnancy using ICD-9 codes. Maternal and fetal adverse events were evaluated according to maternal HepA exposure status. Adjusted odds ratio (OR) were used to describe the association. Results Among 666,233 pregnancies in the study period, HepA was administered at a rate of 1.7 per 1000 (n = 1140), most commonly within the first six weeks of pregnancy. Less than 3% of those exposed to HepA during pregnancy had an ICD-confirmed risk factor. There were no significant associations between HepA exposure during pregnancy and gestational hypertension, gestational diabetes, pre-eclampsia/eclampsia, cesarean delivery, pre-term delivery, and low birthweight. There was a statistically significant association between HepA exposure during pregnancy and small-for-gestational age (SGA) infants (aOR 1.32, [95% CI 1.09, 1.60], p = 0.004). Conclusions The rate of maternal HepA vaccination was low and rarely due to documented risk factors for vaccination. HepA vaccination during pregnancy was not associated with an increased risk for a range of adverse events examined among pregnancies resulting in live births, but an identified association between maternal HepA and SGA infant outcomes, while likely due to unmeasured confounding, warrants further exploration.

Background In the United States, seasonal inactivated influenza vaccine (IIV) is recommended for pregnant women; however, in early 2009, immunization rates were low, partly due to limited prospective data and concerns about vaccine safety. Objective We conducted a randomized study of two licensed seasonal trivalent IIVs (IIV3) to assess their safety and immunogenicity in pregnant women. Study Design In this prospective, randomized clinical study, 100 pregnant women, 18–39 years of age and ≥14 weeks gestation received a single intramuscular dose of 2008–2009 Fluzone® or Fluarix®. Injection site and systemic reactions were recorded for 7 days after vaccination and serious adverse events (SAEs) and pregnancy outcomes were documented. Serum samples collected before and 28 days after vaccination were tested for hemagglutination inhibition (HAI) antibody levels. Results The majority of the injection site and systemic reactions were mild and self-limited after both vaccines. No fever ≥100 °F was reported. There were no vaccine-associated SAEs. Immune responses to influenza vaccine antigens were similar for the two study vaccines, with robust HAI responses against influenza A strains, and relatively lower responses for influenza B strains. Conclusion Seasonal inactivated influenza vaccines were well tolerated and immunogenic in pregnant women. ClinicalTrials.gov identifier NCT00905125. Synopsis: In this prospective clinical trial, we demonstrated that immunization with seasonal trivalent, inactivated influenza vaccine in the second and third trimester of pregnancy is immunogenic and safe.

Background The 13-valent pneumococcal conjugate vaccine (PCV13) and the 23-valent pneumococcal polysaccharide vaccine (PPSV23) were both recommended to adults aged ≥65 years. The study examines adults ≥65 years for risk of adverse events (AEs) requiring medical attention following vaccination with PCV13 as compared with vaccination with PPSV23, a long-standing vaccine with a satisfactory safety profile. Methods The cohort study included 6 Vaccine Safety Datalink sites. The exposed person-time included follow-up time of the first PCV13 received by subjects age ≥65 years from January 1 to August 15, 2015. The comparator person-time included follow-up time after the first PPSV23 received by subjects of the same age during Janaury 1 to August 15 of each year of 2011–2015. The prespecified AEs included cardiovascular events, Bell’s palsy, Guillain-Barré syndrome, syncope, erythema multiforme, thrombocytopenia, cellulitis and infection, allergic reaction, and anaphylaxis. Inverse probability of treatment weighting–adjusted Poisson regression models was used to estimate the relative risk (RR) of each AE. Results A total of 313 136 doses of PCV13 and 232 591 doses of PPSV23 were included. The adjusted RRs comparing the incidence of AEs following PCV13 vs PPSV23 were all Conclusions These data do not support an increased rate of adverse events following PCV13 administration in elders compared with PPSV23 and should provide reassurance regarding continued use of PCV13.

Everyday there are growing pressures to ensure that services are delivered efficiently, with high levels of quality and with acceptability of regulatory standards. For the Police Force, their service requirement is to the public, with the police officer presence being the most visible product of this criminal justice provision. Using historical data from over 10 years of operation, this research demonstrates the benefits of using data mining methods for knowledge discovery in regards to the crime and incident related elements which impact on the Police Force service provision. In the UK, a Force operates over a designated region (macro-level), which is further subdivided into Beats (micro-level). This research also demonstrates differences between the outputs of micro-level and macro-level analytics, where the lower level analysis enables adaptation of the operational Policing strategy. The evidence base provided through the analysis supports decisions regarding further investigations into the capability of flexible neighbourhood policing practices; alongside wider operations i.e. optimal officer training times.

Altered structural connectivity has been identified as a possible biomarker of autism spectrum disorder (ASD) risk in the developing brain. Core features of ASD include impaired social communication and early language delay. Thus, examining white matter tracts associated with language may lend further insight into early signs of ASD risk and the mechanisms that underlie language impairments associated with the disorder. Evidence of altered structural connectivity has previously been detected in 6-month-old infants at high familial risk for developing ASD. However, as language processing begins in utero, differences in structural connectivity between language regions may be present in the early infant brain shortly after birth. Here we investigated key white matter pathways of the dorsal language network in 6-week-old infants at high (HR) and low (LR) risk for ASD to identify atypicalities in structural connectivity that may predict altered developmental trajectories prior to overt language delays and the onset of ASD symptomatology. Compared to HR infants, LR infants showed higher fractional anisotropy (FA) in the left superior longitudinal fasciculus (SLF); in contrast, in the right SLF, HR infants showed higher FA than LR infants. Additionally, HR infants showed more rightward lateralization of the SLF. Across both groups, measures of FA and lateralization of these pathways at 6 weeks of age were related to later language development at 18 months of age as well as ASD symptomatology at 36 months of age. These findings indicate that early differences in the structure of language pathways may provide an early predictor of future language development and ASD risk.

Home healthcare systems have become a focus of research due to the shifting care requirements of the elderly. Malnourishment, independence and activity are becoming vital metrics when monitoring in patient’s illness. Monitoring devices described in research however express issues in the consistent remote capture of these metrics. This work presents the role of Bluetooth Low-Energy Beacons (BLE) in community based healthcare by examining how passive activity monitoring can assist patients coping with independence and disease management within their homes as an Indoor Proximity System (IPS). BLE sensors will be placed on the patient, in their home and on objects of interest (OOI) such as water bottles, kettles and microwaves. Research described in this paper will focus on accuracy of BLE beacons as an IPS for lifestyle monitoring and its application to intelligent healthcare. This is achieved by creating a model of patient care requirements structured using activities of daily living (ADL) which is evaluated using patient activity pattern recognition in captured sensor data. Pattern analysis uses the changing distance values between BLE sensors to determine movement, motion and location which contribute to the activity, sensor based care model. Results support efficacy when using BLE beacons as an IPS with patient activity patterns becoming observable through monitoring with a consistent ability to distinguish interactions in activity patterns captured. Future experiments will focus on analysing captured sensor metrics to determine care outcomes.

In this research, we utilize semantic technology for robust early diagnosis and decision support. We present a light-weight platform that provides the enduser with direct access to the data through an ontology, and enables detection of any forthcoming faults by considering the data only from the reliable sensors. Concurrently, it indicates the actual sources of the detected faults, enabling mitigation action to be taken. Our work is focused on systems that require only real-time data and a restricted part of the historic data, such as fuel cell stack systems. First, we present an upper-level ontology that captures the semantics of such monitored systems and then we present the structure of the platform. Next, we specialize on the fuel cell paradigm and we provide a detailed description of our platform’s functionality that can aid future servicing problem reporting applications.

Background MMR vaccine is given routinely to young children but may be given at other ages. We described MMR use in adolescent and adult populations in the Vaccine Safety Datalink (VSD) and estimated the incidence of medically-attended outcomes after MMR to inform future studies estimating vaccine-associated risk. Methods The study population included adolescents (9–17 years) and adults (≥18 years) in VSD who received at least one MMR vaccine from 2010 through 2016. Outcomes were pre-specified based on previous vaccine safety studies and categorized as clinically serious (anaphylaxis, encephalitis/myelitis, GBS, meningitis, seizure) or non-serious (allergic reaction, arthropathy, fever, injection site reaction, lymphadenopathy, nonspecific reaction, parotitis, rash, syncope). Outcomes were identified by searching for ICD-9 and ICD-10 diagnosis codes in post-vaccination exposure windows. Medical records were reviewed for all serious outcomes to verify incident diagnoses. Incidence and 95% confidence intervals were calculated for validated serious and all non-serious outcomes. Results 146,503 adolescents and adults received 162,992 MMR vaccines during the study period. The mean age at vaccination was 33.7 years, 65% were female, and 53% received at least one other vaccine simultaneously. Demographic and vaccination characteristics varied across age groups (Table 1). The analysis of post-vaccination outcomes included 162,053 MMR vaccinations. The incidence of validated serious outcomes was low, ranging from 0 to 6.8 per 100,000 vaccinations. Only one serious outcome (anaphylaxis) was noted to be vaccine-associated in the medical record. Incidence of clinically non-serious outcomes varied from 0.4 to 56.0 per 10,000 vaccinations. Injection site reactions were more common among adolescents (118.1 per 10,000 vaccinations), who also had a higher frequency of simultaneous vaccination (80%). Conclusion Clinically serious outcomes were rare following MMR vaccination. Rates of clinically non-serious outcomes varied but were similar to or lower than previous reports in children. This descriptive analysis did not evaluate the association between MMR and adverse events. Future analysis with an appropriate comparison group is needed for risk estimation. Disclosures All authors: No reported disclosures.

Background Live attenuated influenza vaccine (LAIV) and inactivated influenza vaccine (IIV) are both licensed for administration to nursing mothers. Little is known about the potential for transmission of LAIV viruses from the mother to the infant and the comparative breast milk antibody responses to LAIV and IIV. Methods We performed a randomized, double-blind study comparing the immunogenicity of LAIV to IIV when administered to nursing mothers. The safety of LAIV to IIV in women and their infants was also compared. Women received LAIV + intramuscular placebo, or IIV + intranasal placebo on Day 0. Breast milk and nasal swabs (from women and infants) were collected on Days 0, 2, and 8 for detection of LAIV. Breast milk and serum antibody responses were measured at Days 0 and 28. The primary hypothesis was that LAIV would provide superior induction of breast milk IgA responses to influenza as compared to IIV when administered to nursing mothers. Results Breast milk IgG, breast milk IgA (H1N1 only), serum hemagglutination inhibition (HAI), and serum IgG responses were significantly higher following administration of IIV compared to LAIV. Receipt of either LAIV or IIV was safe in women and their infants. One (1%) LAIV recipient transmitted vaccine virus to her infant who remained well. No influenza virus was detected in breast milk. Conclusions Breast milk and serum antibody responses were higher for IIV compared to LAIV. LAIV and IIV were safe for nursing women but there was one (1%) possible transmission of LAIV to an infant. This study suggests that IIV may be the preferred vaccine for nursing mothers.

Objective In-depth example of two new group sequential methods for postmarket safety monitoring of new medical products. Study Design and Setting Existing trial-based group sequential approaches have been extended to adjust for confounders, accommodate rare events, and address privacy-related constraints on data sharing. Most adaptations have involved design-based confounder strategies, for example, self-controlled or exposure matching, while analysis-based approaches like regression and weighting have received less attention. We describe the methodology of two new group sequential approaches that use analysis-based confounder adjustment (GS GEE) and weighting (GS IPTW). Using data from the Food and Drug Administration's Sentinel network, we apply both methods in the context of a known positive association: the measles-mumps-rubella-varicella vaccine and seizure risk in infants. Results Estimates from both new approaches were similar and comparable to prior studies using design-based methods to address confounding. The time to detection of a safety signal was considerably shorter for GS IPTW, which estimates a risk difference, compared to GS GEE, which provides relative estimates of excess risk. Conclusion Future group sequential safety surveillance efforts should consider analysis-based confounder adjustment techniques that evaluate safety signals on the risk difference scale to achieve greater statistical power and more timely results.

A polymer electrolyte membrane (PEM) fuel cell is a power generation device that transforms chemical energy contained within hydrogen and oxygen gases into useful electricity. The performance of a PEMFC unit is governed by three interdependent physical phenomena: heat, mass, and charge transfer. When modelling such a multi-physical system it is advantageous to use an approach capable of representing all the processes in a unified fashion. This paper presents a component-based model of PEMFCs developed using the bond graph (BG) technique in Modelica language. The basics of the BG method are outlined and a number of relevant publications are reviewed. Model assumptions and necessary equations for each fuel cell component are outlined. The overall model is constructed from a set of bond-graphic blocks within thermal, pneumatic and electrical domains. The model output was compared with the experimental data gathered from a two-cell stack and demonstrated a good accuracy in predicting system behaviour. In the future the designed model will be used for fuel cell reliability studies.

Background There have been inconsistent reports of decreased vaccine effectiveness (VE) against influenza viruses among older adults (aged ≥ 65 years) compared with younger adults in the United States. A direct comparison of VE over multiple seasons is needed to assess the consistency of these observations. Methods We performed a pooled analysis of VE over 5 seasons among adults aged ≥ 18 years who were systematically enrolled in the U.S. Flu VE Network. Outpatients with medically-attended acute respiratory illness (cough with illness onset ≤ 7 days prior to enrollment) were tested for influenza by reverse transcription polymerase chain reaction. We compared differences in VE and vaccine failures among older adult age group (65–74, ≥75, and ≥ 65 years) to adults aged 18–49 years by influenza type and subtype using interaction terms to test for statistical significance and stratified by prior season vaccination status. Results Analysis included 20,022 adults aged ≥ 18 years enrolled during the 2011–12 through 2015–16 influenza seasons; 4,785 (24%) tested positive for influenza. VE among patients aged ≥ 65 years was not significantly lower than VE among patients aged 18–49 years against any subtype with no significant interaction of age and vaccination. VE against A(H3N2) viruses was 14% (95% confidence interval [CI] −14% to 36%) for adults ≥ 65 years and 21% (CI 9–32%) for adults 18–49 years. VE against A(H1N1)pdm09 was 49% (95% CI 22–66%) for adults ≥ 65 years and 48% (95% CI 41–54%) for adults 18–49 years and against B viruses was 62% (95% CI 44–74%) for adults ≥ 65 years and 55% (95% CI 45–63%) for adults 18–49 years. There was no significant interaction of age and vaccination for separate strata of prior vaccination status. Conclusions Over 5 seasons, influenza vaccination provided similar levels of protection among older and younger adults, with lower levels of protection against influenza A(H3N2) in all ages.

SUMMARYNon-steroidal anti-inflammatory drugs (NSAIDs) may inhibit antibody production by peripheral blood mononuclear cells; one consequence of this could be decreased effectiveness of vaccines in NSAID users. Because many older adults use low-dose aspirin for primary or secondary prevention of coronary events, any inhibitory effect of aspirin on vaccine immune response could reduce the benefits of vaccination programmes in older adults. We tested whether immune response to vaccination differed between users vs. non-users of low-dose aspirin, using data from four randomized trials of monovalent 2009 pandemic influenza A(H1N1) vaccine. Geometric mean haemagglutination inhibition antibody titres were not significantly lower in low-dose aspirin users compared to non-users. Our results provide reassurance that influenza vaccination effectiveness is probably not reduced in older adults taking chronic low-dose aspirin.