scholarly journals GCalignR: An R package for aligning Gas-Chromatography data

2017 ◽  
Author(s):  
Meinolf Ottensmann ◽  
Martin A. Stoffel ◽  
Hazel J. Nichols ◽  
Joseph I. Hoffman
Keyword(s):  
Gas Chromatography ◽  
Animal Communication ◽  
Kin Recognition ◽  
R Package ◽  
Error Rates ◽  
Fine Tuning ◽  
Alignment Error ◽  
Mass Spectral ◽  
Fur Seals ◽  
The Impact

AbstractChemical cues are arguably the most fundamental means of animal communication and play an important role in mate choice and kin recognition. Consequently, gas chromatography (GC) in combination with either mass spectrometry (MS) or flame ionisation detection (FID) are commonly used to characterise complex chemical samples. Both GC-FID and GC-MS generate chromatograms comprising peaks that are separated according to their retention times and which represent different substances. Across chromatograms of different samples, homologous substances are expected to elute at similar retention times. However, random and often unavoidable experimental variation introduces noise, making the alignment of homologous peaks challenging, particularly with GC-FID data where mass spectral data are lacking. Here we presentGCalignR, a user-friendly R package for aligning GC-FID data based on retention times. The package also implements dynamic visualisations to facilitate inspection and fine-tuning of the resulting alignments, and can be integrated within a broader workflow in R to facilitate downstream multivariate analyses. We demonstrate an example workflow using empirical data from Antarctic fur seals and explore the impact of user-defined parameter values by calculating alignment error rates for multiple datasets. The resulting alignments had low error rates for most of the explored parameter space and we could also show thatGCalignRperformed equally well or better than other available software. We hope thatGCalignRwill help to simplify the processing of chemical datasets and improve the standardization and reproducibility of chemical analyses in studies of animal chemical communication and related fields.

Food Safety Security: A new Concept for Enhancing Food Safety Measures

2012 ◽  
Vol 82 (3) ◽  
pp. 216-222 ◽  
Author(s):  
Venkatesh Iyengar ◽  
Ibrahim Elmadfa
Keyword(s):  
Food Safety ◽  
Hazard Analysis ◽  
Warning System ◽  
Shared Responsibility ◽  
Fine Tuning ◽  
Strategic Action ◽  
Surveillance Network ◽  
Measurement Systems ◽  
Critical Control Points ◽  
The Impact

The food safety security (FSS) concept is perceived as an early warning system for minimizing food safety (FS) breaches, and it functions in conjunction with existing FS measures. Essentially, the function of FS and FSS measures can be visualized in two parts: (i) the FS preventive measures as actions taken at the stem level, and (ii) the FSS interventions as actions taken at the root level, to enhance the impact of the implemented safety steps. In practice, along with FS, FSS also draws its support from (i) legislative directives and regulatory measures for enforcing verifiable, timely, and effective compliance; (ii) measurement systems in place for sustained quality assurance; and (iii) shared responsibility to ensure cohesion among all the stakeholders namely, policy makers, regulators, food producers, processors and distributors, and consumers. However, the functional framework of FSS differs from that of FS by way of: (i) retooling the vulnerable segments of the preventive features of existing FS measures; (ii) fine-tuning response systems to efficiently preempt the FS breaches; (iii) building a long-term nutrient and toxicant surveillance network based on validated measurement systems functioning in real time; (iv) focusing on crisp, clear, and correct communication that resonates among all the stakeholders; and (v) developing inter-disciplinary human resources to meet ever-increasing FS challenges. Important determinants of FSS include: (i) strengthening international dialogue for refining regulatory reforms and addressing emerging risks; (ii) developing innovative and strategic action points for intervention {in addition to Hazard Analysis and Critical Control Points (HACCP) procedures]; and (iii) introducing additional science-based tools such as metrology-based measurement systems.

Determination of multi pesticide residues in leaf and needle samples using a modified QuEChERS approach and gas chromatography-tandem mass spectrometry

2021 ◽  
Author(s):  
Arnelle Löbbert ◽  
Sonja Schanzer ◽  
Henrik Krehenwinkel ◽  
Franz Bracher ◽  
Christoph Müller
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Tandem Mass Spectrometry ◽  
Forest Ecosystems ◽  
Tandem Mass ◽  
Modified Quechers ◽  
Chromatography Tandem Mass Spectrometry ◽  
The Impact ◽  
Impact Of Pesticides

A novel, validated QuEChERS-based GC-MS/MS method was developed, which will allow the assessment of the impact of pesticides on forest ecosystems.

Expectations, Prefitting Counseling, and Hearing Aid Outcome

2009 ◽  
Vol 20 (05) ◽  
pp. 320-334 ◽  
Author(s):  
Gabrielle H. Saunders ◽  
M Samantha Lewis ◽  
Anna Forsline
Keyword(s):  
Hearing Aids ◽  
Hearing Aid ◽  
Well Being ◽  
Fine Tuning ◽  
Initial Contact ◽  
High Expectations ◽  
Digital Hearing Aids ◽  
The Impact ◽  
Unrealistic Expectations

Background: Data suggest that having high expectations about hearing aids results in better overall outcome. However, some have postulated that excessively high expectations will result in disappointment and thus poor outcome. It has been suggested that counseling patients with unrealistic expectations about hearing aids prior to fitting may be beneficial. Data, however, are mixed as to the effectiveness of such counseling, in terms of both changes in expectations and final outcome. Purpose: The primary purpose of this study was to determine whether supplementing prefitting counseling with demonstration of real-world listening can (1) alter expectations of new hearing aid users and (2) increase satisfaction over verbal-only counseling. Secondary goals of the study were to examine (1) the relationship between prefitting expectations and postfitting outcome, and (2) the effect of hearing aid fine-tuning on hearing aid outcome. Research Design: Sixty new hearing aid users were fitted binaurally with Beltone Oria behind-the-ear digital hearing aids. Forty participants received prefitting counseling and demonstration of listening situations with the Beltone AVE™ (Audio Verification Environment) system; 20 received prefitting counseling without a demonstration of listening situations. Hearing aid expectations were measured at initial contact and following prefitting counseling. Reported hearing aid outcome was measured after eight to ten weeks of hearing aid use. Study Sample: Sixty new hearing aid users aged between 55 and 81 years with symmetrical sensorineural hearing loss. Intervention: Participants were randomly assigned to one of three experimental groups, between which the prefitting counseling and follow-up differed: Group 1 received prefitting counseling in combination with demonstration of listening situations. Additionally, if the participant had complaints about sound quality at the follow-up visit, the hearing aids were fine-tuned using the Beltone AVE system. Group 2 received prefitting counseling in combination with demonstration of listening situations with the Beltone AVE system, but no fine-tuning was provided at follow-up. Group 3 received prefitting hearing aid counseling that did not include demonstration of listening, and the hearing aids were not fine-tuned at the follow-up appointment. Results: The results showed that prefitting hearing aid counseling had small but significant effects on expectations. The two forms of counseling did not differ in their effectiveness at changing expectations; however, anecdotally, we learned from many participants that that they enjoyed listening to the auditory demonstrations and that they found them to be an interesting listening exercise. The data also show that positive expectations result in more positive outcome and that hearing aid fine-tuning is beneficial to the user. Conclusions: We conclude that prefitting counseling can be advantageous to hearing aid outcome and recommend the addition of prefitting counseling to address expectations associated with quality of life and self-image. The data emphasize the need to address unrealistic expectations prior to fitting hearing aids cautiously, so as not to decrease expectations to the extent of discouraging and demotivating the patient. Data also show that positive expectations regarding the impact hearing aids will have on psychosocial well-being are important for successful hearing aid outcome.

Degradation of bacteria mass spectral signals via hydrothermal processing and UV irradiation: relevance to life detection on icy moons

2021 ◽  
Author(s):  
Tara Salter ◽  
Hunter Waite ◽  
Mark Sephton
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Uv Irradiation ◽  
Gas Chromatography Mass Spectrometry ◽  
Xenon Lamp ◽  
Hydrothermal Processing ◽  
Mass Spectral ◽  
Icy Moons ◽  
Chromatography Mass Spectrometry ◽  
Life Detection

<p>The inferred subsurface oceans of the icy moons of Jupiter and Saturn, in particular Europa and Enceladus, may contain conditions suitable for life. Plumes of material have been detected from Enceladus and may also be present on Europa. These plumes could contain molecular signs of habitability that could be detected by mass spectrometers on orbiting spacecrafts, such as the upcoming Europa Clipper mission. However, these molecular markers may have degraded between their production and detection, for example by possible hydrothermalism in the subsurface ocean or by UV irradiation once carried into space by the plume. It is important to look at how the biosignatures degrade under different conditions as degradation processes need to be taken into account when analysing the data from life detection missions. We investigate how these two processes affect the mass spectral signals of terrestrial bacteria.</p> <p>Two cyanobacteria samples, <em>Spirulina</em> and <em>Chlorella</em>, were subjected to hydrothermal processing and UV irradiation. Hydrous pyrolysis was used to simulate hydrothermal degradation. Experiments were carried out for 24 or 72 hours at temperatures between 200 and 300 °C. The pyrolyzed contents were subsequently extracted and analysed with gas chromatography-mass spectrometry (GC-MS). UV irradiation was carried out in a vacuum chamber (10<sup>-2</sup> mbar), using a 300 W short arc xenon lamp at UV to near infrared wavelengths (~250 – 800 nm). After UV irradiation, samples were analysed using pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS).</p> <p>Our results show that hydrothermal processing of cyanobacteria affects the compound classes in different ways. Carbohydrate and protein components from the cyanobacteria were significantly affected, with phenol and indole derivatives detected. However, some of the biological fingerprint, such as straight-chain even numbered saturated fatty acids from lipid fragments, remain even at the harshest experimental conditions used in our study. This provides confidence that these diagnostic molecules could be used as fingerprints of biological materials on icy moons.</p>

Aroma profile and lactic acid bacteria characteristic of traditional Slovak cheese “May bryndza”

2021 ◽  
pp. 108201322110399
Author(s):  
Jana Štefániková ◽  
Július Árvay ◽  
Simona Kunová ◽  
Przemysław Łukasz Kowalczewski ◽  
Miroslava Kačániová
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Lactic Acid ◽  
Lactic Acid Bacteria ◽  
Butanoic Acid ◽  
Aroma Profile ◽  
Volatile Organic ◽  
Ewe's Milk ◽  
The Impact

This paper describes the results of the characterization of a traditional Slovak cheese called “May bryndza” with regard to the profiles of volatile organic compounds and lactic acid bacteria. Samples of “May bryndza“ cheese produced solely from unpasteurized ewe's milk were collected from 4 different Slovak farms, and samples of the cheese produced from a mixture of 2 types of milk (raw ewe's and pasteurized cow's milk) were collected from 3 different Slovak industrial dairies. There were 15 compounds detected and identified by the electronic nose. The impact of the kind of milk and the kind of dairy on the aroma profile of the product was not confirmed by PCA. The compounds with the highest relative contents in samples were acetoin (2.59%–24.55%), acetic acid (6.69%–13.39%), methoxy-phenyl-oxime (4.49%–8.52%), butanoic acid (1.89%–5.67%), and 2,3-butanediol (0.98%–4.08%), which were determined with gas chromatography. A total of 1533 isolates of LAB were obtained from the “May bryndza” cheese samples. Four families, five genera, and 19 species were identified with mass spectrometry, and isolated bacteria, both from the farm and industry dairies were the most frequently found to belong to Lactococcus lactis subsp. lactis.

A Comparative Study of Data and Physically Based Gas Turbine Modeling for Long-Term Monitoring Scenarios: Part II — Emission Prediction Utilizing Different Levels of Design Information

2018 ◽  
Author(s):  
Moritz Lipperheide ◽  
Thomas Bexten ◽  
Manfred Wirsum ◽  
Martin Gassner ◽  
Stefano Bernero
Keyword(s):  
Gas Turbine ◽  
A Priori ◽  
Model Development ◽  
Fine Tuning ◽  
Plant Operator ◽  
Engine Model ◽  
Physically Based ◽  
Design Type ◽  
The Impact

Reliable engine and emission models allow for an online monitoring of commercial gas turbine operation and help the plant operator and the original equipment manufacturer (OEM) to ensure emission compliance of the aging engine. However, model development and validation require fine-tuning on the particular engines, which may differ in a fleet of a single design type by production, assembly and aging status. For this purpose, Artificial Neural Networks (ANN) offer a good and fast alternative to traditional physically-based engine modeling, because the model creation and adaption is merely an automatized process in commercially available software environments. However, ANN performance depends strongly on the availability of suitable data and a-priori data processing. The present work investigates the impact of specific engine information from the OEM’s design tools on ANN performance. As an alternative to a strictly data-based benchmark approach, engine characteristics were incorporated into ANNs by a pre-processing of the raw measurements with a simplified engine model. The resulting ‘virtual’ measurements, i.e. hot gas temperatures, then served as inputs to ANN training and application during long-term gas turbine operation. When processed input parameters were used for ANNs, overall long-term NOx prediction improved by 55%, and CO prediction by 16% in terms of RMSE, yielding comparable overall RMSE values to the physically-based model.

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