Average Absolute Difference Research Articles

A deep learning based method for left ventricular strain measurements: repeatability and accuracy compared to experienced echocardiographers.

Speckle tracking echocardiography (STE) provides quantification of left ventricular (LV) deformation and is useful in the assessment of LV function. STE is increasingly being used clinically, and every effort to simplify and standardize STE is important. Manual outlining of regions of interest (ROIs) is labor intensive and may influence assessment of strain values. We hypothesized that a deep learning (DL) model, trained on clinical echocardiographic exams, can be combined with a readily available echocardiographic analysis software, to automate strain calculation with comparable fidelity to trained cardiologists. Data consisted of still frame echocardiographic images with cardiologist-defined ROIs from 672 clinical echocardiographic exams from a university hospital outpatient clinic. Exams included patients with ischemic heart disease, heart failure, valvular disease, and conduction abnormalities, and some healthy subjects. An EfficientNetB1-based architecture was employed, and different techniques and properties including data set size, data quality, augmentations, and transfer learning were evaluated. DL predicted ROIs were reintroduced into commercially available echocardiographic analysis software to automatically calculate strain values. DL-automated strain calculations had an average absolute difference of 0.75 (95% CI 0.58-0.92) for global longitudinal strain (GLS), and 1.16 (95% CI 1.03-1.29) for single-projection longitudinal strain (LS), compared to operators. A Bland-Altman plot revealed no obvious bias, though there were fewer outliers in the lower average LS ranges. Techniques and data properties yielded no significant increase/decrease in performance. The study demonstrates that DL-assisted, automated strain measurements are feasible, and provide results within interobserver variation. Employing DL in echocardiographic analyses could further facilitate adoption of STE parameters in clinical practice and research, and improve reproducibility.

Home blood pressure stability score is associated with better cardiovascular prognosis: data from the nationwide prospective J-HOP study.

A home blood pressure (BP)-centered strategy is emerging as the optimal approach to achieve adequate BP control in individuals with hypertension, but a simple cardiovascular risk score based on home BP level and variability is lacking. This study used prospective data from the Japan Morning Surge-Home Blood Pressure (J-HOP) extended study to develop a simple home BP stability score for the prediction of cardiovascular risk. The J-HOP extended study included 4070 participants (mean age 64.9 years) who measured home BP three times in the morning and evening for 14 days at baseline. During the mean 6.3-year follow-up, there were 260 cardiovascular events. A home BP stability score was calculated based on the average of morning and evening systolic BP (SBP; MEave), and three home BP variability metrics: average real variability (average absolute difference between successive measurements); average peak (average of the highest three SBP values for each individual), and time in therapeutic range (proportion of time spent with MEave home SBP 100-135 mmHg). There was a curvilinear association between the home BP stability score and the risk of cardiovascular events. Compared with individuals in the optimal home SBP stability score group (9-10 points), those in the very high-risk group (0 points) had significantly higher cardiovascular event risk during follow-up (adjusted hazard ratio 3.97, 95% confidence interval 2.22-7.09; p < 0.001), independent of age, sex, medication, cardiovascular risk factors, and office BP. These data show the potential for a simple home BP-based score to predict cardiovascular event risk in people with hypertension.

Enhancing stereotactic ablative boost radiotherapy dose prediction for bulky lung cancer: A multi-scale dilated network approach with scale-balanced structure loss.

Partial stereotactic ablative boost radiotherapy (P-SABR) effectively treats bulky lung cancer; however, the planning process for P-SABR requires repeated dose calculations. To improve planning efficiency, we proposed a novel deep learning method that utilizes limited data to accurately predict the three-dimensional (3D) dose distribution of the P-SABR plan for bulky lung cancer. We utilized data on 74 patients diagnosed with bulky lung cancer who received P-SABR treatment. The patient dataset was randomly divided into a training set (51 plans) with augmentation, validation set (7 plans), and testing set (16 plans). We devised a 3D multi-scale dilated network (MD-Net) and integrated a scale-balanced structure loss into the loss function. A comparative analysis with a classical network and other advanced networks with multi-scale analysis capabilities and other loss functions was conducted based on the dose distributions in terms of the axial view, average dose scores (ADSs), and average absolute differences of dosimetric indices (AADDIs). Finally, we analyzed the predicted dosimetric indices against the ground-truth values and compared the predicted dose-volume histogram (DVH) with the ground-truth DVH. Our proposed dose prediction method for P-SABR plans for bulky lung cancer demonstrated strong performance, exhibiting a significant improvement in predicting multiple indicators of regions of interest (ROIs), particularly the gross target volume (GTV). Our network demonstrated increased accuracy in most dosimetric indices and dose scores in different ROIs. The proposed loss function significantly enhanced the predictive performance of the dosimetric indices. The predicted dosimetric indices and DVHs were equivalent to the ground-truth values. Our study presents an effective model based on limited datasets, and it exhibits high accuracy in the dose prediction of P-SABR plans for bulky lung cancer. This method has potential as an automated tool for P-SABR planning and can help optimize treatments and improve planning efficiency.

7938 Validation of Inflammatory Cytokine Multiplex Array With Variations in Target Panel

Abstract Disclosure: W.M. Sanders: None. C.A. Karvonen-Gutierrez: None. D.S. McConnell: None. Background: Multiplex arrays are an invaluable tool for conducting large-scale biomarker research as they provide a high-throughput, cost-effective method for quantifying a panel of endocrine markers. However, the shared reaction environment between antibodies of differing reactivities creates the potential for inducing a technical difference in the assay methods due to any variation in panel selection. Methods: We evaluated the R&amp;D Systems Luminex HS Cytokine Panel A (Catalog # FCSTM09) for systematic differences when measuring a “panel” of IL-1β, TNF-α, and IL-10 vs. measuring “IL-10 only.” We selected 72 serum samples and assayed them in singleton 4 times: 2 separate “panel” batches, and 2 separate “IL-10 only” batches. Differences in log-transformed IL-10 results for sample replicates within and between the “panel” and “IL-10 only” batches were assessed for significance with paired t-tests (α=.01). We also assessed the differences graphically with Bland-Altman plots of differences and absolute percent differences.All batches included control materials from R&amp;D Systems and internal lab serum pools (male and female). To retroactively assess the test batches, we graphically compared their quality control results to those of the subsequent, larger assay project we were piloting. Results: The “IL-10 only” assay yielded an average result of .879 pg/mL (SD .57) on batch 1 and .712 pg/mL (SD .58) on batch 2, with an average paired sample difference of .167 pg/mL, and an average absolute percent difference of 28.8%. The “panel” assay produced an average IL-10 result of .645 pg/mL (SD .50) on batch 1 and .720 pg/mL (SD .52) on batch 2, with an average paired sample difference of .075 pg/mL, and an average absolute percent difference of 15.5%. Comparing pooled IL-10 results from the “IL-10 only” batches with the “panel” batches, there was an average paired difference of .113 pg/mL and absolute percent difference of 16.2%. Paired t-testing of log-transformed results for within “panel,” within “IL-10 only,” and between pooled results from the two methods demonstrated that each had significant differences (p&amp;lt;.0001). The Bland-Altman plots further revealed that these differences were ubiquitously large for samples with low concentrations of IL-10.Test batch quality control results were consistent with those in the primary assay project. The serum pool QCs exhibited significant inter-assay variation – the male pool average result was .41 pg/mL (SD .10) vs. .359 in the test batches, and the female pool average was .57 pg/mL (SD .10) vs. .548 in the test batches. Conclusion: The multiplex assay had considerable inter-assay variation at low concentrations of IL-10, and low results were prevalent. Due to this, we determined that any methodological differences between the “panel” and “IL-10 only” methods were undetectable compared to ambient variation, and irrelevant given the sample characteristics. Presentation: 6/3/2024

Diffusion in Polymethylene Chain Solutions with a Polar Component.

A hydrodynamic bead model based on Kirkwood-Riseman theory has been used to calculate the translational diffusion constant, D, for solutes with polymethylene chains in solutions with a polar component. A comparison with the experimental values for nonpolar n-alkanes in polar 2-propanol, tetrahydrofuran, chlorobenzene, chloroform, 1-octanol, quinoline, and chloroform (78 D values) and polar primary alcohols in nonpolar benzene and n-octane (24 D values) gives an average absolute percentage difference of ∼3% between the 102 experimental and calculated D values. Consideration of the solvent's temperature-dependent changes in the degree of aggregation due to hydrogen bonding was necessary for the n-alkanes in 1-octanol. Good agreement was not found for primary alcohols in 1-octanol due to solute-solvent hydrogen bonding. A correlation that depends on the solutes' molar volumes instead of their chain lengths gives worse agreement than the bead model for the n-alkanes in polar solvents and primary alcohols and n-alkanes in nonpolar solvents.

Does one biopsy cut it? Revisiting human muscle fiber type composition variability using repeated biopsies in the vastus lateralis and gastrocnemius medialis.

Human skeletal muscle fiber type composition varies greatly along the muscle, so one biopsy may not accurately represent the whole muscle. Recommendations on the number of biopsies and fiber counts using immunohistochemistry and whether these findings can be extrapolated to other muscles are lacking. We assessed fiber type composition in the vastus lateralis and gastrocnemius medialis muscles of 40 individuals. Per muscle, we took four biopsy samples from one incision, collecting two samples each from a proximally and distally directed needle. Based on another dataset involving 10 vastus lateralis biopsies per participant (N=7), we calculated 95% limits of agreement for subsets of biopsies and fiber counts compared to the 10-biopsy average. Average absolute differences in type I fiber proportions between proximal and distal, and between within-needle samples were 6.9 and 4.5 percentage points in the vastus lateralis, and 5.5 and 4.4 percentage points in the gastrocnemius medialis, respectively. The 95% limits of agreement narrowed to ±10 percentage points when 200 fibers from at least three biopsies were analyzed, with minimal improvements with greater fiber counts. Type I fiber proportions in the vastus lateralis and gastrocnemius medialis showed a moderate positive association (r²=0.22; p=0.006; at least 200 fibers in each of three to four samples per muscle). In conclusion, three biopsies with a minimum of 200 counted fibers are required to estimate vastus lateralis fiber type composition within ±10 percentage points. Even when using these standards, researchers should be cautious when extrapolating muscle fiber type proportions from one muscle to another.

Standing versus supine pelvic incidence in adult spinal deformity patients.

Pelvic incidence (PI) is commonly used to determine sagittal alignment. Historically, PI was believed to be a fixed anatomic parameter. However, recent studies have suggested that there is positionally-dependent motion that occurs through the sacroiliac joint (SIJ) resulting in changes in PI. We reviewed 100 consecutive adult spinal deformity (ASD) patients seen at our academic tertiary referral center. Two reviewers measured pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), and lumbar lordosis (LL) on standing radiographs and scout computed tomography scans (CT). Unilateral, bilateral, or absent SIJ vacuum sign (VS) was determined using CTs. Eighty-six patients (42M:44F) were included with an average age of 64.1 years and BMI of 28.8kg/m2. Standing PI was low (< 50°) in 35 patients (40.7%), average (50°-60°) in 22 (25.6%), and high (> 60°) in 29 (33.7%). Average and high PI patients had significant PI changes of 3.0° (p = 0.037) and 4.6° (p = 0.005), respectively. Bilateral SIJ VS was seen in 68 patients, unilateral VS in 9, and VS was absent in 9. The average change in PI between standing and supine was 2.1° in bilateral SIJ VS patients (p = 0.045), 2.2° in unilateral SIJ VS (p = 0.23), and - 0.1° in patients without SIJ VS (p = 0.93). The average absolute difference in PI between supine and standing was 5.5° ±5.5° (p < 0.001). There is a change in PI from supine to standing. In patients with high PI and bilateral VS on CT, the change from supine to standing is significant, perhaps representing instability of the SIJ.

Predicting pKa Values of Para-Substituted Aniline Radical Cations vs. Stable Anilinium Ions in Aqueous Media

The focus of pKa calculations has primarily been on stable molecules, with limited studies comparing radical cations and stable cations. In this study, we comprehensively investigate models with implicit solvent and explicit water molecules, direct and indirect calculation approaches, as well as methods for calculating free energy, solvation energy, and quasi-harmonic oscillator approximation for para-substituted aniline radical cations (R-PhNH2•+) and anilinium cations (R-PhNH3+) in the aqueous phase. Properly including and positioning explicit H2O molecules in the models is important for reliable pKa predictions. For R-PhNH2•+, precise pKa values were obtained using models with one or two explicit H2O molecules, resulting in a root mean square error (RMSE) of 0.563 and 0.384, respectively, for both the CBS-QB3 and M062X(D3)/ma-def2QZVP methods. Further improvement was achieved by adding H2O near oxygen-containing substituents, leading to the lowest RMSE of 0.310. Predicting pKa values for R-PhNH3+ was more challenging. CBS-QB3 provided an RMSE of 0.349 and the M062X(D3)/ma-def2QZVP method failed to calculate pKa accurately (RMSE &gt; 1). However, by adopting the double-hybrid functional method and adding H2O near the R substituent group, the calculations were significantly improved with an average absolute difference (ΔpKa) of 0.357 between the calculated and experimental pKa values. Our study offers efficient and reliable methods for pKa calculations of R-PhNH2•+ (especially) and R-PhNH3+ based on currently mature quantum chemistry software.

Exploring the impact of field shape on predicted dose distribution in breast cancer patients using deep learning in radiation therapy

BackgroundGeometrical information such as field shape is essential for dose calculation in radiation therapy. However, new methods of dose prediction based on deep learning only use CT images and contouring of patients. The aim of this study is to develop a deep learning method for three-dimensional dose prediction for breast cancer radiotherapy using field shape as well as CT and contouring images of patients. MethodsA total of 150 breast cancer patients' data treated with 3D conformal radiation therapy (CRT) technique were used to train and test 3D-U-Res-F-Net model. The model inputs were CT images, patients' contouring and field shape. The network output was the corresponding the patients’ dose distribution. Then, the dosimetric parameters extracted from the dose volume histograms related to the planned and predicted dose distributions were compared and were statistically analysed with the paired-samples t-test. These parameters include Dmean and Dmax for planning target volume and organs at risk, D95%, D50%, V47.5Gy for PTV, V30Gy and V25Gy for heart and V20Gy for left lung. The gamma index with 3%/3 mm criteria was calculated for PTV and OARs. ResultsThe average absolute difference of the Dmean relative to the prescribed dose for the PTV, heart, left lung, right lung and spinal cord were 1.37 ± 0.4%, 2.02 ± 2%, 2.12 ± 1%, 0.37 ± 0.3% and 0.41 ± 0.3%, respectively. The average absolute difference of the Dmax relative to the prescribed dose for the PTV and OARs varied from 0.23 ± 0.2% to 2.04 ± 2%. The 3D gamma pass rate with 3mm/3% criteria for planning target volume, heart, left lung, right lung, spinal cord and body were 89 ± 3%, 91 ± 5%, 93 ± 5%, 99 ± 3%, 99 ± 1% and 96 ± 2% respectively. ConclusionsThe results of the proposed model demonstrate that there is no significant difference between the predicted and planned dose distributions. The deep learning model can directly predict the 3D dose distribution faster than treatment planning systems. Further studies with more patients and on other cancer sites are essential to fully validate the proposed method.

It is safe to use the ulnar length difference to correct the radial length difference in the 3D-planning process of a radius osteotomy in patients with a distal radius malunion

BackgroundA corrective radius osteotomy is often performed in patients with a symptomatic distal radius malunion. In 3D-planned osteotomies, the unaffected radius is mirrored over the malunited radius after adjusting for left-right length differences using both ulnae. This approach assumes that ulnar length differences in a malunion population are similar to those in a healthy population. This study was conducted to analyze the difference in ulnar length in a distal radius malunion population and to assess the potential influence of age, sex, or malunion side on this difference.MethodsWe evaluated 65 adult patients with distal radius malunion using bilateral forearm CT scans. 3D models of both ulnae were constructed, and length differences were determined along a standardized length axis. The results were compared to two populations without a radius malunion.ResultsThe average absolute ulnar length difference was 2.57 mm (SD 1.81), which was comparable to the two healthy populations. This difference was not significantly affected by age, sex, or malunion side.ConclusionThis study demonstrated that using the ulnar length difference to correct for radial length difference in the current 3D planning process, before using the contralateral radius as a template for a corrective osteotomy in patients with radius malunion, is safe.

Validation of advanced hybrid SPECT/CT system using dynamic anthropomorphic cardiac phantom

ObjectiveMyocardial blood flow (MBF) assessment can provide incremental diagnostic and prognostic information and thus the validation of dynamic SPECT is of high importance. We recently developed a novel cardiac phantom for dynamic SPECT validation and compared its performance against the GE Discovery NM 530c. We now report its use for validation of a new hybrid SPECT/CT System featuring advanced cadmium zinc telluride (CZT) technology in a ring array detector design (StarGuide™, GE HealthCare).MethodsOur recently developed cardiac phantom with injected technetium-99m radiotracer was used to create physiological time activity curves (TACs) for the left ventricular (LV) cavity and the myocardium. The TACs allow the calculation of uptake rate (K1) and MBF. The StarGuide system was used to acquire and process the TACs, and these were compared to the TACs produced by the phantom and its mathematical model. Fifteen (15) experiments with different doses representing various MBF values were conducted, and a standard statistic tool was applied for significance.ResultsThe TACs produced by the StarGuide system had a significant correlation (p < 0.001) with the reference TACs generated by the phantom both for the LV (r = 0.94) and for the myocardium (r = 0.89). The calculated MBF difference between the system and the phantom was 0.14 ± 0.16 ml/min/g and the average relative absolute difference was 13.2 ± 8.1%. A coefficient of variance of ≤ 11% was observed for all MBF subranges. The regional uptake rate values were similar to the global one with a maximum difference of 5%.ConclusionsOur newly developed dynamic cardiac phantom was used for validation of the dynamic hybrid SPECT/CT CZT-based system (StarGuide™, GE). The accuracy and precision of the system for assessing MBF values were high. The new StarGuide system can reliably perform dynamic SPECT acquisitions over a wide range of myocardial perfusion flow rates.

Rapid Uptitration of Guideline-Directed Medical Therapies in Acute Heart Failure With and Without Atrial Fibrillation

BackgroundRapid uptitration of guideline-directed medical therapy (GDMT) before and after discharge in hospitalized heart failure (HF) patients is feasible, is safe, and improves outcomes; whether this is also true in patients with coexistent atrial fibrillation/flutter (AF/AFL) is not known. ObjectivesThis study sought to investigate whether rapid GDMT uptitration before and after discharge for HF is feasible, safe and beneficial in patients with and without AF/AFL. MethodsIn this secondary analysis of the STRONG-HF (Safety, Tolerability, and Efficacy of Rapid Optimization, Helped by NT-proBNP Testing, of Heart Failure Therapies) trial, GDMT uptitration and patient outcomes were analyzed by AF/AFL status and type (permanent, persistent, paroxysmal). ResultsAmong 1,078 patients enrolled in STRONG-HF, 496 (46%) had a history of AF, including 238 assigned to high-intensity care (HIC) and 258 to usual care (UC), and 581 did not have a history of AF/AFL, including 304 assigned to HIC and 277 to UC. By day 90, the average percent optimal dose of neurohormonal inhibitors achieved in the HIC arm was similar in patients with and without AF/AFL, reaching approximately 80% of the optimal dose (average absolute difference between AF/AFL and non-AF/AFL groups: −0.81%; 95% CI: −3.51 to 1.89). All-cause death or HF readmission by day 180 occurred less frequently in the HIC than the UC arm, both in patients with and without AF (adjusted HR: 0.75 [95% CI: 0.48-1.19] in AF vs adjusted HR: 0.50 [95% CI: 0.31-0.79] in non-AF/AFL patients; P for interaction = 0.2107). Adverse event rates were similar in patients with and without AF/AFL. AF/AFL type did not affect either uptitration or patient outcomes. ConclusionsNearly half of acute HF patients have AF/AFL history. Rapid GDMT uptitration before and early after discharge is feasible, is safe, and may improve outcomes regardless of AF presence or type. (Safety, Tolerability, and Efficacy of Rapid Optimization, Helped by NT-proBNP Testing, of Heart Failure Therapies [STRONG-HF]; NCT03412201)

Hirshfeld atom refinement and dynamical refinement of hexagonal ice structure from electron diffraction data.

Reaching beyond the commonly used spherical atomic electron density model allows one to greatly improve the accuracy of hydrogen atom structural parameters derived from X-ray data. However, the effects of atomic asphericity are less explored for electron diffraction data. In this work, Hirshfeld atom refinement (HAR), a method that uses an accurate description of electron density by quantum mechanical calculation for a system of interest, was applied for the first time to the kinematical refinement of electron diffraction data. This approach was applied here to derive the structure of ordinary hexagonal ice (Ih). The effect of introducing HAR is much less noticeable than in the case of X-ray refinement and it is largely overshadowed by dynamical scattering effects. It led to only a slight change in the O-H bond lengths (shortening by 0.01 Å) compared with the independent atom model (IAM). The average absolute differences in O-H bond lengths between the kinematical refinements and the reference neutron structure were much larger: 0.044 for IAM and 0.046 Å for HAR. The refinement results changed considerably when dynamical scattering effects were modelled - with extinction correction or with dynamical refinement. The latter led to an improvement of the O-H bond length accuracy to 0.021 Å on average (with IAM refinement). Though there is a potential for deriving more accurate structures using HAR for electron diffraction, modelling of dynamical scattering effects seems to be a necessary step to achieve this. However, at present there is no software to support both HAR and dynamical refinement.

Next generation gravel road profiling – The potential of advanced UAV drone in comparison with road surface tester and rotary laser levels

Over the last decades, significant progress has been made and new approaches have been proposed for efficient collection of road condition data. Gravel roads are crucial for connecting urban and rural areas in Sweden, constituting a significant portion of the road network. Therefore, this study addresses the use of a developed Unmanned Aerial Vehicle (UAV)-based digital imaging system focusing on efficient collection of surface condition data over gravel roads.The study focuses on in-situ profile measurements of a gravel road located in Trosa, Sweden, using three different profiling methods: UAV drone with RTK technology, Road Surface Tester (RST), and Rotary Laser Level (RLL) to explore the agreement between these methods.The UAV drone, equipped with Real-Time Kinematic (RTK) technology, captures high-resolution images to produce detailed 3D surface models, overcoming the challenges posed by adverse weather conditions. Notable outcomes reveal RTK technology's stability, maintaining a steady 3D position accuracy below 2 cm. To enhance synchronization and comparison between different profiling methods, efforts should be made to standardize coordinate systems and measurement analysis software.Minimum average absolute differences of 1.1 cm, 1 cm, and 0.7 cm were recorded for all profiles (from 1 m left to 1 m right of the road centerline) in the comparisons between UAV drone – RST, UAV drone – RLL, and RST – RLL methods, respectively. This underlines the significant advancement in UAV drone technology, enabling remarkably accurate measurements of vertical offsets for profiling the tested gravel road despite the high altitude at which the UAV drone operates.

Association Between Intrauterine System Hormone Dosage and Depression Risk.

The authors compared the associated risk of incident depression between first-time users of low-, medium-, and high-dose levonorgestrel-releasing intrauterine systems (LNG-IUSs). This national cohort study was based on Danish register data on first-time users of LNG-IUSs, 15-44 years of age, between 2000 and 2022. Cox regression and a G-formula estimator were used to report 1-year average absolute risks, risk differences, and risk ratios of incident depression, defined as initiation of an antidepressant or receipt of a depression diagnosis, standardized for calendar year, age, education level, parental history of mental disorders, endometriosis, menorrhagia, polycystic ovary syndrome, dysmenorrhea, leiomyoma, and postpartum initiation. In total, 149,200 women started using an LNG-IUS, among whom 22,029 started a low-dose one (mean age, 22.9 years [SD=4.5]), 47,712 a medium-dose one (mean age, 25.2 years [SD=6.2]), and 79,459 a high-dose one (mean age, 30.2 years [SD=5.6]). The associated subsequent 1-year adjusted absolute risks of incident depression were 1.21% (95% CI=1.06-1.36), 1.46% (95% CI=1.33-1.59), and 1.84% (95% CI=1.72-1.96), respectively. For the users of high-dose LNG-IUSs, the risk ratios were 1.52 (95% CI=1.30-1.74) and 1.26 (95% CI=1.10-1.41) compared with users of the low- and medium-dose LNG-IUSs, respectively. For users of medium-dose LNG-IUSs, the risk ratio was 1.21 (95% CI=1.03-1.39) compared with users of low-dose LNG-IUSs. First-time use of an LNG-IUS was positively associated with incident depression in an LNG-dose-dependent manner across low-, medium-, and high-dose LNG-IUSs. Although the observational design of the study does not permit causal inference, the dose-response relationship contributes to the body of evidence suggesting a relationship between levonorgestrel exposure and risk of depression.

Sub-surface geospatial intelligence in carbon capture, utilization and storage: A machine learning approach for offshore storage site selection

This study introduces an innovative data-driven and machine-learning framework designed to accurately predict site scores in the site screening study for specific offshore CO2 storage sites. The framework seamlessly integrates diverse sub-surface geospatial data sources with human aided expert-weighted criteria, thereby providing a high-resolution screening tool. Tailored to accommodate varying data accessibility and the significance of criteria, this approach considers both technical and non-technical factors. Its purpose is to facilitate the identification of priority locations for projects associated with Carbon Capture, Utilization, and Storage (CCUS). Through aggregating and analyzing geospatial datasets, the study employs machine learning algorithms and an expert-weighted model to identify suitable geologic CCUS regions. This process adheres to stringent safety, risk control, and environmental guidelines, addressing situations where human analysis may fail to recognize patterns and provide detailed insights in suitable site screening techniques. The primary emphasis of this research is to bridge the gap between scientific inquiry and practical application, facilitating informed decision-making in the implementation of CCUS projects. Rigorous assessments encompassing geological, oceanographic, and eco-sensitivity metrics contribute valuable insights for policymakers and industry leaders. To ensure the accuracy, efficiency, and scalability of the established offshore CO2 storage facilities, the proposed machine learning approach undergoes benchmarking. This comprehensive evaluation includes the utilization of machine learning algorithms such as Extreme Gradient Boosting (XGBoost), Random Forest (RF), Multilayer Extreme Learning Machine (MLELM), and Deep Neural Network (DNN) for predicting more suitable site scores. Among these algorithms, the DNN algorithm emerges as the most effective in site score prediction. The strengths of the DNN algorithm encompass nonlinear modeling, feature learning, scale invariance, handling high-dimensional data, end-to-end learning, transfer learning, representation learning, and parallel processing. The evaluation results of the DNN algorithm demonstrate high accuracy in the testing subset, with values of AAPD (Average Absolute Percentage Difference) = 1.486 %, WAAPD (Weighted Average Absolute Percentage Difference) = 0.0149 %, VAF (Variance Accounted For) = 0.9937, RMSE (Root Mean Square Error) = 0.9279, RSR (Root Sum of Squares Residuals) = 0.0068, and R2 (Coefficient of Determination) = 0.9937.

Scaling and interpreting treatment effects in clinical trials using restricted mean survival time.

Restricted mean survival time is the expected duration of survival up to a chosen time of restriction . For comparison studies, the difference in restricted mean survival times between two groups provides a summary measure of the treatment effect that is free of assumptions regarding the relative shape of the two survival curves, such as proportional hazards. However, it can be difficult to judge the magnitude of the effect from a comparison of restricted means due to the truncation of observation at time . In this article, we describe additional ways of expressing the treatment effect based on restricted means that can be helpful in this regard. These include the ratio of restricted means, the ratio of life-years (or time) lost, and the average integrated difference between the survival curves, equal to the difference in restricted means divided by These alternative metrics are straightforward to calculate and provide a means for scaling the effect size as an aid to interpretation. Examples from two randomized, multicenter clinical trials in prostate cancer, NRG/RTOG 0521 and NRG/RTOG 0534, with primary endpoints of overall survival and biochemical/radiological progression-free survival, respectively, are presented to illustrate the ideas. The four effect measures (restricted mean survival time difference, restricted mean survival time ratio, time lost ratio, and average survival rate difference) were 0.45 years, 1.05, 0.81, and 0.038 for RTOG 0521 and 1.36 years, 1.17, 0.56, and 0.12 for RTOG 0534 with = 12 and 11 years, respectively. Thus, for example, the 0.45-year difference in the first trial translates into a 19% reduction in time lost and a 3.8% average absolute difference between the survival curves over the 12-year horizon, a modest effect size, whereas the 1.36-year difference in the second trial corresponds to a 44% reduction in time lost and a 12% absolute survival difference, a rather large effect. In addition to the difference in restricted mean survival times, these alternative measures can be helpful in determining whether the magnitude of the treatment effect is clinically meaningful.

Objective Evaluation of Motion Cueing Algorithms for Vehicle Driving Simulator Based on Criteria Importance through Intercriteria Correlation (CRITIC) Weight Method Combined with Gray Correlation Analysis

Perception-based fidelity evaluation metrics are crucial in driving simulators, as they play a key role in the automatic tuning, assessment, and comparison of motion cueing algorithms. Nevertheless, there is presently no unified and effective evaluation framework for these algorithms. To tackle this challenge, our study initially establishes a model rooted in visual–vestibular interaction and head tilt angle perception systems. We then employ metrics like the Normalized Average Absolute Difference (NAAD), Normalized Pearson Correlation (NPC), and Estimated Delay (ED) to devise an evaluation index system. Furthermore, we use a combined approach incorporating CRITIC and gray relational analysis to ascertain the weights of these indicators. This allows us to consolidate them into a comprehensive evaluation metric that reflects the overall fidelity of motion cueing algorithms. Subjective evaluation experiments validate the reasonableness and efficacy of our proposed Perception Fidelity Evaluation (PFE) method.

Accuracy of portable navigation during THA in patients with severe developmental dysplasia of hip.

Correct cup placement in total hip arthroplasty (THA) for patients with developmental dysplasia of the hip (DDH) is considerably difficult. This study aimed to analyze the orientation accuracy of cup insertion during THA using a portable navigation system in patients with DDH. In this retrospective cohort study, we analyzed data from 64 patients who underwent THA using infrared stereo camera-matching portable navigation. Patients underwent THA via the anterolateral approach in the lateral decubitus position. Navigation records for intraoperative cup angles, postoperative cup angles measured on computed tomography (CT) images, and cup angle measurement differences were measured and compared between patients with non-DDH/mild DDH and severe DDH. Furthermore, the predictive factors for outliers of accurate acetabular cup placement were analyzed. The average measurement absolute abduction differences (postoperative CT-navigation record) were 3.9 ± 3.5° (severe DDH) and 3.3 ± 2.6° (non-DDH/ mild DDH), and the anteversion differences were 4.7 ± 3.4° (severe DDH) and 2.3 ± 2.1° (non-DDH/ mild DDH). The anteversion difference was different between the two groups. Multivariate analysis showed that the navigation difference (absolute difference in anteversion between postoperative CT and navigation records of > 5°) was significantly associated with severe DDH (odds ratio [OR]: 3.3; p = 0.049, 95% confidence interval [CI]: 1.0-11.1) and posterior pelvic tilt (OR: 1.1; p = 0.042, 95% CI: 1.0-1.27). In patients with severe DDH, it is important to pay close attention during THA using portable navigation. However, the average difference was < 5º even in patients with severe DDH, and the accuracy may be acceptable in a clinical setting when the cost is considered.

Planning Application for Mobility Assessment of Intersection Forms in Intersection Control Evaluation

The use of alternative intersections and interchanges (AIIs) has proliferated significantly over the past two decades. Their introduction is motivated by the need to improve mobility and safety at conventional signalized and unsignalized intersections. This paper presents a mobility assessment component of the intersection control evaluation (ICE). The focus of this component was to develop a planning application and computational tools for the Stage II mobility analysis that can fill the current gap in coverage of the diverse (and expanding) suite of AIIs. The design of the tool prioritized the simultaneous analysis of multiple AIIs within the same platform using a common input dataset. This feature of the tool guarantees that alternative forms can be compared side-by-side under the same set of inputs and parameter assumptions using overall system delay as the key performance measure. In addition, the research developed a framework and movement definition scheme that enables the extension of the current platform to accommodate new and yet to be conceived innovative intersection forms. A comparison against two widely used commercial analytical platforms yielded virtually identical system delays and level of service ratings across 17 case studies covering eight different AII forms and under varying intersection congestion levels. The maximum system delay difference between the two methods was about 5 s, with an average absolute difference of less than 2.5 s. Future work will focus on expanding the tool to unsignalized versions of AIIs along with new and innovative forms that appear on the horizon.