Uncorrected Data Research Articles

Measuring the in situ tilt orientation of fish and zooplankton using stereo photogrammetric methods

AbstractAcoustic‐derived estimates of fish and zooplankton numerical and biomass density rely on knowledge of the sound scattered by an individual, known as target strength (TS). An important, but difficult to measure, factor in determining TS is the tilt orientation of animals in relation to the insonifying acoustic wave. Underwater stereo‐camera systems can provide in situ tilt measurements for fish and zooplankton. We describe a protocol to remove the effects of camera pitch and roll from tilt measurements using a low‐cost orientation sensor and a mathematical correction. A tank experiment indicated that tilt estimates made with corrected pitch and roll position data improved measurement accuracy as compared to those made with uncorrected position data. This experiment also provided empirical limits on the range of yaw values that allowed for accurate estimation of target tilt and length. We further tested this protocol using an in situ collection of krill stereo images collected in the Gulf of Alaska. Krill tilts calculated with pitch‐ and roll‐corrected position data were an average of 10° different than those collected with uncorrected position data. Our pitch‐ and roll‐correction improved the accuracy of stereo photogrammetric tilt estimation. Extending this method to appropriate spatial and temporal scales could allow for more accurate parametrization of TS models.

A new method for correcting locational error from aerial surveys improves habitat model performance

AbstractThe utility of aerial survey data in modelling the distribution of wildlife has been questioned due to locational errors. Yet, little effort has been made to correct these errors. Here, a new method is proposed for correcting locational errors associated with aerial survey data. We further tested whether the correction improves model performance using elephant aerial survey data collected at three protected sites in Zimbabwe. Our correction method succeeded in shifting location by 143–177 m from the line of flight. Based on the true skill statistic, models built using corrected data in Hwange and Mana Pools national parks were significantly better than those from uncorrected data and only in Gonarezhou national park were no significant differences in model performance observed. These results underscore the benefit of applying the new correction method in modelling wildlife distribution. The other key result is that the correction seems to be more beneficial in heterogeneous landscapes than homogeneous ones for in the former, a small shift in location results in the sampling of different habitats than where sightings were made. The proposed method opens new opportunities for improving the accuracy of aerial survey data in species distribution modelling.

Detector-specific correction factors in radiosurgery beams and their impact on dose distribution calculations.

Silicon-diode-based detectors are commonly used for the dosimetry of small radiotherapy beams due to their relatively small volumes and high sensitivity to ionizing radiation. Nevertheless, silicon-diode-based detectors tend to over-respond in small fields because of their high density relative to water. For that reason, detector-specific beam correction factors () have been recommended not only to correct the total scatter factors but also to correct the tissue maximum and off-axis ratios. However, the application of to in-depth and off-axis locations has not been studied. The goal of this work is to address the impact of the correction factors on the calculated dose distribution in static non-conventional photon beams (specifically, in stereotactic radiosurgery with circular collimators). To achieve this goal, the total scatter factors, tissue maximum, and off-axis ratios were measured with a stereotactic field diode for 4.0-, 10.0-, and 20.0-mm circular collimators. The irradiation was performed with a Novalis® linear accelerator using a 6-MV photon beam. The detector-specific correction factors were calculated and applied to the experimental dosimetry data for in-depth and off-axis locations. The corrected and uncorrected dosimetry data were used to commission a treatment planning system for radiosurgery planning. Various plans were calculated with simulated lesions using the uncorrected and corrected dosimetry. The resulting dose calculations were compared using the gamma index test with several criteria. The results of this work presented important conclusions for the use of detector-specific beam correction factors ( in a treatment planning system. The use of for total scatter factors has an important impact on monitor unit calculation. On the contrary, the use of for tissue-maximum and off-axis ratios has not an important impact on the dose distribution calculation by the treatment planning system. This conclusion is only valid for the combination of treatment planning system, detector, and correction factors used in this work; however, this technique can be applied to other treatment planning systems, detectors, and correction factors.

Influence of k-space trajectory corrections on proton density mapping with ultrashort echo time imaging: Application for imaging of short T2 components in white matter

PurposeTo evaluate the impact of MR gradient system imperfections and limitations for the quantitative mapping of short T2* signals performed by ultrashort echo time (UTE) acquisition approach. Materials and methodsThe measurement of short T2* signals from a phantom and a healthy volunteer study (8 subjects of average age 28 ± 4 years) were performed on a 3T scanner. The characteristics of the gradient system were obtained using calibration method performed directly on the measured subject or phantom. This information was used to calculate the actual sampling trajectory with the help of a parametric eddy current model. The actual sample positions were used to reconstruct corrected images and compared with uncorrected data. ResultsComparison of both approaches, i.e., without and with correction of k-space sampling trajectories revealed substantial improvement when correction was applied. The phantom experiments demonstrate substantial in-plane signal intensity variations for uncorrected sampling trajectories. In the case of the volunteer study, this led to significant differences in relative proton density (RPD) estimation between the uncorrected and corrected data (P = 0.0117 by Wilcoxon matched-pairs test) and provides for about ~15% higher values for short T2* components of white matter (WM) in the case of uncorrected images. ConclusionThe imperfection of the applied gradients could induce errors in k-space data sampling which further propagates into the fidelity of the UTE images and jeopardizes precision of quantification. However, the study proved that measurement of gradient errors together with correction of sample positions can contribute to increased accuracy and unbiased characterization of short T2* signals.

The effect of the correction of self-assessment-based chance success on psychometric characteristics of the test

This study examines the effect of self-assessment-based chance success on psychometric characteristics of the test. First, the data was cleared of chance success by means of correction-for-guessing formula and self-assessment, and then statistical analyses were conducted. Item discriminations showed an increase when the correction-for-guessing formula was used; and when self-assessment was used, they showed variability. Test validity increased when correction formula was used; and when self-assessment was used, a slight decrease was observed. Besides, this study examined the effect of correction for chance success upon corrected self-assessment based on IRT guessing parameter. It was observed that the data that were not corrected in accordance with chance scores had higher guessing parameters than those corrected in accordance with self-assessment. In addition, it was evident that the difference between the guessing parameters of the uncorrected data and the data cleared of chance scores by means of self-assessment was significant. It was also revealed that the correction of self-assessment-based chance success have an advantage over classical correction for guessing formula on psychometric characteristics of the test.

Correcting for solvent replacement effects in quartz crystal microbalance measurements

The quartz crystal microbalance (QCM) is frequently used to measure the adsorption of molecules from a liquid bulk phase onto surfaces. However, determining the true mass adsorbed onto the surface from the raw frequency shift values often involves various correction factors. In this paper, we highlight yet another correction factor that arises from correcting for the bulk, Kanazawa–Gordon-like solvent contribution to the total frequency shift. This correction factor depends on the cross-sectional size of the solute and solvent molecules on the surface, and shows that the apparent mass adsorbed reported by the QCM can significantly differ from the true mass. By performing molecular dynamics simulations of adsorption from a liquid phase, we are able to accurately estimate the molecular sizes of the solvent and solute. Using stearic acid in heptane solutions, and iron oxide surfaces, we quantify the magnitude of the correction factor by comparing the uncorrected and corrected QCM data. This paper emphasizes the importance of accounting for deviations from widely used models in analyzing measured frequency shifts in QCM experiments, to accurately obtain the true adsorbed mass.

The geomagnetic jerk of 2003.5-characterisation with regional observatory secular variation data

The 2003.5 geomagnetic jerk was identified in geomagnetic records from satellite data, and a matching feature reported in variations in length-of-day (ΔLOD), but detailed study has been hampered by lack of geomagnetic observatory data where it appears strongest. Here we examine secular variation (annual differences of monthly means) based on a new resource of 43 Chinese observatory records for 1998 until the present, focusing on 10 series of particularly high quality and consistency. To obtain a clean series, we calculate the covariance matrix of residuals between measurements and a state-of-the-art field model, CHAOS-6, and use eigenvalue analysis to remove noisy contributions from the uncorrected data. The magnitude of the most significant eigenvector correlates well with Dcx (corrected, extended Dst), suggesting the noise originates from unmodelled external magnetic field. Removal of this noise eliminates much coherent misfit around 2003—2005; nevertheless, the 2003.5 jerk is seen clearly in the first time derivative of the East component in Chinese data, and is also seen in the first time derivative of the vertical component in European data. Estimates of the jerk time are centred on 2003.5, but with some spatial variation; this variation can be eliminated if we allow a discontinuity in the secular variation as well as its temporal gradient. Both regions also provide evidence for a jerk around 2014, although less clearly than 2003.5. We create a new field model based on new data and CHAOS-6 to further examine the regional signals. The new model is close to CHAOS-6, but better fits Chinese data, although modelling also identifies some data features as unphysical.

Dosimetric Impact of Metal Artifacts From Dental Implants and Clinical Implications for Head And Neck IMRT Treatment Planning

Dental implants are increasingly prevalent in the head and neck cancer patient population and result in the creation of artifacts on CT imaging for treatment planning. In our practice, we have noticed more mucosal toxicity adjacent to dental implants and hypothesized that this observation may be due to errors in dose calculation. The purpose of this study was to retrospectively evaluate dosimetric differences in target coverage and organ at risk (OAR) sparing when adjusting for spurious CT measurements attributed to dental metal artifact. Nine patients with dental implants who were previously treated at our institution with definitive radiation for oropharyngeal cancer were selected for this retrospective study. All patients were treated with 6 MV photons using intensity modulated radiation therapy (IMRT). Dose calculation was performed using an algorithm with heterogeneity corrections. Dental implant and streak artifact volumes were contoured and new IMRT plans were generated with identical beam geometry and monitor units using the uncorrected reference CT data set and a corrected CT data set. Artifacts were assigned a soft tissue electron density value with a Hounsfield unit (HU) of zero. Using descriptive statistics, target volumes and OAR dosimetry were reported and compared between the clinical treatment plans and re-calculated plans. Target volumes analyzed were GTV (D95, D98, D99), intermediate-risk PTV (D95, D98, D99), and high-risk PTV (D95, D98, D99, D2cc). The maximum dose, Dmax, was also collected for each plan. OARs analyzed included the bilateral parotids (mean), oral uninvolved (mean), OAR pharynx (mean), mandible (max), and cord (max). The median artifact volume was 41.6 cc (range, 22.5 to 56.8 cc). When accounting for artifact error, there were small but statistically significant relative increases in Dmax (0.24%, P=.0273), mean oral uninvolved dose (0.24%, P=.0234), and mean left parotid dose (0.20%, P=.0469). On average, the hot spot (Dmax) increased by 181 cGy when accounting for artifact. There were no significant dosimetric differences between plans in terms of GTV, intermediate-risk PTV, and high-risk PTV coverage. There were no significant differences for the mandible max dose, cord max dose, OAR pharynx mean dose, or the right parotid mean dose. In this retrospective study, there was minimal dose variation to target volumes and OAR structures when substituting artifact with soft tissue density HUs. There were significant differences in terms of maximum dose and dose to the uninvolved oral cavity, which suggests that ignoring artifacts in CT images during planning may result in greater hot spots. While small, these differences are worthy of further study as they may at least partially contribute to increased rates of empirically observed mucosal toxicity in the vicinity of dental artifacts.

Radar-based quantitative precipitation estimation for the identification of debris flow occurrence over earthquake-affected regions in Sichuan, China

Abstract. Both Ms 8.0 Wenchuan earthquake on 12 May 2008 and Ms 7.0 Lushan earthquake on 20 April 2013 occurred in the province of Sichuan, China. In the earthquake-affected mountainous area, a large amount of loose material caused a high occurrence of debris flow during the rainy season. In order to evaluate the rainfall intensity–duration (I–D) threshold of the debris flow in the earthquake-affected area, and to fill up the observational gaps caused by the relatively scarce and low-altitude deployment of rain gauges in this area, raw data from two S-band China New Generation Doppler Weather Radar (CINRAD) were captured for six rainfall events that triggered 519 debris flows between 2012 and 2014. Due to the challenges of radar quantitative precipitation estimation (QPE) over mountainous areas, a series of improvement measures are considered: a hybrid scan mode, a vertical reflectivity profile (VPR) correction, a mosaic of reflectivity, a merged rainfall–reflectivity (R − Z) relationship for convective and stratiform rainfall, and rainfall bias adjustment with Kalman filter (KF). For validating rainfall accumulation over complex terrains, the study areas are divided into two kinds of regions by the height threshold of 1.5 km from the ground. Three kinds of radar rainfall estimates are compared with rain gauge measurements. It is observed that the normalized mean bias (NMB) is decreased by 39 % and the fitted linear ratio between radar and rain gauge observation reaches at 0.98. Furthermore, the radar-based I–D threshold derived by the frequentist method is I = 10.1D−0.52 and is underestimated by uncorrected raw radar data. In order to verify the impacts on observations due to spatial variation, I–D thresholds are identified from the nearest rain gauge observations and radar observations at the rain gauge locations. It is found that both kinds of observations have similar I–D thresholds and likewise underestimate I–D thresholds due to undershooting at the core of convective rainfall. It is indicated that improvement of spatial resolution and measuring accuracy of radar observation will lead to the improvement of identifying debris flow occurrence, especially for events triggered by the strong small-scale rainfall process in the study area.

Unbiased Approach to Counteract Upward Drift in Cerebrospinal Fluid Amyloid-β 1-42 Analysis Results.

Low cerebrospinal fluid (CSF) amyloid-β 1-42 (Aβ 1-42) concentrations indicate amyloid plaque accumulation in the brain, a pathological hallmark of Alzheimer disease (AD). Innotest assay values of Aβ 1-42 have gradually increased over the past 2 decades, which might lead to misclassification of AD when a single cutpoint for abnormality is used. We propose an unbiased approach to statistically correct for drift. We determined year-specific cutpoints with Gaussian mixture modeling, based on the cross-section of bimodal distributions of Aβ 1-42 concentrations in 4397 memory clinic patients. This allowed us to realign year-specific cutpoints as an unbiased method to remove drift from the data. Sensitivity and specificity to detect AD dementia were compared between corrected and uncorrected values. Aβ 1-42 values increased 22 pg/mL annually, and this could not be explained by changes in cohort composition. Our approach removed time dependencies [β (SE) = 0.07 (0.59); P = 0.91]. Statistically correcting for drift improved the sensitivity to detect AD dementia to 0.90 (95% CI, 0.89-0.92) from at least 0.66 (95% CI, 0.64-0.69) based on uncorrected data. Specificity became lower (0.69; 95% CI, 0.67-0.70) vs at most 0.80 (95% CI, 0.79-0.82) for uncorrected data. This approach may also be useful to standardize Aβ 1-42 CSF concentrations across different centers and/or platforms, and to optimize use of CSF biomarker data collected over a long period.

Motion correction for infant functional near-infrared spectroscopy with an application to live interaction data.

Correcting for motion is an important consideration in infant functional near-infrared spectroscopy studies. We tested the performance of conventional motion correction methods and compared probe motion and data quality metrics for data collected at different infant ages (5, 7, and 12 months) and during different methods of stimulus presentation (video versus live). While 5-month-olds had slower maximum head speed than 7- or 12-month-olds, data quality metrics and hemodynamic response recovery errors were similar across ages. Data quality was also similar between video and live stimulus presentation. Motion correction algorithms, such as wavelet filtering and targeted principal component analysis, performed well for infant data using infant-specific parameters, and parameters may be used without fine-tuning for infant age or method of stimulus presentation. We recommend using wavelet filtering with [Formula: see text]; however, a range of parameters seemed acceptable. We do not recommend using trial rejection alone, because it did not improve hemodynamic response recovery as compared to no correction at all. Data quality metrics calculated from uncorrected data were associated with hemodynamic response recovery error, indicating that full simulation studies may not be necessary to assess motion correction performance.

Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring.

The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (Ox) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor.

Safe and sensible preprocessing and baseline correction of pupil-size data

Measurement of pupil size (pupillometry) has recently gained renewed interest from psychologists, but there is little agreement on how pupil-size data is best analyzed. Here we focus on one aspect of pupillometric analyses: baseline correction, i.e., analyzing changes in pupil size relative to a baseline period. Baseline correction is useful in experiments that investigate the effect of some experimental manipulation on pupil size. In such experiments, baseline correction improves statistical power by taking into account random fluctuations in pupil size over time. However, we show that baseline correction can also distort data if unrealistically small pupil sizes are recorded during the baseline period, which can easily occur due to eye blinks, data loss, or other distortions. Divisive baseline correction (corrected pupil size = pupil size/baseline) is affected more strongly by such distortions than subtractive baseline correction (corrected pupil size = pupil size − baseline). We discuss the role of baseline correction as a part of preprocessing of pupillometric data, and make five recommendations: (1) before baseline correction, perform data preprocessing to mark missing and invalid data, but assume that some distortions will remain in the data; (2) use subtractive baseline correction; (3) visually compare your corrected and uncorrected data; (4) be wary of pupil-size effects that emerge faster than the latency of the pupillary response allows (within ±220 ms after the manipulation that induces the effect); and (5) remove trials on which baseline pupil size is unrealistically small (indicative of blinks and other distortions).

Modeling and forecasting the volatility of carbon emission market: The role of outliers, time-varying jumps and oil price risk

The objectives of this study are three-fold. First, we aim to assess whether outliers or extreme observations occur in the European Union Allowance (EUA) data. Second, we examine if time-varying jumps are present in the carbon emission market. Third, we use the crude oil volatility index (OVX) to investigate the effect of oil market uncertainty on the emission price volatility. In order to detect the possible outliers in the EUA market, we employ a standard methodology proposed by Ané et al. (2008) and identify several outliers in the emission data. After spotting and then removing those extreme points, we apply the GARCH-jump models to both original and outlier free observations. The results of the jump model show that while time-varying jumps do exist in the uncorrected data, most of the jump parameters, however, become insignificant in case of outlier-free observations. Next, the application of an extended EGARCH model, in which OVX is introduced in the GARCH specification, demonstrates that emission prices are highly sensitive to oil market implied volatility and that the impact of OVX on the EUA market appears to be asymmetric. Additionally, the use of forecast encompassing test documents that considering the outlier-free data and using the information content of OVX would improve the volatility forecasts for the carbon emission market. The results of our research carry important implications for both investors and policymakers.

Partial-volume correction increases estimated dopamine D2-like receptor binding potential and reduces adult age differences

The relatively modest spatial resolution of positron emission tomography (PET) increases the likelihood of partial volume effects such that binding potential (BPND) may be underestimated. Given structural grey matter losses across adulthood, partial volume effects may be even more problematic in older age leading to overestimation of adult age differences. Here we examined the effects of partial volume correction (PVC) in two studies from different sites using different high-affinity D2-like radioligands (18 F-Fallypride, 11C-FLB457) and different PET camera resolutions (∼5 mm, 2.5 mm). Results across both data sets revealed that PVC increased estimated BPND and reduced, though did not eliminate, age effects on BPND. As expected, the effects of PVC were smaller in higher compared to lower resolution data. Analyses using uncorrected data that controlled for grey matter volume in each region of interest approximated PVC corrected data for some but not all regions. Overall, the findings suggest that PVC increases estimated BPND in general and reduces adult age differences especially when using lower resolution cameras. The findings suggest that the past 30 years of research on dopamine receptor availability, for which very few studies use PVC, may overestimate effects of aging on dopamine receptor availability.

Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval

Abstract. Over the past decade, sea-ice freeboard has been monitored with various satellite altimetric missions with the aim of producing long-term time series of ice thickness. While recent studies have demonstrated the capacity of the CryoSat-2 mission (2010–present) to provide accurate freeboard measurements, the current estimates obtained with the Envisat mission (2002–2012) still require some large improvements. In this study, we first estimate Envisat and CryoSat-2 radar freeboard by using the exact same processing algorithms. We then analyse the freeboard difference between the two estimates over the common winter periods (November 2010–April 2011 and November 2011–March 2012). The analysis of along-track data and gridded radar freeboard in conjunction with Envisat pulse-peakiness (PP) maps suggests that the discrepancy between the two sensors is related to the surface properties of sea-ice floes and to the use of a threshold retracker. Based on the relation between the Envisat pulse peakiness and the radar freeboard difference between Envisat and CryoSat-2, we produce a monthly CryoSat-2-like version of Envisat freeboard. The improved Envisat data set freeboard displays a similar spatial distribution to CryoSat-2 (RMSD = 1.5 cm) during the two ice growth seasons and for all months of the period of study. The comparison of the altimetric data sets with in situ ice draught measurements during the common flight period shows that the improved Envisat data set (RMSE = 12–28 cm) is as accurate as CryoSat-2 (RMSE = 15–21 cm) and much more accurate than the uncorrected Envisat data set (RMSE = 178–179 cm). The comparison of the improved Envisat radar freeboard data set is then extended to the rest of the Envisat mission to demonstrate the validity of PP correction from the calibration period. The good agreement between the improved Envisat data set and the in situ ice draught data set (RMSE = 13–32 cm) demonstrates the potential of the PP correction to produce accurate freeboard estimates over the entire Envisat mission lifetime.

A double echo ultra short echo time (UTE) acquisition for respiratory motion-suppressed high resolution imaging of the lung.

Magnetic resonance imaging is a promising alternative to computed tomography for lung imaging. However, organ motion and poor signal-to-noise ratio, arising from short T2*, impair image quality. To alleviate these issues, a new retrospective gating method was implemented and tested with an ultra-short echo time sequence. A 3D double-echo ultra-short echo time sequence was used to acquire data during free breathing in ten healthy adult subjects. A self-gating method was used to reconstruct respiratory motion suppressed expiratory and inspiratory images. These images were objectively compared to uncorrected data sets using quantitative end-points (pulmonary vessel sharpness, lung-liver interface definition, signal-to-noise ratio). The method was preliminarily tested in two cystic fibrosis patients who underwent computed tomography. Vessel sharpness in expiratory ultra-short echo time data sets with second echo motion detection was significantly higher (13% relative increase) than in uncorrected images while the opposite was observed in inspiratory images. The method was successfully applied in patients and some findings (e.g., hypointense areas) were similar to those from computed tomography. Free breathing ultra-short echo time was successfully implemented, allowing flexible image reconstruction of two different respiratory states. Objective improvements in image quality were obtained with the new method and initial feasibility in a clinical setting was demonstrated. Magn Reson Med 79:2297-2305, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

A statistical comparison of cirrus particle size distributions measured using the 2-D stereo probe during the TC<sup>4</sup>, SPARTICUS, and MACPEX flight campaigns with historical cirrus datasets

Abstract. This paper addresses two straightforward questions. First, how similar are the statistics of cirrus particle size distribution (PSD) datasets collected using the Two-Dimensional Stereo (2D-S) probe to cirrus PSD datasets collected using older Particle Measuring Systems (PMS) 2-D Cloud (2DC) and 2-D Precipitation (2DP) probes? Second, how similar are the datasets when shatter-correcting post-processing is applied to the 2DC datasets? To answer these questions, a database of measured and parameterized cirrus PSDs – constructed from measurements taken during the Small Particles in Cirrus (SPARTICUS); Mid-latitude Airborne Cirrus Properties Experiment (MACPEX); and Tropical Composition, Cloud, and Climate Coupling (TC4) flight campaigns – is used.Bulk cloud quantities are computed from the 2D-S database in three ways: first, directly from the 2D-S data; second, by applying the 2D-S data to ice PSD parameterizations developed using sets of cirrus measurements collected using the older PMS probes; and third, by applying the 2D-S data to a similar parameterization developed using the 2D-S data themselves. This is done so that measurements of the same cloud volumes by parameterized versions of the 2DC and 2D-S can be compared with one another. It is thereby seen – given the same cloud field and given the same assumptions concerning ice crystal cross-sectional area, density, and radar cross section – that the parameterized 2D-S and the parameterized 2DC predict similar distributions of inferred shortwave extinction coefficient, ice water content, and 94 GHz radar reflectivity. However, the parameterization of the 2DC based on uncorrected data predicts a statistically significantly higher number of total ice crystals and a larger ratio of small ice crystals to large ice crystals than does the parameterized 2D-S. The 2DC parameterization based on shatter-corrected data also predicts statistically different numbers of ice crystals than does the parameterized 2D-S, but the comparison between the two is nevertheless more favorable. It is concluded that the older datasets continue to be useful for scientific purposes, with certain caveats, and that continuing field investigations of cirrus with more modern probes is desirable.

Evaluation of the impact of Illumina error correction tools on de novo genome assembly

BackgroundRecently, many standalone applications have been proposed to correct sequencing errors in Illumina data. The key idea is that downstream analysis tools such as de novo genome assemblers benefit from a reduced error rate in the input data. Surprisingly, a systematic validation of this assumption using state-of-the-art assembly methods is lacking, even for recently published methods.ResultsFor twelve recent Illumina error correction tools (EC tools) we evaluated both their ability to correct sequencing errors and their ability to improve de novo genome assembly in terms of contig size and accuracy.ConclusionsWe confirm that most EC tools reduce the number of errors in sequencing data without introducing many new errors. However, we found that many EC tools suffer from poor performance in certain sequence contexts such as regions with low coverage or regions that contain short repeated or low-complexity sequences. Reads overlapping such regions are often ill-corrected in an inconsistent manner, leading to breakpoints in the resulting assemblies that are not present in assemblies obtained from uncorrected data. Resolving this systematic flaw in future EC tools could greatly improve the applicability of such tools.

Impact of partial-volume correction in oncological PET studies: a systematic review and meta-analysis

PurposePositron-emission tomography can be useful in oncology for diagnosis, (re)staging, determining prognosis, and response assessment. However, partial-volume effects hamper accurate quantification of lesions <2–3× the PET system’s spatial resolution, and the clinical impact of this is not evident. This systematic review provides an up-to-date overview of studies investigating the impact of partial-volume correction (PVC) in oncological PET studies.MethodsWe searched in PubMed and Embase databases according to the PRISMA statement, including studies from inception till May 9, 2016. Two reviewers independently screened all abstracts and eligible full-text articles and performed quality assessment according to QUADAS-2 and QUIPS criteria. For a set of similar diagnostic studies, we statistically pooled the results using bivariate meta-regression.ResultsThirty-one studies were eligible for inclusion. Overall, study quality was good. For diagnosis and nodal staging, PVC yielded a strong trend of increased sensitivity at expense of specificity. Meta-analysis of six studies investigating diagnosis of pulmonary nodules (679 lesions) showed no significant change in diagnostic accuracy after PVC (p = 0.222). Prognostication was not improved for non-small cell lung cancer and esophageal cancer, whereas it did improve for head and neck cancer. Response assessment was not improved by PVC for (locally advanced) breast cancer or rectal cancer, and it worsened in metastatic colorectal cancer.ConclusionsThe accumulated evidence to date does not support routine application of PVC in standard clinical PET practice. Consensus on the preferred PVC methodology in oncological PET should be reached. Partial-volume-corrected data should be used as adjuncts to, but not yet replacement for, uncorrected data.