Phase-space path-integral representation of the quantum density of states: Monte Carlo simulation of strongly correlated soft-sphere fermions.

The Wigner formulation of quantum mechanics is used to derive a path-integral representation of the quantum density of states (DOS) of strongly correlated fermions in the canonical ensemble. A path-integral Monte Carlo approach for the simulation of DOS and other thermodynamic functions is suggested. The derived Wigner function in the phase space resembles the Maxwell-Boltzmann distribution but allows for quantum effects. We consider a three-dimensional quantum system of strongly correlated soft-sphere fermions at different densities and temperatures. The calculated properties include the DOS, momentum distribution functions, spin-resolved radial distribution functions, potentials of mean force, and related energy levels obtained from the Bohr-Sommerfeld condition. We observe sharp peaks on DOS and momentum distribution curves, which are explained by the appearance of fermionic bound states.

Accuracy of artificial intelligence-assisted growth prediction in skeletal Class I preadolescent patients using serial lateral cephalograms for a 2-year growth interval.

OBJECTIVE: To investigate the accuracy of artificial intelligence-assisted growth prediction using a convolutional neural network (CNN) algorithm and longitudinal lateral cephalograms (Lat-cephs). MATERIALS AND METHODS: A total of 198 Japanese preadolescent children, who had skeletal Class I malocclusion and whose Lat-cephs were available at age 8 years (T0) and 10 years (T1), were allocated into the training, validation, and test phases (n = 161, n = 17, n = 20). Orthodontists and the CNN model identified 28 hard-tissue landmarks (HTL) and 19 soft-tissue landmarks (STL). The mean prediction error values were defined as 'excellent,' 'very good,' 'good,' 'acceptable,' and 'unsatisfactory' (criteria: 0.5 mm, 1.0 mm, 1.5 mm, and 2.0 mm, respectively). The degree of accurate prediction percentage (APP) was defined as 'very high,' 'high,' 'medium,' and 'low' (criteria: 90%, 70%, and 50%, respectively) according to the percentage of subjects that showed the error range within 1.5 mm. RESULTS: All HTLs showed acceptable-to-excellent mean PE values, while the STLs Pog', Gn', and Me' showed unsatisfactory values, and the rest showed good-to-acceptable values. Regarding the degree of APP, HTLs Ba, ramus posterior, Pm, Pog, B-point, Me, and mandibular first molar root apex exhibited low APPs. The STLs labrale superius, lower embrasure, lower lip, point of lower profile, B', Pog,' Gn' and Me' also exhibited low APPs. The remainder of HTLs and STLs showed medium-to-very high APPs. CONCLUSION: Despite the possibility of using the CNN model to predict growth, further studies are needed to improve the prediction accuracy in HTLs and STLs of the chin area.

Retrospective comparisons of competing demographic models give clarity from "messy" management on a Scottish grouse moor.

Retrospective comparison of predictive models that describe competing hypotheses regarding system function can shed light on regulatory mechanisms within the framework of adaptive resource management. We applied this approach to a 28-year study of red grouse (Lagopus lagopus scotica) in Scotland, with the aims of reducing uncertainty regarding important drivers of grouse population dynamics, and of evaluating the efficacy of using seasonal versus annual model assessments. We developed three sets of models that predicted pre-breeding and post-breeding grouse density, matching the timing of grouse counts on the ground. We updated conditions and management through time in the spirit of a real-time, adaptive management program and used a Bayesian model weight updating process to compare model predictions with empirical grouse densities. The first two model sets involved single annual updates from either pre-breeding or post-breeding counts; the third set was updated twice a year. Each model set comprised seven models representing increasingly complex hypotheses regarding potentially important drivers of grouse: the baseline model included weather and parasite effects on productivity, shooting losses and density-dependent overwinter survival; subsequent models incorporated the effect of habitat gain/loss (HAB), control of non-protected predators (NPP) and predation by protected hen harriers (Circus cyaneus, HH) and buzzards (Buteo buteo, BZ). The weight of evidence was consistent across model sets, settling within 10 years on the harrier (NPP + HH), buzzard (NPP + HH + BZ) and buzzard + habitat (NPP + HH + BZ + HAB) models, and downgrading the baseline + habitat, non-protected predator, and non-protected predator + habitat models. By the end of the study only the buzzard and buzzard + habitat models retained substantial weights, emphasizing the dynamical complexity of the system. Habitat inclusion failed to improve model predictions, implying that over the period of this study habitat quantity was unimportant in determining grouse abundance. Comparing annually and biannually assessed model sets, the main difference was in the baseline model, whose weight increased or remained stable when assessed annually, but collapsed when assessed biannually. Our adaptive modeling approach is suitable for many ecological situations in which a complex interplay of factors makes experimental manipulation difficult.

Visualizing social-ecological intensities for management of recreation visitors in a multiuse system.

Accounting for the variation of visitor conflicts and ecological disturbance of outdoor recreation activities across space and time can cause difficulty for managers seeking to make decisions in social-ecological systems (SESs). We develop a method to quantify and visualize social and ecological intensities resulting from outdoor recreation. We demonstrate the utility of our method at Valentine National Wildlife Refuge, where we conducted onsite surveys for an entire year of recreationists participating in consumptive (i.e., hunting), intermediate-consumptive (i.e., fishing) and nonconsumptive (e.g., hiking) activities. We use survey results and combine them with expert consensus by engaging refuge managers and scientists (i.e., Delphi method) to chart patterns in social (e.g., visitor conflicts) and ecological (e.g., damages to natural resources) intensities across multiple spatial and temporal scales. We highlight unexpected patterns that are revealed by collectively considering multi-activity groups through space and time and combining different survey methods (onsite, Delphi method). Based on the consensus reached using the Delphi method, the consumptive group had the greatest potential for social conflicts and ecological disturbances. Social and ecological intensities (i.e., hotspots) of recreation varied across lake types and seasons, highlighting high-intensity areas and periods on the refuge. Accounting for diverse outdoor recreation activities and coinciding social and ecological intensities will allow managers of SESs the ability to concomitantly preserve ecological resources, prioritize conservation efforts, and minimize visitor conflicts. We demonstrate the utility and ease of use of this technique, which can be implemented by managers and scientists within their respective SES of interest.

Uniform electron gas at finite temperature by fermionic-path-integral Monte Carlo simulations.

In this paper we study thermodynamic properties of uniform electron gas (UEG) over wide density and temperature range, using the improved fermionic-path-integral Monte Carlo (FPIMC) method. This method demonstrates a significant reduction of the "fermionic sign problem," which takes place in standard path-integral Monte Carlo simulations of degenerate fermionic systems. We introduce three basic improvements. The first one is the improved treatment of exchange interaction, achieved by the proper change of variables in the path-integral measure. The second improvement is the inclusion of long-range Coulomb effects into an angle-averaged effective potential, as proposed by Yakub and Ronchi [J. Chem. Phys. 119, 11556 (2003)JCPSA60021-960610.1063/1.1624364]. The third improvement is the angle-averaging of an exchange determinant, describing the fermionic exchange interaction not only between particles in the main Monte Carlo cell, but also with electrons in the nearest periodic images. The FPIMC shows very good agreement with analytical data for ideal Fermi gas. For strongly coupled UEG under warm dense matter conditions we compare our total and exchange-correlation energy results with other Monte Carlo approaches.

Fire legacies in eastern ponderosa pine forests.

Disturbance legacies structure communities and ecological memory, but due to increasing changes in disturbance regimes, it is becoming more difficult to characterize disturbance legacies or determine how long they persist. We sought to quantify the characteristics and persistence of material legacies (e.g., biotic residuals of disturbance) that arise from variation in fire severity in an eastern ponderosa pine forest in North America. We compared forest stand structure and understory woody plant and bird community composition and species richness across unburned, low-, moderate-, and high-severity burn patches in a 27-year-old mixed-severity wildfire that had received minimal post-fire management. We identified distinct tree densities (high: 14.3 ± 7.4 trees per ha, moderate: 22.3 ± 12.6, low: 135.3 ± 57.1, unburned: 907.9 ± 246.2) and coarse woody debris cover (high: 8.5 ± 1.6% cover per 30 m transect, moderate: 4.3 ± 0.7, low: 2.3 ± 0.6, unburned: 1.0 ± 0.4) among burn severities. Understory woody plant communities differed between high-severity patches, moderate- and low-severity patches, and unburned patches (all p < 0.05). Bird communities differed between high- and moderate-severity patches, low-severity patches, and unburned patches (all p < 0.05). Bird species richness varied across burn severities: low-severity patches had the highest (5.29 ± 1.44) and high-severity patches had the lowest (2.87 ± 0.72). Understory woody plant richness was highest in unburned (5.93 ± 1.10) and high-severity (5.07 ± 1.17) patches, and it was lower in moderate- (3.43 ± 1.17) and low-severity (3.43 ± 1.06) patches. We show material fire legacies persisted decades after the mixed-severity wildfire in eastern ponderosa forest, fostering distinct structures, communities, and species in burned versus unburned patches and across fire severities. At a patch scale, eastern and western ponderosa system responses to mixed-severity fires were consistent.

Engaging stakeholders in research to address water-energy-food (WEF) nexus challenges.

The water-energy-food (WEF) nexus has become a popular, and potentially powerful, frame through which to analyse interactions and interdependencies between these three systems. Though the case for transdisciplinary research in this space has been made, the extent of stakeholder engagement in research remains limited with stakeholders most commonly incorporated in research as end-users. Yet, stakeholders interact with nexus issues in a variety of ways, consequently there is much that collaboration might offer to develop nexus research and enhance its application. This paper outlines four aspects of nexus research and considers the value and potential challenges for transdisciplinary research in each. We focus on assessing and visualising nexus systems; understanding governance and capacity building; the importance of scale; and the implications of future change. The paper then proceeds to describe a novel mixed-method study that deeply integrates stakeholder knowledge with insights from multiple disciplines. We argue that mixed-method research designs-in this case orientated around a number of cases studies-are best suited to understanding and addressing real-world nexus challenges, with their inevitable complex, non-linear system characteristics. Moreover, integrating multiple forms of knowledge in the manner described in this paper enables research to assess the potential for, and processes of, scaling-up innovations in the nexus space, to contribute insights to policy and decision making.

The perpetual state of emergency that sacrifices protected areas in a changing climate.

A modern challenge for conservation biology is to assess the consequences of policies that adhere to assumptions of stationarity (e.g., historic norms) in an era of global environmental change. Such policies may result in unexpected and surprising levels of mitigation given future climate-change trajectories, especially as agriculture looks to protected areas to buffer against production losses during periods of environmental extremes. We assessed the potential impact of climate-change scenarios on the rates at which grasslands enrolled in the Conservation Reserve Program (CRP) are authorized for emergency harvesting (i.e., biomass removal) for agricultural use, which can occur when precipitation for the previous 4 months is below 40% of the normal or historical mean precipitation for that 4-month period. We developed and analyzed scenarios under the condition that policy will continue to operate under assumptions of stationarity, thereby authorizing emergency biomass harvesting solely as a function of precipitation departure from historic norms. Model projections showed the historical likelihood of authorizing emergency biomass harvesting in any given year in the northern Great Plains was 33.28% based on long-term weather records. Emergency biomass harvesting became the norm (>50% of years) in the scenario that reflected continued increases in emissions and a decrease in growing-season precipitation, and areas in the Great Plains with higher historical mean annual rainfall were disproportionately affected and were subject to a greater increase in emergency biomass removal. Emergency biomass harvesting decreased only in the scenario with rapid reductions in emissions. Our scenario-impact analysis indicated that biomass from lands enrolled in the CRP would be used primarily as a buffer for agriculture in an era of climatic change unless policy guidelines are adapted or climate-change projections significantly depart from the current consensus.

Present and future thermal environments available to Sharp-tailed Grouse in an intact grassland.

Better understanding animal ecology in terms of thermal habitat use has become a focus of ecological studies, in large part due to the predicted temperature increases associated with global climate change. To further our knowledge on how ground-nesting endotherms respond to thermal landscapes, we examined the thermal ecology of Sharp-tailed Grouse (Tympanuchus phasianellus) during the nesting period. We measured site-specific iButton temperatures (TiB) and vegetation characteristics at nest sites, nearby random sites, and landscape sites to assess thermal patterns at scales relevant to nesting birds. We asked if microhabitat vegetation characteristics at nest sites matched the characteristics that directed macrohabitat nest-site selection. Grouse selected sites sheltered by dense vegetation for nesting that moderated TiB on average up to 2.7°C more than available landscape sites. Successful nests were positioned in a way that reduced exposure to thermal extremes by as much as 4°C relative to failed nests with an overall mean daytime difference (±SE) of 0.4 ±0.03°C. We found that macrohabitat nest-site selection was guided by dense vegetation cover and minimal bare ground as also seen at the microhabitat scale. Global climate projections for 2080 suggest that TiB at nest sites may approach temperatures currently avoided on the landscape, emphasizing a need for future conservation plans that acknowledge fine-scale thermal space in climate change scenarios. These data show that features of grassland landscapes can buffer organisms from unfavorable microclimatic conditions and highlight how thermal heterogeneity at the individual-level can drive decisions guiding nest site selection.

Towards Personal Exposures: How Technology Is Changing Air Pollution and Health Research.

PURPOSE OF REVIEW: We present a review of emerging technologies and how these can transform personal air pollution exposure assessment and subsequent health research. RECENT FINDINGS: Estimating personal air pollution exposures is currently split broadly into methods for modeling exposures for large populations versus measuring exposures for small populations. Air pollution sensors, smartphones, and air pollution models capitalizing on big/new data sources offer tremendous opportunity for unifying these approaches and improving long-term personal exposure prediction at scales needed for population-based research. A multi-disciplinary approach is needed to combine these technologies to not only estimate personal exposures for epidemiological research but also determine drivers of these exposures and new prevention opportunities. While available technologies can revolutionize air pollution exposure research, ethical, privacy, logistical, and data science challenges must be met before widespread implementations occur. Available technologies and related advances in data science can improve long-term personal air pollution exposure estimates at scales needed for population-based research. This will advance our ability to evaluate the impacts of air pollution on human health and develop effective prevention strategies.

Assessing landscape constraints on species abundance: does the neighborhood limit species response to local habitat conservation programs?

Landscapes in agricultural systems continue to undergo significant change, and the loss of biodiversity is an ever-increasing threat. Although habitat restoration is beneficial, management actions do not always result in the desired outcome. Managers must understand why management actions fail; yet, past studies have focused on assessing habitat attributes at a single spatial scale, and often fail to consider the importance of ecological mechanisms that act across spatial scales. We located survey sites across southern Nebraska, USA and conducted point counts to estimate Ring-necked Pheasant abundance, an economically important species to the region, while simultaneously quantifying landscape effects using a geographic information system. To identify suitable areas for allocating limited management resources, we assessed land cover relationships to our counts using a Bayesian binomial-Poisson hierarchical model to construct predictive Species Distribution Models of relative abundance. Our results indicated that landscape scale land cover variables severely constrained or, alternatively, facilitated the positive effects of local land management for Ring-necked Pheasants.

[Occupational skin diseases as social-economic problem].

The article deals with factors causative of high social-economic importance of occupational skin diseases, presents parameters of occupational skin diseases prevalence, exogenous and endogenous risk factors of occupational skin diseases. This conditions appear to have negative influence on everyday life and occupational activities of the patients, induce lower quality of life and work performance. Pathogenesis and clinical signs, laboratory values characterizing atopic and allergic dermatitis are discussed. The authors necessitated a search of signs or complex of signs, that can point to predisposition for sensitization of individuals exposed to occupational hazards.

[Information value of lipid peroxidation parameters in patients with occupational allergic dermatoses].

Evaluation of lipid peroxidation in patients with occupational allergic dermatoses revealed activation of free radical oxidation. Serum levels of diene conjugates and end products of free radical lipid peroxidation appeared to be informative parameters for assessing influences on body system and for estimating the disease severity and the individual protective means efficiency.

Exercise in the community for people with minimal gait impairment due to MS: an assessor-blind randomized controlled trial.

BACKGROUND: While there is an increasing body of evidence supporting the efficacy of exercise in people with multiple sclerosis (MS), additional information on the effectiveness of combining aerobic and resistance training, and yoga is required. OBJECTIVES: This study evaluated the effectiveness of community exercise interventions for people with MS having minimal gait impairment. METHODS: A multi-centred, block-randomised, assessor-blinded, controlled trial was conducted. Participants were randomised in groups of eight to physiotherapist (PT)-led exercise (n = 80), yoga (n = 77), fitness instructor (FI)-led exercise (n = 86) and they took part in weekly community-based group exercise sessions. Those in the control group were asked not to change of their exercise habits (n = 71). The primary outcome was the Multiple Sclerosis Impact Scale (MSIS) 29v2 physical component, measured before and after the 10-week intervention. Secondary outcomes were the MSIS 29v2 psychological component, the Modified Fatigue Impact Scale (MFIS) and the 6-Minute Walk Test (6MWT). RESULTS: The group x time interaction approached significance for the MSIS-29v2 physical component (f = 2.48, p = 0.061) and MFIS total (f = 2.50, p = 0.06), and it was significant for the MFIS physical subscale (f = 4.23, p = 0.006). All three exercise interventions led to a statistically significant improvement on the MSIS-29 psychological component and both the MFIS total and physical subscales, which were greater than the control (p < 0.05). Only the PT-led and FI-led interventions significantly improved the MSIS-29 physical and 6MWT to levels greater than the control (p < 0.05). CONCLUSIONS: This study provides evidence for the positive effect of exercise on the physical impact of MS and fatigue. The group nature of the classes may have contributed to the positive effects seen on the psychological impact of MS.

Systemic FasL neutralization increases eosinophilic inflammation in a mouse model of asthma.

BACKGROUND: Eosinophils and lymphocytes are pathogenically important in allergic inflammation and sensitive to Fas-mediated apoptosis. Fas ligand (FasL) activity therefore should play a role in regulating the allergic immune response. We aimed to characterize the role of FasL expression in airway eosinophilia in Aspergillus fumigatus (Af)-induced sensitization and to determine whether FasL neutralization alters the inflammatory response. METHODS: Sensitized Balb/c mice were killed before (day 0) and 1, 7 and 10 days after a single intranasal challenge with Af. Animals received either neutralizing antibody to FasL (clone MFL4) or irrelevant hamster IgG via intraperitoneal injection on days -1 and 5. FasL expression, BAL and tissue inflammatory cell and cytokine profile, and apoptosis were assessed. RESULTS: Postchallenge FasL gene expression in BAL cells and TUNEL positivity in the airways coincided with the height of inflammatory cell influx on day 1, while soluble FasL protein was released on day 7, preceding resolution of the inflammatory changes. Although eosinophil numbers showed a negative correlation with soluble FasL levels in the airways, MBP(+) eosinophils remained TUNEL negative in the submucosal tissue, throughout the 10-day period after Af challenge. Systemic FasL neutralization significantly enhanced BAL and tissue eosinophil counts. This effect was associated with increased activation of T cells and release of IL-5, IL-9, and GM-CSF in the BAL fluid of mice, indicating an involvement of pro-eosinophilic survival pathways. CONCLUSIONS: FasL activity may play an active role in resolving eosinophilic inflammation through regulating T cells and pro-eosinophilic cytokine release during the allergic airway response.

Multimodel inference and adaptive management.

Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study's inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.

Membrane transport proteins in human melanoma: associations with tumour aggressiveness and metastasis.

BACKGROUND: Malignant melanoma, generally described as incurable, is notoriously refractory to chemotherapy. The mechanisms contributing to this have not yet been defined and the contributions of drug efflux pumps, implicated in chemo-resistance of many other cancer types, have not been extensively investigated in melanoma. METHODS: In this study, expression of multi-drug resistant (MDR1/P-gp and MRP-1) proteins was examined, by immunohistochemistry, in archival specimens from 134 melanoma patients. This included 92 primary tumours and 42 metastases. RESULTS: On assessing all specimens, MRP-1 and MDR1/P-gp expression was found to be common, with the majority (81%) of melanomas expressing at least one of these efflux pumps. Although there is significant association between expression of these pumps (P=0.007), MRP-1 was found to be the predominant (67% of cases) form detected. chi(2) analysis showed significant associations between expression of MRP-1 and/or MDR1/P-gp and the aggressive nature of this disease specifically increased Breslow's depth, Clark's level and spread to lymph nodes. This association with aggressiveness and spread is further supported by the observation that a significantly higher percentage of metastases, than primary tumours, express MRP-1 (91% vs 57%; P<0.0001) and MDR1/P-gp (74% vs 50%; P=0.010). CONCLUSION: The predominant expression of these pumps and, in particular, MRP-1 suggests that they may be important contributors to the inherent aggressive and resistant nature of malignant melanoma.

Development of training syllabi for radiation protection and quality assurance of dual-energy X-ray absorptiometry (DXA) systems.

The use of dual-energy X-ray absorptiometry (DXA) scanners for measuring bone mineral density (BMD) is on the increase. A single DXA scan is a relatively low-dose diagnostic X-ray examination; however, radiation protection (RP) issues should not be trivialised. One objective of the EU 6th Framework SENTINEL co-ordination action was to develop training syllabi in RP and quality assurance (QA) for BMD, and this study presents the results. An EU-wide survey was carried out which confirmed that there was a need for an accredited DXA RP training course in many EU states. There is also limited published guidance on acceptance testing/QA for DXA. Two training syllabi were developed: one on RP and one on QA of DXA systems. A training course was delivered in Ireland in 2006 by the Medical Physics & Bioengineering Department of St James's Hospital, Dublin. Following the training course, a PC-based training CD was developed and will be made available. A harmonised approach to training will promote consistent approaches to radiation safety across the EU.

QA/acceptance testing of DEXA X-ray systems used in bone mineral densitometry.

New developments in dual energy X-ray absorptiometry (DEXA) imaging technology [fan beam and cone beam (CB)] result in higher exposure levels, shorter scan times, increased patient throughput and increased shielding requirements. This study presents the results of a European survey detailing the number and location of DEXA systems in SENTINEL partner states and the QA (quality assurance) currently performed by physicists and operators in these centres. The results of a DEXA equipment survey based on an in-house developed QA protocol are presented. Measurements show that the total effective dose to the patient from a spine and dual femur DEXA examination on the latest generation DEXA systems is comparable with a few microSv at most. Scatter measurements showed that the use of a mobile lead screen for staff protection was necessary for fan and CB systems. Scattered dose from newer generation systems may also exceed the exposure limits for the general public so structural shielding may also be required. Considerable variation in the magnitude and annual repeatability of half value layer was noted between different models of DEXA scanners. A comparative study of BMD (bone mineral density) accuracy using the European Spine Phantom highlighted a deviation of up to 7% in BMD values between scanners of different manufacturers.

Quality assurance of computed and digital radiography systems.

Computed radiography (CR) and digital radiography (DR) are replacing traditional film screen radiography as hospitals move towards digital imaging and picture archiving and communication systems (PACS). Both IPEM and KCARE have recently published quality assurance and acceptance testing guidelines for DR. In this paper, the performance of a range of CR and DR systems is compared. Six different manufacturers are included. Particular attention is paid to the performance of the systems under automatic exposure control (AEC). The patient is simulated using a range of thicknesses of tissue equivalent material. Image quality assessment was based on detector assessment protocols and includes pixel value measures as well as subjective assessment using Leeds Test Objects. The protocols for detector assessment cover a broad range of tests and in general detectors (whether DR or CR) performed satisfactorily. The chief limitation in performing these tests was that not all systems provided ready access to pixel values. Subjective tests include the use of the Leeds TO20. As part of this work, suggested reference values are provided to calculate the TO20 image quality factor. One consequence of moving from film screen to digital technologies is that the dynamic range of digital detectors is much wider, and increased exposures are no longer evident from changes in image quality. As such, AEC is a key parameter for CR and DR. Dose was measured using a standard phantom as a basic means of comparing systems. In order to assess the AEC performance, exit doses were also measured while varying phantom thickness. Signal-to-noise ratios (SNRs) were calculated on a number of systems where pixel values were available. SNR was affected by the selection of acquisition protocol. Comparisons between different technologies and collation of data will help refine acceptance thresholds and contribute to optimising dose and image quality.