Model Analysis Research Articles

Lean Mass Longitudinally Confounds Sedentary Time and Physical Activity With Blood Pressure Progression in 2513 Children.

Randomized controlled trials have reported no effect of moderate-to-vigorous physical activity (MVPA) on reducing blood pressure (BP) in youth, probably due to short trial durations. This study examined the longitudinal effect of sedentary time (ST), light PA (LPA) and MVPA on BP in 11-year-old children followed up for 13 years to determine the confounding and mediating role of body composition. Data included 2513 children from the Avon Longitudinal Study of Parents and Children (ALSPAC), UK birth cohort who had data on at least one time-point measure of accelerometer-based movement behaviour across the follow-up and complete BP measures at ages 11, 15 and 24 years. Body composition was assessed with dual-energy x-ray absorptiometry at all time points. Multivariate adjusted generalized linear mixed-effect model and structural equation causal mediation model analyses were conducted. Among 2513 participants (61% female, mean [SD] age 11.72 [0.21] years), ST steadily increased from ~6 h/day in childhood (age 11 years) to ~9 h/day in young adulthood (age 24 years), whereas LPA and MVPA decreased, but BP had an inverted U-shaped increase. In the longitudinal analysis, after full adjustment, a 1-min cumulative ST from ages 11 to 24 years was positively associated with increased systolic BP (0.009 mmHg [95% CI 0.007-0.011]; p < 0.001) and diastolic BP. A 1-min cumulative LPA was inversely associated with systolic BP (-0.007 mmHg [-0.009 to -0.004]; p < 0.001), but not diastolic BP. In isotemporal substitution analyses, longitudinal replacement of 10 min of ST with equal time in LPA during childhood, adolescence and young adulthood cumulatively decreased systolic BP by -2.63 mmHg [95% CI -3.17 to -2.08] (p < 0.0001) and diastolic BP by -1.93 mmHg [95% CI -2.36 to -1.50] (p < 0.0001). Replacing 10 min of ST with 10 min of MVPA had no statistically significant effect due to an absolute confounding effect of lean mass. The association of ST with systolic BP was fully mediated by increased lean mass (93% mediation). Increased total fat mass partially mediated (19%-27%) the inverse associations of cumulative MVPA with cumulative systolic and diastolic BP. Theoretically replacing 10 min/day spent sedentary with 10 min/day of LPA during growth from childhood through young adulthood may lower systolic BP by -3 mmHg and diastolic BP by -2 mmHg. Lean mass seems more significant than fat mass in the relations of ST and PA with BP and should be accounted for in future intervention studies in the paediatric and young adult population.

Acoustic analysis of a three-dimensional cylindrical shell model under electromagnetic vibration

This paper presents the acoustic analysis of a three-dimensional cylindrical shell model under electromagnetic vibration, a critical factor affecting the performance of electric motors in various applications such as automotive, aerospace, and industrial systems. The study provides a multidisciplinary approach that integrates electromagnetics, structural vibration, and acoustics, solved using the fast multipole boundary element method (FMBEM). The results summarize the validation of the analytical models and numerical simulations, offering insights into effective vibration reduction methods. The conclusions indicate that the 3-D numerical analysis using FMBEM aligns well with the analytical solution for the sound pressure in the exterior acoustic domain of the cylindrical shell model. The paper contributes valuable insights for the design of low-noise motors and the control of electromagnetic vibration and noise in electric motors.

Adrenal indeterminate nodules: CT-based radiomics analysis of different machine learning models for predicting adrenal metastases in lung cancer patients

ObjectiveThere is a paucity of research using different machine learning algorithms for distinguishing between adrenal metastases and benign tumors in lung cancer patients with adrenal indeterminate nodules based on plain and biphasic-enhanced CT radiomics.Materials and MethodsThis study retrospectively enrolled 292 lung cancer patients with adrenal indeterminate nodules (training dataset, 205 (benign, 96; metastases, 109); testing dataset, 87 (benign, 42; metastases, 45)). Radiomics features were extracted from the plain, arterial, and portal CT images, respectively. The independent risk radiomics features selected by least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression (LR) were used to construct the single-phase and combined-phase radiomics models, respectively, by support vector machine (SVM), decision tree (DT), random forest (RF), and LR. The independent clinical-pathological and radiological risk factors for predicting adrenal metastases selected by using univariate and multivariate LR were used to develop the traditional model. The optimal model was selected by ROC curve, and the models’ clinical values were estimated by decision curve analysis (DCA).ResultsIn the testing dataset, all SVM radiomics models showed the best robustness and efficiency, and then RF, LR, and DT models. The combined radiomics model had the best ability in predicting adrenal metastases (AUC=0.938), and then the plain (AUC=0.935), arterial (AUC=0.870), and portal radiomics model (AUC=0.851). Besides, compared to clinical-pathological-radiological model (AUC=0.870), the discriminatory capability of the plain and combined radiomics model were further improved. All radiomics models had good calibration curves and DCA showed the plain and combined radiomics models had more optimal clinical efficacy compared to other models, with the combined radiomics model having the largest net benefit.ConclusionsThe combined SVM radiomics model can non-invasively and efficiently predict adrenal metastatic nodules in lung cancer patients. In addition, the plain radiomics model with high predictive performance provides a convenient and accurate new method for patients with contraindications in enhanced CT.

Humanistic approach in protecting victims of human trafficking crimes

Cases of human trafficking are becoming more prevalent and represent grave abuses of human rights. Both locally and internationally, victims of human trafficking run the danger of being exploited, violent, or infected with contagious illnesses. The Indonesian government has not fully complied with the minimal criteria for safeguarding victims of human trafficking, notwithstanding Law Number 21 of 2007 for the Eradication of the Crime of Human Trafficking. Human rights restoration and respect for victims of human trafficking must be given priority in the implementation of legal protection for these individuals. To strengthen and increase the security of victims’ rights in the future, this study intends to conduct a thorough analysis of the humanism approach model and policies for safeguarding victims of human trafficking. This research uses an empirical technique to support its normative legal analysis. Primary and secondary legal sources are used in this research. The study’s findings show that the protection provided by humanist criminal law for victims of human trafficking is founded on humanitarian principles that derive from the divine principles found in the Pancasila ideology. There are additional requirements for punishment, such as its purpose, its ability to serve as therapy, and its determination to reflect the victim’s and society’s sense of justice. This criminal law is founded on the principles of legality and balance.

Film image processing and production based on high-performance calculation

In film and television production, efficient and precise image processing is vital for achieving realistic visual effects. Therefore, exploring and applying advanced image processing technologies has become an essential method for elevating the production quality of film and television projects. This work investigates the application of artificial intelligence (AI) technology in the processing and production of animated images in film and television scenarios. By comparing the performance of standard Generative Adversarial Network (GAN), DenseNet, and CycleGAN models under different noise conditions, it is found that CycleGAN performs the best in image denoising and detail restoration. Experimental results demonstrate that CycleGAN achieves a Peak Signal-to-noise Ratio (PSNR) of 30.1dB and a Structural Similarity Index Measure (SSIM) of 0.88 under Gaussian noise conditions. Moreover, CycleGAN achieves a PSNR of 29.5dB and an SSIM of 0.85 under salt-and-pepper noise conditions. It outperforms the other models in both conditions. Additionally, CycleGAN’s mean absolute error is significantly lower than that of the other models. This work demonstrates that CycleGAN can more effectively handle complex noise and generate high-quality images under unsupervised learning conditions. These findings provide new directions for future image processing research and offer important references for model selection in practical applications. This work not only offers new perspectives on the development of animation image processing technology but also establishes a theoretical foundation for applying advanced AI techniques in film and television production. Through comparative analysis of various deep learning models, this work highlights the superior performance of CycleGAN under complex noise conditions. This advancement not only drives progress in image processing technology but also provides effective solutions for efficient production and quality enhancement of future film and television works.

Performance Analysis of ML and DL Models: Impact of Linear and Non-Linear Optimizers on Model Efficiency

Introduction: Emphasizing the effect of linear and non-linear optimizers on the performance of machine learning (ML) and deep learning (DL) models, this work addresses the CIFAR-10 image classification task. The work explores over multiple data sets how optimizers influence model behavior and efficiency. Objectives: With a view on five primary assessment metrics—accuracy, precision, recall, F1-score, and AUC the main purpose is to evaluate on SVM and CNN models the performance of linear optimizers (gradient descent, SGD) and non-linear optimizers (Adam, RMSProp). Methods: The study offers fair and complete comparison by way of a consistent evaluation strategy. Analyzing how different optimizer influences model convergence rates, computational cost, and training stability takes front stage in the experimental setting. Designed on CIFAR-10, optimizers are used on ML and DL models whose performance on all metrics is noted. Results: Results show that non-linear optimizers especially Adam much increase CNN model performance by means of faster convergence, higher classification accuracy, and better model stability. While helpful for simpler models, linear optimizers such SGD show slower convergence and limited adaptation with more complicated data. Conclusions: This study provides direction on selecting appropriate optimizers depending on model complexity, job needs, and computing restrictions coupled with important information on optimizing model training in image classification and other areas.

Investigation on novel ultralight weight thermally insulated fireproof composite

Abstract This study highlights the performance of ultra-lightweight fireproof composite. Polyacrylonitrile based carbon fiber (CF) has been reinforced in Polyetherimide (PEI) polymer to develop the composite. The Surfac2e of CF and PEI film was modified by low-pressure plasma to improve the bonding strength between matrix and reinforcement. The polymeric composite was fabricated by compression molding with a pressure of 2 bar, temperature of 380 °C and holding time of 30 min. CF/PEI composite was used to make a hybrid composite by layering of silicone foam in between the layers. The hybrid composite was exposed to a Bunsen burner under sustained flame for a duration of 10 min. The composite panel’s flame-facing side reached 676.2 °C after 10 min of fire exposure, while the temperature on the other side only reached 58.2 °C. The fabricated hybrid composite was exposed to very low temperature in order to test its ability of thermal insulation under extreme cold temperature. Over the specific period of testing, the temperature of the dry ice decreased from 25 °C to −3.1 °C. After exposure to fire, only minimal loss of material was observed. The hybrid composite of carbon fiber and PEK film, sandwiched between silicone foam, exhibits excellent fire resistance due to its high limiting oxygen index. This composite is considered to be among the best thermally insulating and fire-resistant materials. Thermogravimetric analysis of carbon fiber and PEI-Carbon fiber composite was performed to determine the optimal processing temperature of compression molding for the composite, upon heating, it showed a modest weight decrease of 6.053%. The composite shows a significant improvement of impact resistance, compressive strength and thermal stability. A simulation model was developed under Ansys fluent software for both heating and cooling. The analysis of developed model also shows similar results.

Experimental Assessment between Dissimilar Techniques and Methodologies to Sports Knee Injury using Magnetic Resonance Imaging

The anterior cruciate ligaments, which are crucial for conserving the normal biomechanics of human being knees, are the majority commonly injured knee-ligaments. An anterior cruciate ligament injury is originated by a split or wrench of the anterior cruciate ligaments, which are imperative ligaments in the knee. ACL injure is mainly and frequently caused by sports like football, soccer, and the like that require quick pauses or direction changes, jumping, and landings. These days, the area of diagnostics heavily relies on magnetic resonance imaging. It is effective in determining the presence of meniscal tears and damage to the cruciate ligament. This study's primary objective is to use magnetic resonance imaging knee images to find anterior cruciate ligament tears, which can be useful in identifying issues with the knee. Inception-v3, an established deep transfer learning (DTL) model based on a DCNN was used in this study to classify anterior cruciate ligament tears in MRI scans. Classification, Preprocessing, and feature extraction are the major processes used in the current study executions. The dataset type utilized in this article of research study was built using the MRNet database. Seventy percent of the data set is used for preparation and testing, while the lingering thirty percent is utilized for performance analysis in this comparison model. The future augmented methodology can improve upon the present models' performance through the application of DL and ML techniques.

Sugar-sweetened beverage consumption in Thailand: Determinants and variation across socioeconomic status

ObjectivesReducing consumption of sugar-sweetened beverages (SSBs) is a primary public health goal in Thailand, but information on the characteristics of SSB consumers remains limited. This study aims to gain knowledge about the characteristics of SSB consumers in Thailand. Study designSecondary analysis of survey data. MethodsThe study used data from the Health Behaviour of Population Survey conducted by Thailand's National Statistics Office between February and May 2021. SSB consumption was sourced from a survey question about the consumption of prepackaged sugar-sweetened non-alcoholic beverages. The influence of demographic, socioeconomic, behavioural, habitual, and health factors on mean daily intake and daily consumption was assessed using a two-part model and logistic regression analysis, respectively. Decomposition analysis was conducted to understand how the impact of these factors affecting SSB consumption varied across socioeconomic groups. ResultsFrequent SSB consumers exhibited various unhealthy behaviours, including smoking, unhealthy food consumption, low physical activity, and making food selections driven by appetitive motivations. Although higher socioeconomic status was associated with greater consumption of SSBs, it stabilised at elevated income levels. Increased SSB consumption in higher socioeconomic groups was linked to mixed eating habits, being overweight, and occasional drinking, while in lower socioeconomic groups, it was associated with unhealthy behaviours like smoking, regular alcohol drinking, appetitive food choices, and low physical activity. ConclusionsSSB consumption in Thailand is multifactorial, varying by socioeconomic status. These insights are crucial for policy formation aimed at reducing SSB consumption in the country. Policymakers should explore interventions that address overall unhealthy behaviours alongside those targeting overconsumption of SSBs.

ASK HEART GAME CARD DEVELOPMENT TO PROVIDE AN UNDERSTANDING OF MARRIAGE READINESS IN EARLY ADULTHOOD

This research aims to provide an understanding of marriage readiness in early adulthood through the media of the Tanya Hati card game as an effort to fulfill one of the developmental tasks in early adulthood. Apart from that, this research was carried out as a form of optimizing the Guidance and Counseling program through the development of Guidance and Counseling media in the form of game cards. The research method used is “Research and Development” using the ADDIE model (analysis, design, development, implementation and evaluation). Data collection through observation, interviews and questionnaires. The research results show that the Tanya Hati card game media developed is very suitable for use with an average result of 85% from expert assessments. Based on limited trials on 8 students, the heart question card game media obtained a score of 84%. The research results show that the development of the Tanya Hati card game media is valid and effective as a medium that provides an understanding of marriage readiness in early adulthood.

Mathematical model and backward bifurcation analysis of pneumonia infection with intervention measures

Mathematical model and backward bifurcation analysis of pneumonia infection with intervention measures

An integrated microbiome- and metabolome-genome-wide association study reveals the role of heritable ruminal microbial carbohydrate metabolism in lactation performance in Holstein dairy cows.

Despite the growing number of studies investigating the connection between host genetics and the rumen microbiota, there remains a dearth of systematic research exploring the composition, function, and metabolic traits of highly heritable rumen microbiota influenced by host genetics. Furthermore, the impact of these highly heritable subsets on lactation performance in cows remains unknown. To address this gap, we collected and analyzed whole-genome resequencing data, rumen metagenomes, rumen metabolomes and short-chain fatty acids (SCFAs) content, and lactation performance phenotypes from a cohort of 304 dairy cows. The results indicated that the proportions of highly heritable subsets (h2 ≥ 0.2) of the rumen microbial composition (55%), function (39% KEGG and 28% CAZy), and metabolites (18%) decreased sequentially. Moreover, the highly heritable microbes can increase energy-corrected milk (ECM) production by reducing the rumen acetate/propionate ratio, according to the structural equation model (SEM) analysis (CFI = 0.898). Furthermore, the highly heritable enzymes involved in the SCFA synthesis metabolic pathway can promote the synthesis of propionate and inhibit the acetate synthesis. Next, the same significant SNP variants were used to integrate information from genome-wide association studies (GWASs), microbiome-GWASs, metabolome-GWASs, and microbiome-wide association studies (mWASs). The identified single nucleotide polymorphisms (SNPs) of rs43470227 and rs43472732 on SLC30A9 (Zn2+ transport) (P < 0.05/nSNPs) can affect the abundance of rumen microbes such as Prevotella_sp., Prevotella_sp._E15-22, Prevotella_sp._E13-27, which have the oligosaccharide-degradation enzymes genes, including the GH10, GH13, GH43, GH95, and GH115 families. The identified SNPs of chr25:11,177 on 5s_rRNA (small ribosomal RNA) (P < 0.05/nSNPs) were linked to ECM, the abundance alteration of Pseudobutyrivibrio_sp. (a genus that was also showed to be linked to the ECM production via the mWASs analysis), GH24 (lysozyme), and 9,10,13-TriHOME (linoleic acid metabolism). Moreover, ECM, and the abundances of Pseudobutyrivibrio sp., GH24, and 9,10,13-TRIHOME were significantly greater in the GG genotype than in the AG genotype at chr25:11,177 (P < 0.05). By further the SEM analysis, GH24 was positively correlated with Pseudobutyrivibrio sp., which was positively correlated with 9,10,13-triHOME and subsequently positively correlated with ECM (CFI = 0.942). Our comprehensive study revealed the distinct heritability patterns of rumen microbial composition, function, and metabolism. Additionally, we shed light on the influence of host SNP variants on the rumen microbes with carbohydrate metabolism and their subsequent effects on lactation performance. Collectively, these findings offer compelling evidence for the host-microbe interactions, wherein cows actively modulate their rumen microbiota through SNP variants to regulate their own lactation performance. Video Abstract.

Analysis of Sustainable Efficiency of Freight Transport in Major European Economies: An Integrated Multi-Region Input-Output and DEA Approach

This paper integrates the multi-region input-output model (MRIO) and data envelopment analysis (DEA) methods to analyze the freight transport efficiency in Europe. Social, economic, and environmental influences were combined into a sustainable efficiency rating of the freight transport sector of Germany, France, Italy, Spain, and the Netherlands. First, the freight transport sector's carbon footprint (CFP) was quantified using the MRIO model. The lifecycle-based CFP emissions of freight transport activities were assessed using a dataset from 2000 to 2018. Nineteen stochastic model-based MRIO lifecycle assessments were built for each country. Secondly, sixty instances of DEA models were created using a linear program for each mode in the selected countries. Thirdly, the sustainable efficiency scores were determined for each freight transport mode in each country over four periods: 2000–2004, 2005–2009, 2010–2014, and 2015–2018. The results illustrate that the sustainable efficiency score of inland, water, and air transport modes ranged from 0.38 to 1.

Finite Element Modeling and Artificial Neural Network Analyses on the Flexural Capacity of Concrete T-Beams Reinforced with Prestressed Carbon Fiber Reinforced Polymer Strands and Non-Prestressed Steel Rebars

The use of carbon fiber reinforced polymer (CFRP) strands as prestressed reinforcement in prestressed concrete (PC) structures offers an effective solution to the corrosion issues associated with prestressed steel strands. In this study, the flexural behavior of PC beams reinforced with prestressed CFRP strands and non-prestressed steel rebars was investigated using finite element modeling (FEM) and artificial neural network (ANN) methods. First, three-dimensional nonlinear FE models were developed. The FE results indicated that the predicted failure mode, load-deflection curve, and ultimate load agreed well with the previous test results. Variations in prestress level, concrete strength, and steel reinforcement ratio shifted the failure mode from concrete crushing to CFRP strand fracture. While the ultimate load generally increased with a higher prestressed level, an excessively high prestress level reduced the ultimate load due to premature fracture of CFRP strands. An increase in concrete strength and steel reinforcement ratio also contributed to a rise in the ultimate load. Subsequently, the verified FE models were utilized to create a database for training the back propagation ANN (BP-ANN) model. The ultimate moments of the experimental specimens were predicted using the trained model. The results showed the correlation coefficients for both the training and test datasets were approximately 0.99, and the maximum error between the predicted and test ultimate moments was around 8%, demonstrating that the BP-ANN method is an effective tool for accurately predicting the ultimate capacity of this type of PC beam.

Abstract 4138374: Coronary Endothelial Dysfunction Plays Important Roles on Development of Acute Coronary Syndrome and Fatal Cardiovascular Events During Long-Term Follow-up Over 10 Years

Introduction: Although coronary endothelial dysfunction is thought to affect coronary atherothrombogenic processes, there has been little practical evidence for the relationship between clinical evolution of fatal or non-fatal acute coronary syndrome and coronary endothelial dysfunction. Hypothesis: We assessed hypothesis that coronary endothelial dysfunction has clinical impacts on development of acute coronary syndrome and fatal cardiovascular events. Methods: Coronary endothelial dysfunction was practically graded by the flow-mediated endothelium-dependent reactive changes in coronary artery diameter (CFMD) to infusion of adenosine triphosphate (ATP ; 50μg) into the normal left coronary artery using quantitative coronary arteriography in 150 patients with stable coronary artery disease. The enrolled patients were categorized into tertile groups according to the values of CFMD, and we prospectively followed-up major adverse clinical cardiac events including acute coronary syndrome and cardiovascular death. Results: For a mean follow-up period of 132 months (range; 120 to 144) with complete follow-up, the patients in the lower third with severe coronary endothelial dysfunction (Group-L) more frequently developed acute coronary syndrome than those in the middle third with mild coronary endothelial dysfunction (Group-M) plus those in the higher third without coronary endothelial dysfunction (Group-H) [Group-L versus Group-M plus Group-H: 15(30%) versus 5(10%) plus 0(0%), p&lt;0.001, by Kaplan-Meier analysis]. Majority of the patients who resulted in cardiovascular death belonged to Group-L, [6(12%) versus 1(2%) plus 0(0%), p=0.014, by Kaplan-Meier analysis]. Cox hazard proportional model analyses including clinical and angiographical variables indicated that severe coronary endothelial dysfunction was the strong predictor for future acute coronary syndrome (hazard ratio=7.53, 95%confidential interval; 1.78-12.25, p&lt;0.001) and future cardiovascular death (hazard ratio=13.50, 95%confidential interval; 1.55-25.25, p=0.005). Conclusions: This is the novel and longest follow-up investigation that demonstrates coronary endothelial dysfunction plays important roles on development of acute coronary syndrome and fatal cardiovascular events and therefore the strategies based on practical status of coronary endothelial dysfunction are required to prevent major adverse ischemic cardiac events.

Examining the Impact of Pandemic Stressors on Parental Stress in Sub‐Saharan Africa: A Double ABC‐X and Moderated Mediation Model Analysis of Family Mechanisms

ABSTRACTThis study investigated family mechanisms through which pandemic stressors affect parental stress using the Double ABC‐X model of family stress and adaptation. Specifically, this study examines the moderated mediation effects to test the conditional indirect influence of a moderating variable (i.e., family resilience beliefs) on the relationship between a predictor (i.e., stressor pile‐up) and an outcome variable (i.e., stress) through potential mediators (i.e., family satisfaction and relationship satisfaction). The analytic sample included 9269 participants from 10 sub‐Saharan countries. The findings do not support the hypothesis predicting a second‐stage moderating mediation model where family resiliency beliefs would moderate the second‐stage indirect paths of family satisfaction and relationship satisfaction, creating conditional indirect effects. The findings suggest that interventions should involve community‐based programmes that emphasize family support and access to resources while recognizing the complex interplay between family resilience beliefs, cultural values and beliefs of African families.

Gestational diabetes mellitus (GDM): diagnosis using biochemical parameters and anthropometric measurements during the first trimester in the Indian population.

The objective of the study was to use anthropometric measurements (age, BMI, and subcutaneous fat) inconjunction with biochemical parameters (sex hormone-binding globulin (SHBG), homeostasis model assessment-insulin resistance (HOMA-IR), fasting glucose, serum insulin, and total cholesterol) to predict the probability of gestational diabetes mellitus (GDM) in the first trimester. The study enrolled 48 pregnant women with GDM and 64 high-risk pregnant women without GDM. During the first-trimester examination, maternal blood samples were collected to measure SHBG, fasting blood glucose, serum insulin, and total cholesterol levels. Regression model analysis was used to examine the variables that showed statistically significant differences between the groups and were independent predictors of GDM. Receiver operating characteristic (ROC) curve analysis was employed to determine the risk of developing GDM based on cut-off values. The levels of SHBG, HOMA-IR, serum insulin, fasting glucose, and total cholesterol were identified as significant independent markers for predicting GDM. Meanwhile, age, body mass index, and subcutaneous fat values were found to be non-independent predictors of GDM. The areas under the ROC curve were calculated to determine the predictive accuracy of total cholesterol, HOMA-IR, SHBG, and subcutaneous fat for developing into GDM, and were 0.869, 0.977, 0.868, and 0.822 respectively. The sensitivities for a false positive rate of 5 % for predicting GDM were 68.7 , 91.67, 91.7, and 97.9 % for total cholesterol, HOMA-IR, SHBG, and subcutaneous fat, respectively. The independent predictors for the subsequent development of GDM in high-risk pregnancies are HOMA-IR, SHBG, Total cholesterol, and subcutaneous fat (SC) levels. These parameters can be used to create a regression model to predict the occurrence of GDM.

Simple model, complex strata: 2-D numerical forward model analysis of heterogeneity and controls in submarine fan systems

ABSTRACT Turbidite strata stacking patterns are interpreted as products of either allogenic forcing, autogenic processes, or a combination of both. However, the relative influence of each remains difficult to constrain. Here, a simple reduced-complexity 2-D numerical forward model (Lobyte2D) simulates gravity flows passing down a slope, running out, and depositing across a flat basin floor. Flows can erode, bypass, or deposit, cumulatively producing a variety of entirely autogenic retrograding, aggrading, and prograding strata with stratigraphic completeness values ranging from less than 1% to around 40%. Complexity of modeled strata is measured with a spatial entropy metric, and sensitivity analysis indicates that grain-size and flow-acceleration parameters are the key controls on stratal complexity: larger grain sizes are associated with deeper erosion, which makes more rugged topography, and higher values of flow acceleration make flow speeds more sensitive to topography, which triggers localized deposition and/or erosion. Such complexity produced by a simple two-dimensional numerical forward model suggests that even more complex behavior is likely in natural systems, and this should be reflected in outcrop and subsurface interpretations. However, comparison of geometries in chronostratigraphic and cross-section plots of modeled strata shows that, due to a variety of cryptic bypass and erosion surfaces, stacking trends visible in chronostratigraphic plots are much more difficult to detect in outcrop and subsurface cross sections and vertical sections. These insights suggest that many outcrop and subsurface interpretations of submarine-fan strata, particularly sequence stratigraphic interpretations, may be missing substantial complexity, and underestimating the uncertainty inherent in limited data.

Effects of GlideScope, Pentax Airway Scope, and Macintosh Blade on the incidence of postoperative sore throat: a cohort study of 9,881 patients.

Postoperative sore throat (POST) is a common complaint after general anesthesia. POST is defined by the presence of a self-reported foreign body sensation or a painful sensation in the throat after general anesthesia. This condition may affect recovery and patient satisfaction and is associated with many factors, including intubation tools. Previous studies have reported conflicting results on POST. This retrospective cohort study, with sample size of 9,881 patients, was conducted to confirm the hypothesis that the use of video laryngoscopy (VL) is associated with a lower incidence of POST compared with direct laryngoscopy (DL). Data were extracted from a prospectively maintained quality improvement database. A total of 9,881 patients were included in the study. Statistical analysis was conducted for comparisons of demographic characteristics and to determine the effect of intubation tools on the incidence of POST. The patients had similar baseline demographic characteristics. Compared with DL, VL was associated with a lower incidence of POST (12.98% vs. 17.49%, P < 0.001). In addition, the use of Pentax Airway Scope (AWS) was associated with a lower incidence of POST compared with the use of GlideScope (GVL, 8.14% vs. 16.25%, P < 0.001). To better adjust for possible confounding factors, mixed-effects generalized linear model analysis revealed that older age (odds ratio [OR]: 0.995, 95% confidence interval [CI]: 0.992-0.999, P = 0.006), AWS compared to DL (OR: 0.416, 95% CI: 0.350-0.494, P < 0.001), and male sex (OR: 0.836, 95% CI: 0.747-0.935, P = 0.002) are associated with reduced incidence of POST. Compared with DL, VL is associated with a lower incidence of POST. In addition, the use of AWS is associated with a lower incidence of POST compared with the use of GVL. Retrospectively registered, NCT06515808, date of registration: 23/07/2024.

Abstract 4122763: Health Status Outcomes of Antianginal Therapies in Patients After Coronary Revascularization: Insights From the GREAT Disease Registry Study

Background: The impact of antianginal therapies on the health status of coronary artery disease (CAD) patients who have undergone coronary revascularization has not been extensively researched. This study aimed to investigate the effect of nicorandil on the health status in patients after coronary revascularization, measured by the Seattle Angina Questionnaire (SAQ). Methods: We analyzed data from 1,556 patients enrolled in the GREAT Disease Registry Study (Clinicaltrial No. NCT05050773) between September 2021 and May 2022. Changes in SAQ summary score (SAQ-SS) from baseline to 3, 6, 9, and 12 months were assessed. Statistical methods included a linear mixed-effects model and propensity score matching (PSM) for comparative analysis. Results: Among the 1,038 patients receiving revascularization analyzed (22.7% female; mean age [SD], 59.9 [10.2] years), 648 (62.4%) received nicorandil, while 390 (37.6%) did not. In the linear mixed-effects model analysis, statistically significant improvements were observed with nicorandil in SAQ-SS across all time points ( Table 1 ), indicating beneficial effects of nicorandil on health status outcomes after revascularization. Sensitive analysis was conducted using the PSM method. After PSM adjustment, both groups comprised 321 patients each. The change in SAQ-SS from baseline to 12 months was significantly greater in the nicorandil group (19.2 ± 14.06 points) compared to the non-nicorandil group (14.91 ± 12.9 points, p &lt; 0.001). Conclusions: These findings indicated that nicorandil is associated with improved health status outcomes in CAD patients who have undergone coronary revascularization.