ORCID Profile
0000-0003-3462-7648
Current Organisation
University of South Australia
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Publisher: Informa UK Limited
Date: 02-2011
DOI: 10.3155/1047-3289.61.2.142
Abstract: The Windsor, Ontario Exposure Assessment Study evaluated the contribution of ambient air pollutants to personal and indoor exposures of adults and asthmatic children living in Windsor, Ontario, Canada. In addition, the role of personal, indoor, and outdoor air pollution exposures upon asthmatic children's respiratory health was assessed. Several active and passive s ling methods were applied, or adapted, for personal, indoor, and outdoor residential monitoring of nitrogen dioxide, volatile organic compounds, particulate matter (PM PM ≤2.5 μm [PM
Publisher: IEEE
Date: 03-2019
Publisher: Elsevier BV
Date: 2017
DOI: 10.1016/J.NLM.2016.11.017
Abstract: False memory has been claimed to be the result of an associative process of generalisation, as well as to be representative of memory errors. These can occur at any stage of memory encoding, consolidation, or retrieval, albeit through varied mechanisms. The aim of this paper is to experimentally determine: (i) if cognitive dysfunction brought about by sleep loss at the time of stimulus encoding can influence false memory production and (ii) whether this relationship holds across sensory modalities. Subjects undertook both the Deese-Roedigger-McDermott (DRM) false memory task and a visual task designed to produce false memories. Performance was measured while subjects were well-rested (9h Time in Bed or TIB), and then again when subjects were either sleep restricted (4h TIB for 4 nights) or sleep deprived (30h total SD). Results indicate (1) that partial and total sleep loss produced equivalent effects in terms of false and veridical verbal memory, (2) that subjects performed worse after sleep loss (regardless of whether this was partial or total sleep loss) on cued recognition-based false and veridical verbal memory tasks, and that sleep loss interfered with subjects' ability to recall veridical, but not false memories under free recall conditions, and (3) that there were no effects of sleep loss on a visual false memory task. This is argued to represent the dysfunction and slow repair of an online verbal associative process in the brain following inadequate sleep.
Publisher: IEEE
Date: 03-2023
Publisher: Oxford University Press (OUP)
Date: 02-2013
DOI: 10.5665/SLEEP.2380
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 11-2020
Publisher: Human Kinetics
Date: 04-2023
Abstract: Posttraining meditation has been shown to promote wakeful memory stabilization of explicit motor sequence information in learners who are experienced meditators. We investigated the effect of single-session mindfulness meditation on wakeful and sleep-dependent forms of implicit motor memory consolidation in meditation naïve adults. Immediately after training with a target implicit motor sequence, participants ( N = 20, eight females, 23.9 ± 3.3 years) completed either a 10-min mindfulness meditation ( N = 10) or a control listening task before exposure to task interference induced by training with a novel implicit sequence. Target sequence performance was tested following 5-hr wakeful and 15-hr postsleep periods. Bayesian inference was applied to group comparisons of mean reaction time (RT) changes across training, interference, wakeful, and postsleep timepoints. Relative to control conditions, posttraining meditation reduced RT slowing between target sequence training and interference sequence introduction (BF 10 [Bayes factors] = 6.61) and supported RT performance gains over the wakeful period (BF 10 = 8.34). No group differences in postsleep RT performance were evident (BF 10 = 0.38). These findings illustrate that posttraining mindfulness meditation expedites wakeful, but not sleep-dependent, offline learning with implicit motor sequences. Previous meditation experience is not required to obtain wakeful consolidation gains from posttraining mindfulness meditation.
Publisher: MDPI AG
Date: 16-08-2010
Publisher: Springer Science and Business Media LLC
Date: 30-03-2023
DOI: 10.1007/S41465-023-00259-W
Abstract: Previous investigations into the effect of mindfulness meditation on false memory have reported mixed findings. One potential issue is that mindfulness meditation involves different styles that establish distinct cognitive control states. The present work aimed to address this issue by comparing the effects of single-session focused attention (FAM) and open monitoring (OMM) mindfulness meditation styles on true and false memory recall. Strengthened cognitive control states associated with FAM were predicted to increase true memory recall and decrease false memory recall. Conversely, weakened cognitive control established by OMM was predicted to increase false memory recall. Thirty-four meditation-naïve participants (23 females, mean age = 23.4 years, range = 18–33) first completed pre-meditation learning and recall phases of the Deese-Roediger-McDermott (DRM) task. Participants then completed a single session of FAM or OMM prior to a second, post-meditation, round of DRM task learning and recall phases with a novel word list. Finally, participants completed a recognition test with true and false memory, and distractor words. Both FAM and OMM groups demonstrated significant increase in false memory recall between pre- and post-meditation recall tests but these groups did not differ with respect to true and false memory recall and recognition. The present findings are consistent with previous reports of increased false memory arising from mindfulness meditation. Distinct cognitive control states associated with FAM and OMM states do not result in distinct true and false memory formation, at least in meditation-naïve adults.
Publisher: Emerald Publishing Limited
Date: 22-11-2021
Publisher: Informa UK Limited
Date: 02-2013
DOI: 10.2147/NSS.S38369
Publisher: Elsevier BV
Date: 2008
DOI: 10.1016/J.ENVRES.2007.09.004
Abstract: There are acknowledged difficulties in epidemiological studies to accurately assign exposure to air pollution for large populations, and large, long-term cohort studies have typically relied upon data from central monitoring stations. This approach has generally been adequate when populations span large areas or erse cities. However, when the effects of intra-urban differences in exposure are being studied, the use of these existing central sites are likely to be inadequate for representing spatial variability that exists within an urban area. As part of the Border Air Quality Strategy (BAQS), an international agreement between the governments of Canada and the United States, a number of air health effects studies are being undertaken by Health Canada and the US EPA. Health Canada's research largely focuses on the chronic exposure of elementary school children to air pollution. The exposure characterization for this population to a variety of air pollutants has been assessed using land-use regression (LUR) models. This approach has been applied in several cities to nitrogen dioxide (NO2), as an assumed traffic exposure marker. However, the models have largely been developed from limited periods of saturation monitoring data and often only represent one or two seasons. Two key questions from these previous efforts, which are examined in this paper, are: If NO2 is a traffic marker, what other pollutants, potentially traffic related, might it actually represent? How well is the within city spatial variability of NO2, and other traffic-related pollutants, characterized by a single saturation monitoring c aign. Input data for the models developed in this paper were obtained across a network of 54 monitoring sites situated across Windsor, Ontario. The pollutants studied were NO2, sulfur dioxide (SO2) and volatile organic compounds, which were measured in all four seasons by deploying passive s lers for 2-week periods. Correlations among these pollutants were calculated to assess what other pollutants NO2 might represent, and correlations across seasons for a given pollutant were determined to assess how much the within-city spatial pattern varies with time. LUR models were then developed for NO2, SO2, benzene, and toluene. A multiple regression model including proximity to the Ambassador Bridge (the main Canada-US border crossing point), and proximity to highways and major roads, predicted NO2 concentrations with an R2=0.77. The SO2 model predictors included distance to the Ambassador Bridge, dwelling density within 1500m, and Detroit-based SO2 emitters within 3000m resulting in a model with an R2=0.69. Benzene and toluene LUR models included traffic predictors as well as point source emitters resulting in R2=0.73 and 0.46, respectively. Between season pollutant correlations were all significant although actual concentrations for each site varied by season. This suggests that if one season were to be selected to represent the annual concentrations for a specific site this may lead to a potential under or overestimation in exposure, which could be significant for health research. All pollutants had strong inter-pollutant correlations suggesting that NO2 could represent SO2, benzene, and toluene.
Publisher: MDPI AG
Date: 23-08-2010
Publisher: Elsevier BV
Date: 2014
DOI: 10.1016/J.AAP.2013.09.003
Abstract: Drivers are not always aware that they are becoming impaired as a result of sleepiness. Using specific symptoms of sleepiness might assist with recognition of drowsiness related impairment and help drivers judge whether they are safe to drive a vehicle, however this has not been evaluated. In this study, 20 healthy volunteer professional drivers completed two randomized sessions in the laboratory - one under 24h of acute sleep deprivation, and one with alcohol. The Psychomotor Vigilance Task (PVT) and a 30min simulated driving task (AusEdTM) were performed every 3-4h in the sleep deprivation session, and at a BAC of 0.00% and 0.05% in the alcohol session, while electroencephalography (EEG) and eye movements were recorded. After each test session, drivers completed the Karolinska Sleepiness Scale (KSS) and the Sleepiness Symptoms Questionnaire (SSQ), which includes eight specific sleepiness and driving performance symptoms. A second baseline session was completed on a separate day by the professional drivers and in an additional 20 non-professional drivers for test-retest reliability. There was moderate test-retest agreement on the SSQ (r=0.59). Significant correlations were identified between in idual sleepiness symptoms and the KSS score (r values 0.50-0.74, p<0.01 for all symptoms). The frequency of all SSQ items increased during sleep deprivation (χ(2) values of 28.4-80.2, p<0.01 for all symptoms) and symptoms were related to increased subjective sleepiness and performance deterioration. The symptoms "struggling to keep your eyes open", "difficulty maintaining correct speed", "reactions were slow" and "head dropping down" were most closely related to increased alpha and theta activity on EEG (r values 0.49-0.59, p<0.001) and "nodding off to sleep" and "struggling to keep your eyes open" were related to slow eye movements (r values 0.67 and 0.64, p<0.001). Symptoms related to visual disturbance and impaired driving performance were most accurate at detecting severely impaired driving performance (AUC on ROC curve of 0.86-0.91 for detecting change in lateral lane position greater than the change at a BAC of 0.05%). In idual sleepiness symptoms are related to impairment during acute sleep deprivation and might be able to assist drivers in recognizing their own sleepiness and ability to drive safely.
Publisher: Cold Spring Harbor Laboratory
Date: 24-03-2022
DOI: 10.1101/2022.03.23.485424
Abstract: The endeavour to understand human cognition has largely relied upon investigation of task-related brain activity. However, resting-state brain activity can also offer insights into in idual information processing and performance capabilities. Previous research has identified electroencephalographic resting-state characteristics (most prominently: the in idual alpha frequency IAF) that predict cognitive function. However, it has largely overlooked a second component of electrophysiological signals: aperiodic 1/ f activity. The current study examined how both oscillatory and aperiodic resting-state EEG measures, alongside traditional cognitive tests, can predict performance in a dynamic and complex, semi-naturalistic cognitive task. Participants’ resting-state EEG was recorded prior to engaging in a Target Motion Analysis (TMA) task in a simulated submarine control room environment (CRUSE), which required participants to integrate dynamically changing information over time. We demonstrated that the relationship between IAF and cognitive performance extends from simple cognitive tasks (e.g., digit span) to complex, dynamic measures of information processing. Further, our results showed that in idual 1/ f parameters (slope and intercept) differentially predicted performance across practice and testing sessions, whereby flatter slopes were associated with improved performance during learning, while higher intercepts were linked to better performance during testing. In addition to the EEG predictors, we demonstrate a link between cognitive skills most closely related to the TMA task (i.e., spatial imagery) and subsequent performance. Overall, the current study highlights (1) how resting-state metrics – both oscillatory and aperiodic - have the potential to index higher-order cognitive capacity, while (2) emphasising the importance of examining these electrophysiological components within more dynamic settings and over time.
Publisher: Elsevier BV
Date: 06-2022
Publisher: ACM
Date: 29-11-2022
Publisher: Frontiers Media SA
Date: 09-05-2022
DOI: 10.3389/FNHUM.2022.821191
Abstract: Relatively little is known regarding the interaction between encoding-related neural activity and sleep-based memory consolidation. One suggestion is that a function of encoding-related theta power may be to “tag” memories for subsequent processing during sleep. This study aimed to extend previous work on the relationships between sleep spindles, slow oscillation-spindle coupling, and task-related theta activity with a combined Deese-Roediger-McDermott (DRM) and nap paradigm. This allowed us to examine the influence of task- and sleep-related oscillatory activity on the recognition of both encoded list words and associative theme words. Thirty-three participants (29 females, mean age = 23.2 years) learned and recognised DRM lists separated by either a 2 h wake or sleep period. Mixed-effects modelling revealed the sleep condition endorsed more associative theme words and fewer list words in comparison to the wake group. Encoding-related theta power was also found to influence sleep spindle density, and this interaction was predictive of memory outcomes. The influence of encoding-related theta was specific to sleep spindle density, and did not appear to influence the strength of slow oscillation-spindle coupling as it relates to memory outcomes. The finding of interactions between wakeful and sleep oscillatory-related activity in promoting memory and learning has important implications for theoretical models of sleep-based memory consolidation.
Publisher: Informa UK Limited
Date: 03-2011
DOI: 10.3155/1047-3289.61.3.324
Abstract: The Windsor, Ontario Exposure Assessment Study evaluated the contribution of ambient air pollutants to personal and indoor exposures of adults and asthmatic children living in Windsor, Ontario, Canada. In addition, the role of personal, indoor, and outdoor air pollution exposures upon asthmatic children's respiratory health was assessed. Several active and passive s ling methods were applied, or adapted, for personal, indoor, and outdoor residential monitoring of nitrogen dioxide, volatile organic compounds, particulate matter (PM PM ≤ 2.5 μm [PM
Publisher: Informa UK Limited
Date: 12-2014
DOI: 10.2147/NSS.S54913
Publisher: Springer Science and Business Media LLC
Date: 28-09-2022
DOI: 10.1038/S41598-022-20704-8
Abstract: Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more in iduals engaging cooperatively in real-world tasks, such as in operational training environments. In this exploratory study, we recruited forty in iduals paired as twenty dyads and recorded dual-EEG at rest and during realistic training scenarios of increasing complexity using virtual simulation systems. We estimated markers of intrinsic brain activity (i.e., in idual alpha frequency and aperiodic activity), as well as task-related theta and alpha oscillations. Using nonlinear modelling and a logistic regression machine learning model, we found that resting-state EEG predicts performance and can also reliably differentiate between members within a dyad. Task-related theta and alpha activity during easy training tasks predicted later performance on complex training to a greater extent than prior behaviour. These findings complement laboratory-based research on both oscillatory and aperiodic activity in higher-order cognition and provide evidence that theta and alpha activity play a critical role in complex task performance in team environments.
Publisher: American Chemical Society (ACS)
Date: 06-2009
DOI: 10.1021/ES900419N
Abstract: This analysis examines differences between measured ambient indoor, and personal sulfate concentrations across cities, seasons, and in iduals to elucidate how these differences may impact PM2.5 exposure measurement error. Data were analyzed from four panel studies conducted in Atlanta, Baltimore, Boston, and Steubenville (OH). Among the study locations, 1912 person-days of personal sulfate data were collected over 396 days involving 245 in idual s ling sessions. Long-term differences in ambient and personal levels averaged over time are examined. Differences between averaged ambient and personal sulfate among and within cities were observed, driven by between subject and city differences in sulfate infiltration, F(inf), from outdoors to indoors. Neglecting this source of variability in associations may introduce bias in studies examining long-term exposures and chronic health. Indoor sulfate was highly correlated with and similar in magnitude to personal sulfate, suggesting indoor PM monitoring may be another means of characterizing true exposure variability.
Publisher: Elsevier BV
Date: 11-2010
Publisher: Elsevier BV
Date: 12-2011
Publisher: Elsevier BV
Date: 11-2014
DOI: 10.1016/J.NEUBIOREV.2014.10.018
Abstract: The beneficial influence of sleep on memory consolidation is well established however, the mechanisms by which sleep can dynamically consolidate new memories into existing networks for the continued environmental adaptation of the in idual are unclear. The role of sleep in complex associative memory is an emerging field and the literature has not yet been systematically reviewed. Here, we systematically review the published literature on the role of sleep in complex associative memory processing to determine (i) if there is reasonable published evidence to support an active role for sleep facilitating complex associative processes such rule and gist extraction and false memory (ii) to determine which sleep physiological events and states impact these processes, and to quantify the strength of these relationships through meta-analysis. Twenty-seven studies in healthy adults were identified which combined indicate a moderate effect of sleep in facilitating associative memory as tested behaviourally. Studies which have measured sleep physiology have reported mixed findings. Significant associations between sleep electrophysiology and outcome appear to be based largely on mode of acquisition. We interpret these findings as supporting reactivation based models of associative processing.
Publisher: Cold Spring Harbor Laboratory
Date: 11-08-2022
DOI: 10.1101/2022.08.07.503118
Abstract: Current assessment of excessive daytime somnolence (EDS) requires subjective measurements such as the Epworth Sleepiness Scale (ESS), and/or resource intensive sleep laboratory investigations. Recent work 1,2 has called for more non-performance-based measures of EDS. One promising non-performance-based measure of EDS is the aperiodic component of electroencephalography (EEG). Aperiodic (non-oscillatory) activity reflects excitation/inhibition ratios of neural populations and is altered in various states of consciousness, and thus may be a potential biomarker of hypersomnolence. We retrospectively analysed EEG data from patients who underwent a Multiple Sleep Latency Test (MSLT) and determined whether aperiodic neural activity is predictive of EDS. Participants having undergone laboratory polysomnogram and next day MSLT were grouped into MSLT+ ( n = 26) and MSLT– ( n = 33) groups (mean sleep latency of 8min and 10min, respectively) and compared against a non-clinical (Control) group of participants ( n = 26). While the MSLT+ and MSLT– groups did not differ in their aperiodic activity, the Control group had a significantly flatter slope and larger offset compared to both MSLT+ and MSLT– groups. Logistic regression machine learning predicted group status (i.e., symptomatic, non-symptomatic) with 90% accuracy based on the aperiodic slope while controlling for age. Slow oscillation-spindle coupling was also significantly stronger in the Control group relative to MSLT+ and MSLT– groups. Our results provide first evidence that aperiodic neural dynamics and sleep-based cross-frequency coupling is predictive of EDS, thereby providing a novel avenue for basic and applied research in the study of sleepiness.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 11-2010
DOI: 10.1038/AJG.2010.252
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 07-2008
Publisher: Elsevier BV
Date: 03-2010
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 09-2009
Publisher: Hindawi Limited
Date: 2011
DOI: 10.1100/2011/167973
Abstract: Spatial monitoring c aigns of volatile organic compounds were carried out in two similarly sized urban industrial cities, Windsor and Sarnia, ON, Canada. For Windsor, data were obtained for all four seasons at approximately 50 sites in each season (winter, spring, summer, and fall) over a three-year period (2004, 2005, and 2006) for a total of 12 s ling sessions. S ling in Sarnia took place at 37 monitoring sites in fall 2005. In both cities, passive s ling was done using 3M 3500 organic vapor s lers. This paper characterizes benzene, toluene, ethylbenzene, o , and ( m + p )-xylene (BTEX) concentrations and relationships among BTEX species in the two cities during the fall s ling periods. BTEX concentration levels and rank order among the species were similar between the two cities. In Sarnia, the relationships between the BTEX species varied depending on location. Correlation analysis between land use and concentration ratios showed a strong influence from local industries. Use one of the ratios between the BTEX species to diagnose photochemical age may be biased due to point source emissions, for ex le, 53 tonnes of benzene and 86 tonnes of toluene in Sarnia. However, considering multiple ratios leads to better conclusions regarding photochemical aging. Ratios obtained in the s ling c aigns showed significant deviation from those obtained at central monitoring stations, with less difference in the ( m + p )/E ratio but better overall agreement in Windsor than in Sarnia.
Publisher: CMA Joule Inc.
Date: 05-10-2009
DOI: 10.1503/CMAJ.082068
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 21-04-2016
Publisher: Springer Science and Business Media LLC
Date: 05-12-2008
Abstract: We evaluated the impact on personal exposure to air pollutants of following advice which typically accompanies air quality advisories and indices. Scripts prescribed the time, location, duration and nature of activities intended to simulate daily activity patterns for adults and children. Scripts were paired such that one in idual would proceed with usual activities (base scenario), whereas the other (intervention scenario) would alter activities as if following advice. Other than commuting, where the intervention group walked or used public transportation rather than riding in personal vehicles, this group generally spent less time outdoors. Ultra-fine particles (UFPs), particulate matter of median aerodynamic diameter less than 2.5 mum (PM(2.5)) and total volatile organic compounds (VOCs) were measured using s lers carried by in iduals during the course of daily activities. During daytime activities (e.g., work, daycare) constituting the largest share of s ling time (approximately 6 h per day), the intervention group experienced a 14% reduction in exposure to UFPs (P=0.01), a 21% reduction in exposure to PM(2.5) (P=0.08), and an 86% increase in exposure to VOCs (P=0.02). Other findings included an 89% increase in exposure to UFPs (P=0.02) and a threefold increase in exposure to VOCs (P=0.08) in the intervention group during evening cooking. Following smog advisory advice results in reduced exposures to some pollutants, while at the same time increasing exposure to others. Advice needs to be refined giving consideration to overall personal exposure.
Publisher: Elsevier BV
Date: 2011
Publisher: Cold Spring Harbor Laboratory
Date: 08-05-2023
DOI: 10.1101/2023.05.08.539915
Abstract: The present study investigated the extent of prediction in language by reanalysing Nieuwland and colleagues’ (2018) replication of DeLong et al. (2005). Participants (n = 356) viewed sentences containing articles and nouns of varying predictability, while their electroencephalogram (EEG) was recorded. We measured pre-stimulus and N400 event-related activity and calculated lexical surprisal using Generative Pre-trained Transformer-2 (GPT-2) models. Results demonstrate increases in N400 litude as article surprisal increased, supporting DeLong et al.’s (2005) findings. Strikingly, N400 litudes for surprising articles were reduced when prior word surprisal was high, suggesting that surprising input reduces prediction precision for upcoming words. The magnitude of prediction error effects was additionally modulated by inter-in idual differences (in idual alpha frequency and aperiodic slope of resting EEG). These findings indicate that prediction in language is a flexible mechanism that is adaptive across contexts and in iduals. They further support the assumption that prediction is a unified mechanism of cognition.
Publisher: MDPI AG
Date: 04-08-2010
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 06-2009
Publisher: Springer Science and Business Media LLC
Date: 26-05-2010
DOI: 10.1038/JES.2010.15
Abstract: Continuous monitors can be used to supplement traditional filter-based methods of determining personal exposure to air pollutants. They have the advantages of being able to identify nearby sources and detect temporal changes on a time scale of a few minutes. The Windsor Ontario Exposure Assessment Study (WOEAS) adopted an approach of using multiple continuous monitors to measure indoor, outdoor (near-residential) and personal exposures to PM₂.₅, ultrafine particles and black carbon. About 48 adults and households were s led for five consecutive 24-h periods in summer and winter 2005, and another 48 asthmatic children for five consecutive 24-h periods in summer and winter 2006. This article addresses the laboratory and field validation of these continuous monitors. A companion article (Wheeler et al., 2010) provides similar analyses for the 24-h integrated methods, as well as providing an overview of the objectives and study design. The four continuous monitors were the DustTrak (Model 8520, TSI, St. Paul, MN, USA) and personal DataRAM (pDR) (ThermoScientific, Waltham, MA, USA) for PM₂.₅ the P-Trak (Model 8525, TSI) for ultrafine particles and the Aethalometer (AE-42, Magee Scientific, Berkeley, CA, USA) for black carbon (BC). All monitors were tested in multiple co-location studies involving as many as 16 monitors of a given type to determine their limits of detection as well as bias and precision. The effect of concentration and electronic drift on bias and precision were determined from both the collocated studies and the full field study. The effect of rapid changes in environmental conditions on switching an instrument from indoor to outdoor s ling was also studied. The use of multiple instruments for outdoor s ling was valuable in identifying occasional poor performance by one instrument and in better determining local contributions to the spatial variation of particulate pollution. Both the DustTrak and pDR were shown to be in reasonable agreement (R² of 90 and 70%, respectively) with the gravimetric PM₂.₅ method. Both instruments had limits of detection of about 5 μg/m³. The DustTrak and pDR had multiplicative biases of about 2.5 and 1.6, respectively, compared with the gravimetric s lers. However, their average bias-corrected precisions were <10%, indicating that a proper correction for bias would bring them into very good agreement with standard methods. Although no standard methods exist to establish the bias of the Aethalometer and P-Trak, the precision was within 20% for the Aethalometer and within 10% for the P-Trak. These findings suggest that all four instruments can supply useful information in environmental studies.
Publisher: Cold Spring Harbor Laboratory
Date: 09-04-2031
No related grants have been discovered for Alex Chatburn.