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We report an inter-laboratory comparison of analytical laboratories involved in the quantification of polycyclic aromatic hydrocarbons (PAHs) collected by sampling organisations from industrial stacks (e.g. waste incinerators). Four reference solutions were prepared containing nominally 10 ng/ml, 50 ng/ml, 200 ng/ml and 500 ng/ml of naphthalene, benzo[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, indeno[1,2,3-cd]pyrene and dibenzo[a,h]anthracene prior to despatch to five analytical laboratories with quantification requested in accordance with ISO 11338-2. Across four of the laboratories (the 5th returned unusable data), significant deviations from the reference concentrations were found frequently in excess of the benchmarks of 37 %—from the validation data in ISO 11338-2—and 21 %—from the Environment Agency for England’s Monitoring Certification Scheme. Also, much of the variance was systemic in nature indicating a possible issue with the quality of some of the stock solutions used by the laboratories for calibration. Whilst more proficiency testing would be welcomed to monitor and improve performance, this should be provided in addition to more support for analytical laboratories. A key mechanism of support is the standards themselves and there is a timely opportunity in that ISO/TC 146/SC 1 are due to revise ISO 11338. Possible improvements include full validation of high performance liquid chromatography and gas chromatography–mass spectrometry methods (to better understand what performance can reasonably be expected from laboratories), a requirement to correct results to individual laboratory PAH extraction efficiency, and a required uncertainty stipulated for the overall method (also aiding setting pass/fail criteria for proficiency testing).

Measurement of the composition of ambient air has become increasingly widespread over the last 50 years as the detrimental health effects of some air pollutants have become clearer and requirements for these measurements has been embedded in national and international legislation. The aim of this has been not only to assess exposure of the general population to air pollutants but also to assess the effectiveness of abatement strategies to reduce emissions of these pollutants at source. With a rich industrial heritage, the Swansea Valley (South Wales, UK) has long been associated with the refining and production of metal products, especially nickel. Despite a decline in output during the latter part of the twentieth century there is still sufficient activity to prompt a requirement for targeted air monitoring in the area. This is most important for nickel where there is a local history of measured concentrations exceeding legislative target values. This work demonstrates the effectiveness of nickel emissions abatement strategies over the last 50 years by tracking the falling air concentration of nickel over this period. It also demonstrates how the monitoring network in the Swansea Valley has expanded over this time and become significantly more sensitive to nickel emissions. The data presented represents a significant public health achievement - it is likely that the exposure to nickel in air of the population in the Swansea Valley has decreased more than 100-fold over the last 50 years - and reflects the progress in regulation, industrial efficiency, emissions abatement technology and air quality monitoring science achieved during this period.

Infection by (re-)emerging RNA arboviruses including Chikungunya virus (CHIKV) and Mayaro virus primarily cause acute febrile disease and transient polyarthralgia. However, in a significant subset of infected individuals, debilitating arthralgia persists for weeks over months up to years. The underlying immunopathogenesis of chronification of arthralgia upon primary RNA-viral infection remains unclear. Here, we analysed cell-intrinsic responses to ex vivo arthritogenic alphaviral infection of primary human synovial fibroblasts isolated from knee joints, one the most affected joint types during acute and chronic CHIKV disease. Synovial fibroblasts were susceptible and permissive to alphaviral infection. Base-line and exogenously added type I interferon (IFN) partially and potently restricted infection, respectively. RNA-seq revealed a CHIKV infection-induced transcriptional profile that comprised upregulation of expression of several hundred IFN-stimulated and arthralgia-mediating genes. Single-cell virus-inclusive RNA-seq uncovered a fine-tuned switch from induction to repression of cell-intrinsic immune responses depending on the abundance of viral RNA in an individual cell. Specifically, responses were most pronounced in cells displaying low-to-intermediate amounts of viral RNA and absence of virus-encoded, fluorescent reporter protein expression, arguing for efficient counteraction of innate immunity in cells expressing viral antagonists at sufficient quantities. In summary, cell-intrinsic sensing of viral RNA that potentially persists or replicates at low levels in synovial fibroblasts and other target cell types in vivo may contribute to the chronic arthralgia induced by alphaviral infections. Our findings might advance our understanding of the immunopathophysiology of long-term pathogenesis of RNA-viral infections.

This Feature highlights the role of metrology, the science of measurement, in maintaining the infrastructure we all rely on for accurate chemical measurements. In particular, the recent change to the definition of the mole, the unit of chemistry, is explained.

This report describes work to evaluate the performance of different commercial and proprietary cylinder treatments in improving the stability of ammonia reference materials in high pressure cylinders. Gas mixtures of 100 µmol/mol and 10 µmol/mol ammonia in nitrogen were prepared gravimetrically at both NPL and VSL. Comparative measurements at each amount-of-substance fraction were used to assess which passivation technique minimised the loss of ammonia upon preparation. The results indicate little difference between the commercial treatments, except at lower amount-of-substance fractions (10 μmol/mol). The variation observed in performance might be explained by the different abilities of the various treatments to prevent the adsorption of ammonia molecules on the internal surfaces of the cylinder, although the role of residual water on the cylinder surface in reacting with ammonia is unclear.

Biodiesel will provide a significant renewable energy source for transportation in the near future. In the present study, principal component analysis (PCA) has been used to understand the relationship between important properties of biodiesel and its chemical composition. Finally, several artificial intelligence-based models were developed to predict specific biodiesel properties based on their chemical composition. The experimental study was conducted in order to generate training data for the artificial neural network (ANN). Available (experimental) data from the literature was also employed for this modeling strategy. The analytical part of this study found a complex multi-dimensional correlation between chemical composition and biodiesel properties. Average numbers of double bonds in the chemical structure (representing the unsaturated component in biodiesel) and the poly-unsaturated component in biodiesel had a great impact on biodiesel properties. The simulation result in this study demonstrated that ANN is a useful tool for investigating the fuel properties from its chemical composition which eventually can replace the time consuming and costly experimental test.

The cycle-to-cycle variations (CCVs) in reciprocating internal combustion engines may cause negative influence on diving performance, fuel economy, and emissions. Especially, lean-burn technology or exhaust gas recirculation (EGR) was used to improve engine combustion efficiency and reduce NOx, and the combustion boundary was limited by increased CCVs. Therefore, it was important to identify the complex dynamics of CCVs and to take measures for inhibiting them. The CCVs based on indicated mean effective pressure (IMEP) time series were examined in a lean-burn natural gas engine with a non-uniform pre-mixture based on statistical and multifractal theories. Tests were conducted at an engine speed of 1000 rpm and low loads of 10% and 25%, and combustion data at an engine load of 10% were analysed in detail because the CCVs are less sensitive to changes of gas injection timing (GIT) at the higher engine load. The nonlinear dynamics of the CCVs was revealed at the different GIT from 1° to 120°CA ATDC. The statistical properties of IMEP time series were characterised by distributions of probability density functions (PDF), the multifractal complexities of the combustion fluctuations were quantitatively analysed by the singularity spectra in terms of the Holder exponent based on the theory of wavelet transform modulus maxima, and the primary source leading to the increased CCVs and complex dynamics in a natural gas engine with a non-uniform pre-mixture was identified using 3D-computational fluid dynamics simulations. Results show that as the GIT increased, the kurtosis of the IMEP time series systematically decreased from 592 to 1.8, the fast dynamics transitions from super-Gaussian to quasi-Gaussian distributions in combustion system were revealed, and the lower value of kurtosis implied the lower degree of intermittency. Except for the GIT of 60°CA ATDC, the value of the Holder exponent $$h_{0} > 0.5$$ , which implies that the CCVs for the other GITs behaved like a persistent walk or positive correlation. For GITs of 60° and 90°CA ATDC, the narrow broadness of the singularity spectrum implicated a monofractality, while the obvious multifractal properties could be identified for the other GITs. The transitions of the dynamic behaviours may be caused by the degree of mixture in-homogeneity combined with a new mechanism of “prior-cycle effects” proposed in this paper, and the effect mechanism was not only associated with the residual gas in the cylinder but also with the residual gas fuel in the intake port, rather than independent effect of residual gas in cylinder reported in previous researches. Our research results provided the deeper understanding on the dynamics of combustion system in multi-point injection natural gas engines and may be beneficial to achieve nonlinear prediction and to develop improved control strategies for inhibiting the CCVs.

Background: Growing evidence indicates that restrictive criteria for determining eligibility of breast cancer patients for germline genetic testing (e.g. NCCN, etc.) can missa significant number who may benefit from testing. However, the clinical utility and outcomes of patients with germline pathogenic variants (“positive patients”) who fall outside of current criteria has not been studied,and there is limited data on the clinical impact of nonBRCA pathogenic variantsin patients who fall inside testing criteria. We present longitudinal data from a previous cohort of patients, who are being followed in a new genetics registry that correlates germlinetest results with impact on clinical decision making, disease status, treatmentcourse, clinical trial enrollment and overall survival. Methods: A large multi-center IRB approved prospective Registry initiated in 2017 collected andanalyzed data on 959 breast cancer patients, newly or previously diagnosed, atthe time of genetic test result return (Beitsch et al. JCO 2018)1.This abstract presents clinical data over the intervening 18-24 months on patients with positive variants (83) both in-criteria (IC) and out-of-criteria (OOC),collected via medical record review as part of the iGAP Registry(igapregistry.org), sponsored by Medneon (Cupertino, Ca). Results: Of the 44 positive patients for whom longitudinalclinical outcomes data have been analyzed to date, 24 met guidelines fortesting and 20 did not. 6 had a history of additional primary cancers at thetime of testing. 40/44 patients are disease free; of these 20 were IC,20 were OOC. 1/44 has stable disease and was OCC. 3/44 have progressive orrecurrent breast cancer and 2 were OCC and 1 was IC. 13/44received chemotherapy; 6 IC and 7 OOC. 5 patients (with mutations in BRCA1,BRCA2, PALB2, MUTYH) received carboplatin consistent with the sensitivity toplatinum agents conferred by deficiencies in homologous recombination (HR) andbase-excision repair (BER). Longitudinal outcomes stratified by gene result arein Table 1. Conclusions:This studyprovides initial evidence for the impact of germline genetic test results onlongitudinal patient outcomes, stratified by gene. It also begins to correlategermline results and chemotherapy, as 3/5 OOC patients receiving carboplatinhad mutations in HR or BER genes. This raises the possibility that certain treatment advantages and other beneficial changes in management could bewithheld from OOC patients if restrictive criteria persist, as well as limiting the opportunities for possible preventive interventions for their at-risk family members 1. BeitschPD, Whitworth PW, Hughes K, et al. Underdiagnosis of Hereditary Breast Cancer:Are Genetic Testing Guidelines a Tool or an Obstacle?. J Clin Oncol.2019;37(6):453-460. doi:10.1200/JCO.18.01631 Table 1Positive Gene Variant# reported mutations-by geneSubject Health Status Disease FreeSubject Health Status Stable or Progressive DiseaseNCCN # ICNCCN # OOCATM22002BLM11001BRCA122020BRCA255041CHEK266033DIS3L211001FH11010MITF11010MSH611001MUTYH98127NBN22011NF110101NTLH111001PALB232121RAD5011010RAD51C22011RAD51D32112RECQL422011VHL11010 Citation Format: Peter Beitsch, Rakesh Patel, Pat Whitworth, Barry Rosen, Rick Brown, Gia Compagnoni, Linsey Gold, Ian Grady, Edward Esplin, Sarah Nielsen, Max Brown, Melissa Trudrung, Chloe Wernecke, Mary Kay Hardwick, Robert Nussbaum. Longitudinal clinical outcomes of a multi-center universal genetic testing registry [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS8-30.

The effect of rounding when presenting the uncertainties associated with bespoke gas certified reference materials has been investigated. This has been examined in the context of wanting to provide the customer with as close a match as possible to what was originally contracted whilst needing to comply with the minimum uncertainties allowed by internationally agreed calibration and measurement capabilities under the International Committee for Weights and Measures’ Mutual Recognition Arrangement or other scopes of accreditation. The effect of rounding has, in relative terms, been shown to be large in some cases and this has prompted an investigation into improved methods to express more precisely values presented on certificates accompanying bespoke gas certified reference materials. This has included a new proposal to present relative, instead of absolute, uncertainties on certificates thereby matching exactly customer requirements. This Practitioner’s Report also demonstrates how considerations of customer and quality system requirements should be properly balanced and how internal review of technical procedures leads to continuous improvement.

Recent developments in nanotechnology and engineering have produced a plethora of nanomaterials with amazing physical/chemical properties and enhanced sensing potential for various heavy metals in the environment. Noble metal nanoparticles (NPs), particularly those made from gold and silver, have attracted a great deal of attention mainly due to ease of synthesis, a high degree of surface functionalization, biocompatibility, and tunable physico-chemical properties. The use of noble metal nanoparticles has enabled fast and multiplexed detection of metal ions with excellent sensitivity and selectivity. The optical characteristics of Au–Ag NPs and noble metal-based nanozymes enable the detection of metals based on colorimetry. Color changes of these metal nanoparticles upon interaction with lead ions are based on inter-particle interactions (aggregation/dis-aggregation) and changes in surface modification. This review presents up-to-date information on the applications of noble metal NPs in the colorimetric sensing of lead (Pb2+) ions with special attention on selectivity, sensitivity, and practicality. The extensive potential of noble metal nanomaterials as the next-generation and on-site sensing tools has been explored for the rapid detection of lead ions in environmental matrices.

Tandem inductively coupled plasma mass spectrometry (ICP-MS/MS) with collision/reaction cell capability can achieve highly effective separation of spectral interferences. This improves confidence in measurement, reduces the detection limits achievable and expands the number of isotopes measurable in a range of industries, including semi-conductor, pharmaceutical, environmental, food and nuclear. Amongst the range of cell gases tested, hydrogen (H2) has proven to be an effective cell gas, either used alone or in combination with other gases. This study demonstrates the benefits of using H2 in combination with ICP-MS/MS for improved detection of stable and radioactive pollutants of interest to a number of technical disciplines. This is presented through several case studies considering stable (35Cl, 40Ca, 56Fe, Ni isotopes) and radioactive (36Cl, 41Ca, 63Ni and 93Mo) isotopes in stable element standards and sample matrices including air quality filters and aqueous nuclear decommissioning waste.

This paper describes the many, evidenced-based benefits to the economy of a well-developed measurement infrastructure. In particular, it explains how assuring confidence in measurement may be used to accelerate economic recovery from the COVID-19 pandemic including in emerging sectors such as the digital economy. Recommendations are made for providing near term support for national economic recovery whilst also demonstrating the advantages of sustained development of the measurement infrastructure in the medium-term to maximize the potential of future innovative and disruptive technologies. These recommendations, whilst focused on consideration of the UK, should apply globally.

COVID-19 has demonstrated the power of RNA vaccines as part of a pandemic response toolkit. Another virus with pandemic potential is influenza. Further development of RNA vaccines in advance of a future influenza pandemic will save time and lives. As RNA vaccines require formulation to enter cells and induce antigen expression, the aim of this study was to investigate the impact of a recently developed bioreducible cationic polymer, pABOL for the delivery of a self-amplifying RNA (saRNA) vaccine for seasonal influenza virus in mice and ferrets. Mice and ferrets were immunized with pABOL formulated saRNA vaccines expressing either haemagglutinin (HA) from H1N1 or H3N2 influenza virus in a prime boost regime. Antibody responses, both binding and functional were measured in serum after immunization. Animals were then challenged with a matched influenza virus either directly by intranasal inoculation or in a contact transmission model. While highly immunogenic in mice, pABOL-formulated saRNA led to variable responses in ferrets. Animals that responded to the vaccine with higher levels of influenza virus-specific neutralizing antibodies were more protected against influenza virus infection. pABOL-formulated saRNA is immunogenic in ferrets, but further optimization of RNA vaccine formulation and constructs is required to increase the quality and quantity of the antibody response to the vaccine.

High trait self-control is associated with greater tolerance of unpleasant sensations including effort and pain. Dyspnoea and pain have several commonalities and this study aimed to investigate for the first time whether trait self-control influences responses to a hypercapnic rebreathing challenge designed to induce dyspnoea. As sex also influences tolerance to dyspnoea, we also sought to investigate whether this moderated the role of trait self-control.Participants (n = 65, 32 females) scoring high or low for trait self-control, performed a standardised rebreathing challenge, in which inspired carbon dioxide (COMales high in trait self-control (SCHIGH) (302 ± 42 s), tolerated the rebreathing challenge for longer than males low in self-control (SCLOW) (252 ± 66 s, P = 0.021), experienced slower increases in AH intensity during the rebreathing challenge (0.03 ± 0.01 cmThese results indicate that individuals high in trait self-control are more tolerant of dyspnoea during a CO

Tidal estuaries support everyday functions for over 80% of Australia's population living within 50 km of the coastline and thus come under immense pressure of physicochemical changes. Most studies in estuarine applications have used the bed roughness as the single calibration parameter to calibrate hydrodynamic modelling, yet errors in bathymetric data can significantly impose uncertainties into the model outputs. In this study, we evaluated the sensitivity of a hydrodynamic model of a micro-tidal estuary to both the bed roughness and bathymetry offset through comparing observed and modelled water level and velocity. Treating both bathymetry offset and bed roughness as calibration parameters, three calibration scenarios were tested to examine the impact of these parameters. To validate the model, Lagrangian drifter data as a new dataset in shallow estuaries were used. The analysis shows that model outputs are more sensitive to the variation of bathymetry offset than bed roughness. Results show that calibrating the bathymetry offset alone can significantly improve model performance. Simultaneous calibration of both parameters can provide further improvement, particularly for capturing the water level. Drifter and modelled velocities are highly correlated during flood tides, whereas the correlation is low for slack water because of wind-induced current on drifters.

Four types of fuels blended with diesel in scaling proportion were used in a diesel engine to generate 13 different soot samples. The samples were characterised for their thermal-induced oxidation process with DSC and TGA from which the mass loss during each of three phases and 6 critical temperatures was obtained per sample. With the same samples, soot chemical structure was characterised by Raman, XPS and TEM. This analysis provided information on different carbon chemical structures, O/C ratio on the sample surface, and nanostructure (fringe length and tortuosity). It was observed that generally for oxygenated fuel blends, the soot samples are more reactive, have more O functional groups on the carbon layer edge plane and have smaller polyaromatic layer size than reference diesel soots, while aromatic fuel blends show the opposite trends. However, the trend was not distinctive for all the samples analysed. Nevertheless, the two groups of data are highly correlated which implies that the chemical structure is the underlying reason dominating the soot reactivity. Specifically, the soot samples with more O functional groups and/or C–C bonds on the edge plane, are more reactive, they lose more mass at the lower temperature range and require lower temperature to initiate oxidation.

Background: Molecular genomic profiles are increasingly used to guide treatment of refractory cancers and are on the forefront of personalized medicine for select patients. The neoadjuvant chemotherapy (NAC) setting provides a meaningful opportunity to compare genomic profiles to pathologic response. We report profiles to response in a novel multi center registry. Methods: An ongoing IRB (WIRB) approved registry at 6 community breast practices submitted tumor samples prior to treatment for genomic/proteomic analysis (Paradigm, Phoenix, AZ.) Tumor response and associated molecular profiles were analyzed. The test evaluated over 137 genomic alterations with known actionable variations including mutations, gene-fusions, copy number variations, MRNA expression and protein expression analysis by IHC. Results: 76 patients were enrolled and 42 have completed treatment including definitive surgery and have reported data as of this date. The vast majority of patients had invasive ductal carcinoma with 16% having triple negative biology and 20% having Her2 biology. Of the triple negative patients with reported surgical results, 42% had a complete response or minimal residual disease, and the remaining 58% had a partial response. Of the patients with HER2 biology, 85% had a complete response and the remaining a partial response. 17% of patients with luminal biology had a complete response; the remaining had only a partial response or progression. Overall, 15 patients had a complete response, 4 had minimal residual disease and the remaining (over 50%) had a partial response, stable or progressive disease. Patients who did not achieve a complete response had multiple molecular aberrations with unique markers not present in patients with PCR. These included markers of known or possible drug resistance (IGFR1, CAIX), poor prognostic markers (TP53, MET, PTEN), biomarkers of response to approved treatment that were not utilized and other markers of potential response and research. Conclusions: Comprehensive genomic testing may predict resistant biology and provide additional targets for treatment or clinical study. Genomic analysis earlier in the patient’s care path may improve response rates by suggesting modifications in standard protocols or identifying clinical trials as potential first line options. Repeat genomic analysis may also suggest options for targeted adjuvant therapy for residual cancer after neoadjuvant therapy. Citation Format: Peter Beitsch, Pat Whitworth, Laura Lee, Antonio Ruiz, Rick Brown, Linsey Gold, Paul Baron, Rakesh Patel. Novel use of a precision medicine tool in the neoadjuvant therapy setting [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-16-21.

This discussion article explores how metrology bodies should approach method-defined measurands (also called operationally defined measurands). It begins by considering the different types of measurement that can be encountered and comparing their difference qualities, before discussing in more detail method-defined measurands and the nature of their current and future treatment by the global metrology system. The discussion highlights work performed within the Consultative Committee for Amount of Substance to address what should be within the scope of the International Committee for Weights and Measures Mutual Recognition Arrangement (CIPM-MRA) when method-defined measurands are considered and also how the metrology community can contribute to ensuring stability and comparability of these measurements outside the formal scope of the CIPM-MRA.

Magnetic fields permeate the interstellar medium and are important in the star formation process. Determining the 3D magnetic fields of molecular clouds will allow us to better understand their role in the evolution of these clouds and formation of stars. We fully reconstruct the approximate three-dimensional (3D) magnetic field morphology of the Orion A molecular cloud (on scales of a few to ~100 pc) using Galactic magnetic field models, as well as present line-of-sight and plane-of-sky magnetic field observations. While previous studies identified the 3D magnetic field morphology of the Orion A cloud as an arc shape, in this study we provide the orientation of this arc-shaped field and its plane-of-sky direction, for the first time. We find that this 3D field is a tilted, semi-convex (from our point of view) structure and mostly points in the direction of decreasing latitude and longitude on the plane of the sky, from our vantage point. The previously identified bubbles and events in this region were key in shaping this arc-shaped magnetic field morphology., Comment: 9 pages, 9 Figures, accepted in Astronomy & Astrophysics

Despite recent observational and theoretical advances in mapping the magnetic fields associated with molecular clouds, their three-dimensional (3D) morphology remains unresolved. Multi-wavelength and multi-scale observations will allow us to paint a comprehensive picture of the magnetic fields of these star-forming regions. We reconstruct the 3D magnetic field morphology associated with the Perseus molecular cloud and compare it with predictions of cloud-formation models. These cloud-formation models predict a bending of magnetic fields associated with filamentary molecular clouds. We compare the orientation and direction of this field bending with our 3D magnetic field view of the Perseus cloud. We use previous line-of-sight and plane-of-sky magnetic field observations, as well as Galactic magnetic field models, to reconstruct the complete 3D magnetic field vectors and morphology associated with the Perseus cloud. We approximate the 3D magnetic field morphology of the cloud as a concave arc that points in the decreasing longitude direction in the plane of the sky (from our point of view). This field morphology preserves a memory of the Galactic magnetic field. In order to compare this morphology to cloud-formation model predictions, we assume that the cloud retains a memory of its most recent interaction. Incorporating velocity observations, we find that the line-of-sight magnetic field observations are consistent with predictions of shock-cloud-interaction models. To our knowledge, this is the first time that the 3D magnetic fields of a molecular cloud have been reconstructed. We find the 3D magnetic field morphology of the Perseus cloud to be consistent with the predictions of the shock-cloud-interaction model, which describes the formation mechanism of filamentary molecular clouds., 13 pages,12 figures, accepted for publication in Astronomy & Astrophysics. updated to correct an affiliation

The objective of this study is to develop a shipping emission inventory model incorporating Machine Learning (ML) tools to estimate gaseous emissions. The tools enhance the emission inventories which currently rely on emission factors. The current inventories apply varied methodologies to estimate emissions with mixed accuracy. Comprehensive Bottom-up approach have the potential to provide very accurate results but require quality input. ML models have proven to be an accurate method of predicting responses for a set of data, with emission inventories an area unexplored with ML algorithms. Five ML models were applied to the emission data with the best-fit model judged based on comparing the real mean square errors and the R-values of each model. The primary gases studied are from a vessel measurement campaign in three modes of operation; berthing, manoeuvring, and cruising. The manoeuvring phase was identified as key for model selection for which two models performed best.

Electronic cigarettes (ECs) have recently become very popular among the population due to the various flavors available for vaping products. Consequently, manufacturers are trying to attract more users through the addition of various additives including nicotine, new flavors, and aromas. However, the inhalation of unknown and untested chemicals may cause health problems. Therefore, more clinical reports need to be collected for standardization of ECs for their effective regulation. However, detailed compositional information for EC additives is not commonly available. The aim of this review is, therefore, to study the state-of-the-art methods that can be employed for the quantitative analysis of the composition of electronic cigarettes with respect to these additives and flavors along with the basic cigarette ingredient like nicotine (both before and after consumption). In addition, efforts have also been made to address the clinical impacts of vaping EC and its additives on both the organ and cellular level. It was found that the effect of flavorings in EC is clearly associated with pathogenicity at the molecular level and need of standardization of the usage of EC and its flavorings is urgently needed.