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Applied Optics May 2019The spectrum acquired on the optical instrument usually contains the pure spectrum and undesirable components such as baseline and random noise. However, the intensity...
The spectrum acquired on the optical instrument usually contains the pure spectrum and undesirable components such as baseline and random noise. However, the intensity of the baseline, which seriously submerges the spectrum, is the primary limitation of spectral applications. Thus, baseline correction has become one of the most significant challenges for spectral applications. In this paper, we propose a doubly reweighted penalized least squares method to estimate the baseline. This method utilizes the first-order derivative of the original spectrum and established spectrum as a constraint of similarity. Meanwhile, the doubly reweighted strategy achieves a better effort. Considering the drawbacks of the weighting rules for the adaptive iteratively reweighted penalized least squares method, we adapt a boosted weighting rule based on the softsign function, which performs well when the spectrum contains high noise. The simulated results confirm that the proposed method yields better outcomes. The proposed method can be applied to Raman and near-infrared spectra as well, and the result shows that it can estimate various kinds of baselines effectively.
PubMed: 31158209
DOI: 10.1364/AO.58.003913 -
Sensors (Basel, Switzerland) May 2019Spaceborne multistatic synthetic aperture radar (SAR) tomography (SMS-TomoSAR) systems take full advantage of the flexible configuration of multistatic SAR in the space,...
Spaceborne multistatic synthetic aperture radar (SAR) tomography (SMS-TomoSAR) systems take full advantage of the flexible configuration of multistatic SAR in the space, time, phase, and frequency dimensions, and simultaneously achieve high-precision height resolution and low-deformation measurement of three-dimensional ground scenes. SMS-TomoSAR currently poses a series of key issues to solve, such as baseline optimization, spatial transmission error estimation and compensation, and the choice of imaging algorithm, which directly affects the performance of height-dimensional imaging and surface deformation measurement. This paper explores the impact of baseline distribution on height-dimensional imaging performance for the baseline optimization issue, and proposes a feasible baseline optimization method. Firstly, the multi-base multi-pass baselines of an SMS-TomoSAR system are considered equivalent to a group of multi-pass baselines from monostatic SAR. Secondly, we establish the equivalent baselines as a symmetric-geometric model to characterize the non-uniform characteristic of baseline distribution. Through experimental simulation and model analysis, an approximately uniform baseline distribution is shown to have better SMS-TomoSAR imaging performance in the height direction. Further, a baseline design method under uniform-perturbation sampling with Gaussian distribution error is proposed. Finally, the imaging performance of different levels of perturbation is compared, and the maximum baseline perturbation allowed by the system is given.
PubMed: 31067712
DOI: 10.3390/s19092106 -
Marine Pollution Bulletin Apr 2022Establishing geochemical baselines and assessment of heavy metal pollution in lagoon sediments are critical for providing guidance to coastal zone environmental...
Establishing geochemical baselines and assessment of heavy metal pollution in lagoon sediments are critical for providing guidance to coastal zone environmental management. We analyzed heavy metals in high-resolution sediment cores from Pinqing Lagoon in South China, and defined the baselines of common pollution elements with a significant anthropogenic contribution. With these baselines, a spatiotemporal pollution assessment revealed Cu and Cd as the predominant pollution metals in both core and surface sediments, although the ecological risk level in the interior lagoon remained low during the past ~170 years. Surface sediment pollution status indicate a significant spatial difference. The findings from this typical coastal lagoon evidence a strong self-clean capacity attributable to the frequent water-mass-energy exchange between the lagoon and the sea. Furthermore, despite the significant impact by the sea, the geochemical baselines are close to the catchment soil backgrounds that can be defined using a paleolimnological approach.
Topics: China; Environmental Monitoring; Geologic Sediments; Metals, Heavy; Risk Assessment; Water Pollutants, Chemical
PubMed: 35245766
DOI: 10.1016/j.marpolbul.2022.113459 -
Drug Safety Jun 2013In parallel thorough QT (TQT) studies, it has been speculated that either baseline correction should be omitted, under the assumption that it only adds noise to the...
BACKGROUND
In parallel thorough QT (TQT) studies, it has been speculated that either baseline correction should be omitted, under the assumption that it only adds noise to the data, or a time-averaged baseline instead of a time-matched baseline correction should be considered in order to reduce the study variability.
OBJECTIVE
This study characterized the assumptions and implications of different baseline correction approaches in parallel TQT studies submitted for regulatory review.
DATA AND METHODS
57 parallel TQT studies conducted between 2002 and 2009 in 5591 healthy volunteers were evaluated. Only moxifloxacin and placebo arms, including their baselines, were considered. The options of using no baseline correction, time-averaged baseline correction, and time-matched baseline correction were examined and compared.
RESULTS
QTc values exhibited a diurnal pattern, with longer QTc intervals during sleep preserved when correcting for a time-averaged baseline. Post-dose and baseline QTc values were highly correlated (mean ρ = 0.80, range 0.56-0.98 and mean ρ = 0.79, range 0.50-0.96 in the placebo and moxifloxacin groups, respectively). The variability of raw QTc values was substantially larger than that of baseline-adjusted QTc values. The difference in the point estimate of QTc differences between moxifloxacin and placebo differed by up to ± 4 ms between the time-averaged and the time-matched baseline corrections. Statistical tests indicate that assumptions of time-averaged baseline and no baseline correction are not appropriate.
CONCLUSIONS
Baseline correction in parallel TQT studies leads to more precise QTc estimates. Because of possible inaccuracy introduced by time-averaged baseline correction, the time-matched baseline correction appears to be preferable for a parallel TQT study to both reduce the intrinsic variability due to circadian patterns and obtain more accurate point estimates.
Topics: Adolescent; Adult; Aged; Aged, 80 and over; Anti-Bacterial Agents; Aza Compounds; Cardiotoxins; Cardiovascular Agents; Circadian Rhythm; Data Interpretation, Statistical; Electrocardiography, Ambulatory; Female; Fluoroquinolones; Heart Function Tests; Humans; Investigational New Drug Application; Male; Middle Aged; Moxifloxacin; Quinolines; Randomized Controlled Trials as Topic; United States; United States Food and Drug Administration; Young Adult
PubMed: 23620166
DOI: 10.1007/s40264-013-0040-z -
Sensors (Basel, Switzerland) Jan 2023In this work, a new method for aerial robot remote sensing using stereo vision is proposed. A variable baseline and flexible configuration stereo setup is achieved by...
In this work, a new method for aerial robot remote sensing using stereo vision is proposed. A variable baseline and flexible configuration stereo setup is achieved by separating the left camera and right camera on two separate quadrotor aerial robots. Monocular cameras, one on each aerial robot, are used as a stereo pair, allowing independent adjustment of the pose of the stereo pair. In contrast to conventional stereo vision where two cameras are fixed, having a flexible configuration system allows a large degree of independence in changing the configuration in accordance with various kinds of applications. Larger baselines can be used for stereo vision of farther away targets while using a vertical stereo configuration in tasks where there would be a loss of horizontal overlap caused by a lack of suitable horizontal configuration. Additionally, a method for the practical use of variable baseline stereo vision is introduced, combining multiple point clouds from multiple stereo baselines. Issues from using an inappropriate baseline, such as estimation error induced by insufficient baseline, and occlusions from using too large a baseline can be avoided with this solution.
PubMed: 36772173
DOI: 10.3390/s23031134 -
Frontiers in Neuroscience 2022Artificial neural networks (ANNs) are the basis of recent advances in artificial intelligence (AI); they typically use real valued neuron responses. By contrast,...
Artificial neural networks (ANNs) are the basis of recent advances in artificial intelligence (AI); they typically use real valued neuron responses. By contrast, biological neurons are known to operate using spike trains. In principle, spiking neural networks (SNNs) may have a greater representational capability than ANNs, especially for time series such as speech; however their adoption has been held back by both a lack of stable training algorithms and a lack of compatible baselines. We begin with a fairly thorough review of literature around the conjunction of ANNs and SNNs. Focusing on surrogate gradient approaches, we proceed to define a simple but relevant evaluation based on recent speech command tasks. After evaluating a representative selection of architectures, we show that a combination of adaptation, recurrence and surrogate gradients can yield light spiking architectures that are not only able to compete with ANN solutions, but also retain a high degree of compatibility with them in modern deep learning frameworks. We conclude tangibly that SNNs are appropriate for future research in AI, in particular for speech processing applications, and more speculatively that they may also assist in inference about biological function.
PubMed: 36117617
DOI: 10.3389/fnins.2022.865897 -
BMC Medical Informatics and Decision... Oct 2023There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support...
BACKGROUND
There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of inconsistent methods of estimating baseline serum creatinine (sCr) may result in a poor understanding of these models' effectiveness in clinical practice. Until now, the performance of such models with different baselines has not been compared on a single dataset. Additionally, AKI prediction models are known to have a high rate of false positive (FP) events regardless of baseline methods. This warrants further exploration of FP events to provide insight into potential underlying reasons.
OBJECTIVE
The first aim of this study was to assess the variance in performance of ML models using three methods of baseline sCr on a retrospective dataset. The second aim was to conduct an error analysis to gain insight into the underlying factors contributing to FP events.
MATERIALS AND METHODS
The Intensive Care Unit (ICU) patients of the Medical Information Mart for Intensive Care (MIMIC)-IV dataset was used with the KDIGO (Kidney Disease Improving Global Outcome) definition to identify AKI episodes. Three different methods of estimating baseline sCr were defined as (1) the minimum sCr, (2) the Modification of Diet in Renal Disease (MDRD) equation and the minimum sCr and (3) the MDRD equation and the mean of preadmission sCr. For the first aim of this study, a suite of ML models was developed for each baseline and the performance of the models was assessed. An analysis of variance was performed to assess the significant difference between eXtreme Gradient Boosting (XGB) models across all baselines. To address the second aim, Explainable AI (XAI) methods were used to analyse the XGB errors with Baseline 3.
RESULTS
Regarding the first aim, we observed variances in discriminative metrics and calibration errors of ML models when different baseline methods were adopted. Using Baseline 1 resulted in a 14% reduction in the f1 score for both Baseline 2 and Baseline 3. There was no significant difference observed in the results between Baseline 2 and Baseline 3. For the second aim, the FP cohort was analysed using the XAI methods which led to relabelling data with the mean of sCr in 180 to 0 days pre-ICU as the preferred sCr baseline method. The XGB model using this relabelled data achieved an AUC of 0.85, recall of 0.63, precision of 0.54 and f1 score of 0.58. The cohort size was 31,586 admissions, of which 5,473 (17.32%) had AKI.
CONCLUSION
In the absence of a widely accepted method of baseline sCr, AKI prediction studies need to consider the impact of different baseline methods on the effectiveness of ML models and their potential implications in real-world implementations. The utilisation of XAI methods can be effective in providing insight into the occurrence of prediction errors. This can potentially augment the success rate of ML implementation in routine care.
Topics: Humans; Creatinine; Retrospective Studies; Models, Statistical; Prognosis; Acute Kidney Injury
PubMed: 37814311
DOI: 10.1186/s12911-023-02306-0 -
Analytical Methods : Advancing Methods... May 2021Baseline correction is an important step in energy-dispersive X-ray fluorescence analysis. The asymmetric least squares method (AsLS), adaptive iteratively reweighted...
Baseline correction is an important step in energy-dispersive X-ray fluorescence analysis. The asymmetric least squares method (AsLS), adaptive iteratively reweighted penalized least squares method (airPLS), and asymmetrically reweighted penalized least squares method (arPLS) are widely used to automatically select the data points for the baseline. Considering the parametric sensitivity of the aforementioned methods and the statistical characteristics of the X-ray energy spectrum, this paper proposes an asymmetrically reweighted penalized least squares method based on the Poisson distribution (PD-AsLS) to automatically correct the baseline of X-ray spectra. Monte Carlo (MC) simulation is used to obtain the background spectrum, and PD-AsLS is used to estimate the baseline of the background. The relative error and the absolute error between the simulated background and PD-AsLS estimated background are used to determine the accuracy of PD-AsLS. The correlation coefficient (COR) and the root mean square error (RMSE) between the estmated baseline and the real baseline are calculated, and results of PD-AsLS are compared with results of three other classical methods (arPLS, airPLS and AsLS) to evaluate the reliability of PD-AsLS. The results of PD-AsLS show that the COR is above 0.95 and RMSE is less than 6. The stability and the practicability of PD-AsLS are also evaluated in experiments. A sample is measured five time to get its X-ray energy spectra, and the coefficient of variation (CV) of the estimated baseline is smaller than that of measured spectra. Experiments show that PD-AsLS can estimate baselines better than arPLS without any overestimation. Those results indicate that PD-AsLS can reliably estimate the baselines of X-ray spectra and effectively suppress the statistical fluctuation.
PubMed: 33955992
DOI: 10.1039/d1ay00122a -
The Science of the Total Environment Sep 2022Improving food systems to address food insecurity and minimize environmental impacts is still a challenge in the 21st century. Ecohydrological models are a key tool for...
Improving food systems to address food insecurity and minimize environmental impacts is still a challenge in the 21st century. Ecohydrological models are a key tool for accurate system representation and impact measurement. We used a multi-phase testing approach to represent baseline hydrologic conditions across three agricultural basins that drain parts of north central and central Iowa, U.S.: the Des Moines River Basin (DMRB), the South Skunk River Basin (SSRB), and the North Skunk River Basin (NSRB). The Soil and Water Assessment Tool (SWAT) ecohydrological model was applied using a framework consisting of the Hydrologic and Water Quality System (HAWQS) online platform, 40 streamflow gauges, the alternative runoff curve number method, additional tile drainage and fertilizer application. In addition, ten SWAT baselines were created to analyze both the HAWQS parameters (baseline 1) and nine alternative baseline configurations (considering the framework). Most of the models achieved acceptable statistical replication of measured (close to the outlet) streamflows, with Nash-Sutcliffe (NS) values ranging up to 0.80 for baseline 9 in the DMRB and SSRB, and 0.78 for baseline 7 in the NSRB. However, water balance and other hydrologic indicators revealed that careful selection of management data and other inputs are essential for obtaining the most accurate representation of baseline conditions for the simulated stream systems. Using cumulative distribution curves as a criterion, baselines 7 to 10 showed the best fit for the SSRB and NSRB, but none of the baselines accurately represented 20% of low flows for the DMRB. Analysis of snowmelt and growing season periods showed that baselines 3 and 4 resulted in poor simulations across all three basins using four common statistical measures (NS, KGE, Pbias, and R), and that baseline 9 was characterized by the most satisfactory statistical results, followed by baselines 5, 7 and 1.
Topics: Hydrology; Iowa; Models, Theoretical; Soil; Water Quality
PubMed: 35640760
DOI: 10.1016/j.scitotenv.2022.156302 -
Journal of Biomechanics Jan 2005The purpose of this investigation was to examine if baseline measures are altered between conditions in biomechanical studies and to determine the need for baseline...
The purpose of this investigation was to examine if baseline measures are altered between conditions in biomechanical studies and to determine the need for baseline measurements in biomechanics. Ten runners were asked to run at varying speeds and obstacle heights. Baseline measures were acquired between all conditions. Right lower extremity kinematic and kinetic data were collected for all baseline trials and evaluated by both a group and a single subject analysis. The group analysis revealed significant differences between baselines only for the obstacle perturbation. The single subject analysis indicated that baseline measures are altered in a greater degree for kinematics than kinetics. These findings suggested that baseline measures are altered between conditions in biomechanical studies, and they should be used when a repeated measures or a single subject experimental design is being utilized.
Topics: Biomechanical Phenomena; Humans; Kinetics; Leg; Research Design; Running
PubMed: 15519354
DOI: 10.1016/j.jbiomech.2004.03.007