Converter based electrochemical impedance spectroscopy for fuel cell stacks

Fuel cells are important devices in a hydrogen-based chain of energy conversion. They have distinctive advantages over batteries with their higher energy density and faster refueling speed, which make them attractive in stationary power supplies and heavy-duty vehicles. However, the high cost and low durability associated with modern fuel cells are still hindering their wider commercialization. Besides developing more reliable and lower cost materials and advanced assemblies of cells and stacks, a practical and effective diagnostic tool is highly needed for fuel cells to identify any abnormal internal conditions and assist with maintenance scheduling or application of on-board mitigating schemes. Conventionally, linear instruments were used for fuel cell EIS, however, limited to single cells or short stacks only as a laboratory testing method. With recent developments, EIS enabled by switching power converters are capable of being applied to a high-power stack directly. This approach has the potential for practical field applications such as a servicing tool for fuel cell manufacturers or an on-board diagnostic tool of a moving vehicle. Previous works on converter based EIS have made a few different attempts at conceptually realizing this solution while several significant issues were not well recognized and resolved yet. As such, this thesis explores further on this topic to address the flexibility of EIS perturbation generation, the perturbation frequency range, and the linkage between fuel cell EIS requirements and the converter design to push for its readiness for practical implementations. Several new solutions are proposed and discussed in detail, including a total software approach for existing high-power converters to enable wide-frequency-range EIS, a redesign of the main dc/dc converter enabling wide-frequency-range perturbations, and a separate auxiliary converter as a standalone module for EIS operation. A detailed analysis of oscillations brought by converter based EIS in powertrains is also presented

Accuracy improvement of fuel cell prognostics based on voltage prediction

Proton exchange membrane fuel cell (PEMFC) is a promising hydrogen technique with various application prospects. However, all the PEMFCs are subject to degradation resulting from mechanical and chemical aging. To tackle this challenge, accurately predicting fuel cell degradation is essential for its durability optimization. In this study, an enhanced data-driven prognostic framework is developed to accurately predict short-term and medium-term degradation using only fuel cell voltage as the input feature. Firstly, a local outlier factor (LOF) algorithm is adopted for automatic detection of outliers in raw data collected from actual sensing environments. Then, an advanced deep learning model, residual–CNN–LSTM-random attention, is proposed to optimize voltage prediction to better indicate future PEMFC degradation trend. The proposed work is validated by the IEEE PHM 2014 Data Challenge. Compared to state-of-the-art methods, the proposed framework provides superior prediction accuracies with high stability. For instance, the framework improves short-term prediction, achieving a root mean square error (RMSE) of 0.0021 and a mean absolute percentage error (MAPE) of 0.0323 at steady state when training stops at 600 h. For medium-term prediction, our method also attains better results with an RMSE of 0.0085 and a MAPE of 0.4237 under same working conditions. Additionally, the comparative analyses demonstrate a lower computational burden and higher suitability of proposed work for practical applications

Online systemic energy management strategy of fuel cell system with efficiency enhancement

Temperature plays a crucial role in efficiency improvement and lifespan extension of the fuel cell system which encourages energy management strategy (EMS) taking thermal into consideration. However, sluggish thermal response prevents the fuel cell performance from tracking the optimal states during scenarios with significant power variations, which was disregarded in the previous works. To solve this issue, an online hydrogen consumption minimization guarantee strategy (HCMG) including thermal management is proposed which is divided into two parts: 1) primary power distribution strategy, where a model predictive control (MPC) based EMS is employed herein to distribute power between fuel cell and battery with the objectives of minimizing hydrogen consumption as well as maintaining the state of charge (SOC), and 2) HCMG, where a modified MPC based method is exploited herein to track the reference power and optimal temperature with minimum hydrogen consumption by adjusting both the duty cycle of fan and fuel cell current. The presented approach ascertains hydrogen consumption reduction for 3.448% even under relatively extensive power changes, during which the temperature cannot reach the optimal value in a brief time. The real-time simulation results show the effectiveness of the proposed technique compared with previous EMS methods under various driving cycles

Identifying Interprofessional Global Health Competencies for 21st-Century Health Professionals

Background: At the 2008 inaugural meeting of the Consortium of Universities for Global Health (CUGH), participants discussed the rapid expansion of global health programs and the lack of standardized competencies and curricula to guide these programs. In 2013, CUGH appointed a Global Health Competency Subcommittee and charged this subcommittee with identifying broad global health core competencies applicable across disciplines. Objectives: The purpose of this paper is to describe the Subcommittee's work and proposed list of interprofessional global health competencies. Methods: After agreeing on a definition of global health to guide the Subcommittee's work, members conducted an extensive literature review to identify existing competencies in all fields relevant to global health. Subcommittee members initially identified 82 competencies in 12 separate domains, and proposed four different competency levels. The proposed competencies and domains were discussed during multiple conference calls, and subcommittee members voted to determine the final competencies to be included in two of the four proposed competency levels (global citizen and basic operational level – program oriented). Findings: The final proposed list included a total of 13 competencies across 8 domains for the Global Citizen Level and 39 competencies across 11 domains for the Basic Operational Program-Oriented Level. Conclusions: There is a need for continued debate and dialog to validate the proposed set of competencies, and a need for further research to identify best strategies for incorporating these competencies into global health educational programs. Future research should focus on implementation and evaluation of these competencies across a range of educational programs, and further delineating the competencies needed across all four proposed competency levels

The association between Toll-like receptor 2 single-nucleotide polymorphisms and hepatocellular carcinoma susceptibility

<p>Abstract</p> <p>Background</p> <p>Toll-like receptors (TLR) are key innate immunity receptors participating in an immune response. Growing evidence suggests that mutations of TLR2/TLR9 gene are associated with the progress of cancers. The present study aimed to investigate the temporal relationship of single nucleotide polymorphisms (SNP) of TLR2/TLR9 and the risk of hepatocellular carcinoma (HCC).</p> <p>Methods</p> <p>In this single center-based case-control study, SNaPshot method was used to genotype sequence variants of TLR2 and TLR9 in 211 patients with HCC and 232 subjects as controls.</p> <p>Results</p> <p>Two synonymous SNPs in the exon of TLR2 were closely associated with risk of HCC. Compared with those carrying wild-type homozygous genotypes (T/T), risk of HCC decreased significantly in individuals carrying the heterozygous genotypes (C/T) of the rs3804099 (adjusted odds ratio (OR), 0.493, 95% CI 0.331 - 0.736, <it>P </it>< 0.01) and rs3804100 (adjusted OR, 0.509, 95% CI 0.342 - 0.759, <it>P </it>< 0.01). There was no significant association found in two TLR9 SNPs concerning the risk of HCC. The haplotype TT for TLR2 was associated significantly with the decreased risk of HCC (OR 0.524, 95% CI 0.394 - 0.697, <it>P </it>= 0.000). Inversely, the risk of HCC increased significantly in patients with the haplotype CC (OR 2.743, 95% CI 1.915 - 3.930, <it>P </it>= 0.000).</p> <p>Conclusions</p> <p>These results suggested that TLR2 rs3804099 C/T and rs3804100 C/T polymorphisms were closely associated with HCC. In addition, the haplotypes composed of these two TLR2 synonymous SNPs have stronger effects on the susceptibility of HCC.</p

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

Integrated genomic characterization of oesophageal carcinoma

Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies

Burden of injury along the development spectrum : associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017

Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.Peer reviewe