Curve Fitting Research Articles

Multi-layer and multi-pass welding trajectory planning of thick-walled pipes intersecting curve in a pressure vessel

ABSTRACT Robot welding technology for complex curve in thick-walled pipes is crucial for for engineering applications. The Y-groove weld, characterized by a unilateral V-shaped groove with a blunt edge and commonly found in T-joints, is extensively utilized of class D welding seam in thick-walled pipes. To enhance welding efficiency and quality, simulation platform and an experimental platform have established for collaborative welding robots. A welding robot is employed to realize motions of seam tracking and arc motion, and a clamping robot is employed to realize motions of spatial position. Proposed a welding strategy involving multi-layer and multi-pass welding techniques for Y-groove weld. Developed mathematical models to maintain constant linear speed interpolation of the Tool Center Point (TCP) and equiangular interpolation of the pipe in coordinated welding process. Implemented a curve fitting algorithm for class D welding seam to determine end poses of both robots, ensuring flat welding accuracy while adhering to chord error limit and constant linear speed principle. These algorithmic models have been verified through testing using MATLAB and ADAMS. By inputting the final data into the experimental platform for coordinated welding, a good coordinated welding effect is achieved, which verifies the feasibility and effectiveness of the proposed model.

Obesity mediates the association between psoriasis and diabetes incidence: a population-based study

IntroductionThe aim of this study was to explore the association between psoriasis and diabetes and to assess the potential moderating role of obesity in this relationship.MethodsThe study involving data from 21,835 NHANES participants during 2003–2006 and 2009–2014. The analysis included body mass index (BMI), as well as information about psoriasis and diabetes obtained from questionnaires. The study employed weighted logistic regression to examine the association between psoriasis and diabetes. The nonlinear relationship between obesity, diabetes, and psoriasis was explored through smooth curve fitting, stratified by age and gender. In addition, the authors conducted mediation analysis, which suggested that obesity partially mediated the association between psoriasis and diabetes prevalence.ResultsAfter adjusting for relevant variables, we found that individuals with psoriasis had a significantly higher incidence of diabetes (OR = 1.48, 95% CI = 1.16–1.90, P = 0.002). A positive relationship was identified between BMI levels and diabetes occurrence among individuals with psoriasis, with a significant difference observed between the highest (Q4) and lowest (Q1) BMI quartiles (P < 0.05). Further analysis using smooth curve fitting demonstrated the consistent association between BMI and diabetes, which was also evident in psoriasis patients. Age-stratified analysis showed that diabetes was more prevalent among older adults compared to younger individuals at the same BMI levels. For psoriasis, an inflection point was noted in men where its prevalence began to decline as BMI exceeded a certain threshold. Similarly, in younger adults, psoriasis prevalence decreased above a specific BMI threshold. Additionally, mediation analysis indicated that obesity played a partial role in linking psoriasis and diabetes, accounting for approximately 22.91% of this association.ConclusionThe study found an association between psoriasis and diabetes. Additionally, the analysis suggested that obesity may partially contribute to this relationship, indicating it could play a role in linking the two conditions.

On the reduction of imaging time-points for dosimetry in radionuclide therapy

BackgroundThe aim was to develop a theoretical framework for how errors in estimated activities propagate to a dispersion in time-integrated activity in radionuclide-therapy dosimetry and how this affects the comparison of radionuclide-therapy dosimetry schemes.MethodsFormulae for the variance of relative errors of estimated time-integrated activities and relative differences in time-integrated activities between measurement schemes when one or more time-points are removed were derived using the law of propagation of uncertainty for a population of time-activity-curve parameters. The formulae were derived under the assumptions of fixed coefficients of variation for estimated activities, and underlying mono-exponential curves. Analytical predictions were compared with results from numerical simulations and data for kidneys, liver, and spleen from a data-set of 18 patients treated with 177Lu-DOTA-TATE.ResultsThe dispersion in time-integrated activity is minimized if the time-points used for curve fitting have a large dispersion and are centered over the mean of τ=λeff-1 over the population, where λeff is the effective decay constant (i.e., the sum of the biological and physical decay constants). For large dispersions of decay constants in the population, the centering of time-points becomes gradually less important. The analytical expressions replicated the main trends from the numerical simulations. Furthermore, the analytical expressions predicted correctly the optimal reduced imaging schedule in 9 of 12 pairwise comparisons between schedules for patients.ConclusionsThe dispersion of errors and deviations in estimated time-activity curves can be predicted using simple formulae. These formulae have the potential to be used for optimization of dosimetry measurement schemes for established and new radiopharmaceuticals as long as the mean and dispersion of biological half-lives are known in the patient population.

United States floods within the context of atmospheric moisture sources and pathways

ABSTRACT The present study introduces a comprehensive framework that aims to (a) identify major causes of annual floods using a hydroclimate-based classification, (b) determine the atmospheric moisture tracks linked to flood events based on a new approach that uses the principal curves, and (c) adopt a new modality for risk analyses and estimation of hydroclimatic non-stationarity by climate-informed partitioning of the flood record. The results show that in 623 stream gauges across the conterminous US over the 1956–2015 period, a total of 25,725 (∼73%) out of 37,380 annual floods are caused by atmospheric rivers (ARs). As such, most basins in the Northwest, West, Northeast, and Southeast climate regions observed 70–100% of their annual flood records caused by ARs, while it is widely varying below 70% in the Central, South, East North Central, and 50% in the Southwest. However, ARs cause less than 15% of annual floods in the West North Central. In terms of magnitude, stations with heterogeneous floods and highly affected by ARs have higher ratios of AR-generated floods to non-AR 100-year floods. Finally, the characterization of place-based mixed population floods by ARs moisture sources provides a satisfactory fit of flood frequency curves and determines sources associated with high-risk floods.

Flame Recognition and Location Algorithm based on YOLO v5s and Binocular Vision

Abstract An improved YOLO v5s framework in conjunction with binocular vision is developed to fulfill the stringent requirements for precise identification and accurate localization of flames. An Efficient Multi-scale Attention (EMA) mechanism is seamlessly integrated into the backbone network of the YOLO v5s model, thereby significantly improving the capacity to focus on and interpret critical target features. To bolster the multi-scale feature fusion capability, the Bidirectional Feature Pyramid Network (BiFPN) is strategically introduced at the fusion layer within the object detection architecture. The Semi-Global Block Matching (SGBM) algorithm is deployed to synchronize the binocular images, complemented by the least squares curve fitting method to adjust location inaccuracies, enhancing the precision of flame positioning. A binocular vision system is meticulously constructed to facilitate a series of rigorous experiments on flame detection and location. The experimental results demonstrate that the improved YOLO v5s network model achieves an exceptional flame recognition rate of 96.25%, which represents a noteworthy increase of 0.98% in accuracy in comparison to the original YOLO v5s model. Additionally, within a distance range of 3 to 10 meters, the flame ranging error is consistently less than 0.1 meters, successfully realizing the objective of high-precision flame detection and localization.

Serum uric acid/creatinine ratio and 1-year stroke recurrence in patient with acute ischemic stroke and abnormal renal function: results from the Xi'an stroke registry study of China

BackgroundThe relationship between abnormal renal function and serum uric acid levels in patients with acute ischemic stroke (AIS) remains insufficiently explored. Although uric acid is associated with cardiovascular and cerebrovascular risk, the specific link between normalized serum uric acid (SUA/SCr) and stroke recurrence in patients with impaired renal function has not been well studied. This study aims to fill this gap by investigating the association between SUA/SCr and 1-year stroke recurrence in patients with AIS and abnormal renal function.MethodsThis study utilized the ratio of serum uric acid (SUA) to serum creatinine (SCr) to represent SUA levels normalized for renal function. Abnormal Renal function was defined by the estimated glomerular filtration rate (eGFR) &amp;lt; 90 mL/min/1.73 m2. Multivariable Cox regression, curve fitting, and stratified analyses were employed to assess the relationship between SUA/SCr and 1-year stroke recurrence in patients with AIS and abnormal renal function, considering SUA/SCr as both a continuous variable and in quartiles (Q1–Q4).ResultsOf 1,932 enrolled patients (65.3% male; mean age 66.7 ± 11.3 years), each unit of increase in SUA/SCr was associated with a 17% decrease in 1-year stroke recurrence (HR = 0.83, 95% CI 0.73 to 0.96, P = 0.009). Compared to Q1, the Q2 and Q4 groups showed significantly reduced risk in 1-year stroke recurrence (Q2: HR = 0.46, 95% CI 0.27 to 0.79, P = 0.005; Q4: HR = 0.47, 95% CI 0.27 to 0.81, P = 0.007), with a significant trend across all quartiles (P = 0.01 for trend tests). Curve fitting revealed a negative but non-linear correlation. Subgroup analyses showed that in patients with eGFR &amp;lt; 60 ml/min/1.73 m2, Q4 had significantly lower 1-year stroke recurrence risk than Q1 (HR = 0.19, 95% CI 0.04 to 0.86, P = 0.031).ConclusionLow SUA/SCr independently predicts 1-year stroke recurrence in patients with AIS and abnormal renal function, particularly in those with eGFR &amp;lt; 60 mL/min/1.73 m2.

Automatic and accurate phase aberration compensation for a digital holographic microscopy system based on one-dimensional weighted curve fitting

We propose an automatic and accurate phase aberration compensation method for a digital holographic microscopy system. The phase aberrations are extracted by the one-dimensional weighted curve fitting method where the pre-compensated phase is obtained by the phase segmentation method based on the median absolute deviation (MAD) criterion, and the weights of the object phase and the background phase are acquired such that the object phase can be eliminated. Our approach does not require manual selection of area with no sampling and prior optical system parameters. Numerical simulation verifies that the proposed method is more accurate than the general one-dimensional curve fitting method. Experimental measurements demonstrate the effectiveness and applicability of the proposed method in USAF1951 resolution plates and living cells including BCAF breast cancer cells and HCT116 colon cancer cells.

Nonlinear relationship between hepatic steatosis index and reversion to normal glucose regulation in Chinese adults with prediabetes.

The hepatic steatosis index (HSI) has been demonstrated to have a significant correlation with prediabetes and diabetes; however, its potential association with reversion to normal glucose regulation (NGR) from prediabetes remains insufficiently investigated. The primary objective of this study was to elucidate the relationship between HSI levels and the probability of reversion to NGR among Chinese adults with prediabetes. This retrospective cohort study utilized health examination data from 11,241 Chinese adults with prediabetes. Cox proportional hazard models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI) to assess the association between HSI levels and reversion to NGR. Additionally, a Cox proportional hazards regression model incorporating cubic spline functions and smooth curve fitting was utilized to determine any nonlinear relationships between HSI levels and reversion to NGR. The results of the multivariate analyses demonstrated a significant association between reduced HSI levels and an increased likelihood of reversion to NGR (HR = 0.92, 95%CI: 0.89-0.95, P < 0.0001). Furthermore, a nonlinear relationship was identified between HSI levels and the reversion to NGR, with a critical threshold at an HSI value of 43.08. Below this threshold, a strong negative association was observed, markedly enhancing the probability of returning to normoglycemic status (HR = 0.91, 95% CI: 0.88-0.94, P < 0.0001). This study reveals a negative, nonlinear correlation between HSI levels and the reversion to NGR in individuals with prediabetes. These findings highlight the essential role of effectively managing HSI as part of comprehensive prediabetes treatment strategies, which may significantly enhance the likelihood of achieving normoglycemic status.

Integrating feedback control for improved human-structure interaction analysis

The human body, composed of interconnected subsystems with complex dynamic behavior, is often oversimplified or neglected by structural designers and building codes. Human-induced loads, whether passive (e.g., standing, sitting) or active (e.g., walking, dancing, jumping), considerably impact the dynamic response of structures such as grandstands, slender slabs, and pedestrian bridges, highlighting the necessity for their consideration in design. This study introduces three closed-loop control models to represent the human-structure interaction (HSI) effect: a Proportional Integral (PI) controller, the Pole Placement control algorithm (PP), and the Linear Quadratic Regulator with an Observer (LQR + L). While well-established in robotics and automation engineering, these control algorithms represent a novel and transformative approach when applied to HSI. They offer an intuitive and effective framework for modeling the dynamic feedback mechanisms inherent in HSI. The model parameters are obtained using global optimization and curve fitting methods, followed by experimental validation on a test structure. The results of this study indicate that feedback controllers accurately predict the experimental structural response for different subjects. These findings highlight the importance of incorporating HSI effects into structural design, promising the design of safer and more comfortable structures in human-occupied environments.

An optional formula for calculating crustal thickness using Sr/Y ratio and its application to the southeastern margin of the Central Asian Orogenic Belt

ABSTRACT Though tracking changes in crustal thickness during orogenic evolution with specific element ratios has been proven effective, available empirical formulas sometimes yield unreasonable results. In this study, we proposed a new formula for calculating the crustal thickness by the Sr/Y ratio. Global lower crust-derived magmatic rock (younger than 23 Ma) data from diverse geological settings were selected and filtered using key geochemical criteria, alternating and iteratively using K-means clustering algorithm and improved Thompson tau method to exclude outliers. Curve fitting between the filtered elemental ratios and crustal thickness showed that the formula derived from maximum Sr/Y is best fitted by quadratic fitting. The rmse value between the calculated crustal thickness using the new Sr/Y formula and the true values worldwide is 14.84, lower than those of previous formulas ranging from 19.15 to 32.77. It is shown that our new formula possibly performs better for revealing temporal variations of Paleozoic crustal thickness at the southeastern margin of the Central Asian Orogenic Belt. During the Early Paleozoic Era, the crustal thickness of the Bainaimiao arc increased, corresponding to the subduction of the Southern Bainaimiao Ocean. In the Devonian, the crust in the Bainaimiao arc and northern North China Craton both continued thinning, implying for a post-collisional setting after the amalgamation between these two blocks. Crustal thickness in northern North China experienced transition from thickening to thinning, revealing a subduction-related convergent setting in the Carboniferous and an extensional setting due to slab roll-back in the Early Permian. The crustal thickness rapidly increased in the Late Permian and decreased in the Triassic, consistent with syn-collisional and post-collisional settings, respectively, associated with final closure of the Paleo-Asian Ocean. These results demonstrated that crustal thickness evolution of an orogen can be depicted in detail by our new formula and can put more insights into the understanding the complex histories of accretionary orogenic belts.

Small unmanned helicopter system identification based on the weighted least square method and improved grey wolf optimisation algorithm

Abstract Aiming to address the issue of low accuracy in model predictions obtained from fitting frequency domain response curves for small unmanned helicopters during the process of modeling their flight dynamics, this study proposes a system identification algorithm based on the combination of weighted least squares and improved grey wolf optimisation algorithm. The algorithm utilises the weighted least squares method to obtain the initial model structure, optimises the initial model parameters using the improved grey wolf optimisation algorithm, and enhances the local search and global optimisation ability of the grey wolf optimisation algorithm by introducing an improved grey wolf subgrouping rule, nonlinear convergence factor and dynamic cooperative rule. Ultimately, this approach establishes a dynamic model for small, unmanned helicopters. The identified model is validated using flight test data, with findings demonstrating that this method achieves higher accuracy in model identification and better fits to frequency domain response curves, thus providing a more accurate reflection of the flight dynamics of small unmanned helicopters.

Association of a novel nutritional index with cognitive impairment in middle-aged and elderly Chinese adults: a cross-sectional analysis from the China Health and Retirement Longitudinal Study

PurposeThe triglyceride-cholesterol-body weight index (TCBI), a novel and easily computable nutritional index, incorporates serum triglyceride (TG), total cholesterol (TC), and body weight (BW). This study explored the association between TCBI and cognitive impairment in middle-aged and elderly Chinese populations.Patients and methodsThis cross-sectional study employed data from the China Health and Retirement Longitudinal Study (CHARLS) baseline survey, including 7,145 participants. TCBI was calculated as TG (mg/dL) × TC (mg/dL) × BW (kg)/1,000. Cognitive function was assessed based on mental status and episodic memory, with a total score below 11 indicating cognitive impairment. The relationship between TCBI and cognitive impairment was examined using multiple logistic regression, smooth curve fitting, and subgroup analyses.ResultsAfter full adjustment, each 1-unit increase in log-transformed TCBI (Lg TCBI) was associated with a 29.7% reduction in cognitive impairment risk [odds ratio (OR) = 0.703, 95% confidence interval (CI): 0.529–0.933; p = 0.015]. When Lg TCBI was categorized into quartiles, the Q2, Q3, and Q4 groups exhibited a reduced risk of cognitive impairment by 19.9, 16.3, and 22.9%, respectively (p for trend = 0.043), compared to the Q1 group. Smooth curve fitting revealed a consistent decrease in cognitive impairment risk with higher Lg TCBI levels. Subgroup analysis indicated that the association was stronger among participants aged ≥60 years (OR = 0.655, 95% CI: 0.438–0.979), non-current drinkers (OR = 0.643, 95% CI: 0.451–0.917), and those who engaged in socializing (OR = 0.568, 95% CI: 0.371–0.871).ConclusionTCBI was significantly and negatively associated with cognitive impairment in Chinese middle-aged and elderly individuals, with the effect more pronounced in those aged ≥60 years, non-current drinkers, and socially active participants.

Fluctuating Genetic Influences at Three Different Stages of Development of Dental Arches: A Complex System

Background/Objectives: The development of dental arches is a complex adaptive system with interactions between genetic and environmental factors. At different developmental stages, the relative contribution of these factors varies. The aims of this project were to identify the longitudinal changes of dental arches in the primary, mixed and permanent dentition stages, using curve fitting methods on serial dental casts, and to investigate the contribution of the genotype to dental arch development. Methods: Longitudinal dental records from 125 monozygotic same-sex twin pairs, 89 dizygotic same-sex twin pairs, and 49 opposite-sex dizygotic twin pairs were used. Standardized model photographs were collected, and key landmarks were digitized. Fourth-order orthogonal polynomials were applied to the Cartesian data. Descriptive statistics were calculated, and structural equation models were developed to analyze the individual polynomial coefficients. The final models employed a genetic simplex framework, enabling the evaluation of how genetic and environmental influences changed over time. These changes were examined both quantitatively (e.g., variations in heritability) and qualitatively (e.g., the influence of different genes at various stages). Results: In the primary dentition, arches were typically parabolic, while in the permanent dentition, they tended to be more square-shaped. Asymmetry made a minor contribution to variation across all stages of development. Genetic analysis revealed that a core group of genes influenced arch shape over time, though their impact varied. Additionally, some genes were specific to certain developmental stages, with their relative contributions differing significantly. Notably, there was evidence of sexual heterogeneity in arch shape, particularly in the permanent dentition. Heritability was consistently high, both at individual developmental stages and throughout the overall developmental process. Conclusions: The degree of genetic influence at each developmental stage was substantial but it fluctuated between the primary, mixed, and permanent dentition stages.

Nonlinear associations of the hs-CRP/HDL-C index with metabolic dysfunction-associated steatotic liver disease and advanced liver fibrosis in US adults: insights from NHANES 2017–2018

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a globally widespread chronic liver condition that may progress to severe liver diseases, including advanced liver fibrosis. The high-sensitivity C-reactive protein-to-high-density lipoprotein cholesterol (hs-CRP/HDL-C) index may be a potential indicator for MASLD and advanced liver fibrosis, given its relevance to inflammation and plasma lipids. In this study, the hs-CRP/HDL-C index was investigated in relation to prevalent MASLD and advanced liver fibrosis. The study analyzed secondary data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 database. The hs-CRP/HDL-C index was calculated by the quotient of hs-CRP and HDL-C. Multiple logistic regression models, Cochran-Armitage trend tests, smooth curve fitting, threshold effect analyses, and stratified analyses were used to evaluate whether the hs-CRP/HDL-C index associated with MASLD and advanced liver fibrosis. The study cohort comprised 3684 participants, of whom 1268 (34.42%) were diagnosed with MASLD and 156 (12.28%) with advanced liver fibrosis. Logistic analyses adjusted for covariates revealed positive associations of the hs-CRP/HDL-C index with MASLD and advanced liver fibrosis, consistent across all subgroups. Smooth curve fitting and threshold effect analyses revealed nonlinear relationships of hs-CRP/HDL-C index with MASLD and advanced liver fibrosis, with inflection points at 0.8 for MASLD and 1.2 for advanced liver fibrosis. Additionally, significant interactions were observed between MASLD and covariates such as gender, smoking status, chronic kidney disease (CKD), and cancer. Similarly, the hs-CRP/HDL-C index exhibited positive correlations with advanced liver fibrosis across diverse subgroups, with notable interactions related to cancer. MASLD and advanced liver fibrosis were associated with hs-CRP/HDL-C index, indicating its potential utility as a clinical marker for these conditions.

The association between eight complete blood count-derived inflammatory markers and muscle health

BackgroundMost studies have evaluated sarcopenia and muscle health solely based on muscle mass. This study comprehensively examined the associations between eight inflammatory indicators and muscle mass and strength, with the aim of identifying an indicator capable of evaluating muscle health across multiple dimensions.MethodsThis study included 10,440 participants from the National Health and Nutrition Examination Survey (NHANES, 2011–2018) and 5,384 participants from NHANES (2011–2014). Multivariate logistic regression, smooth curve fitting, restricted cubic spline (RCS) analysis, subgroup analysis, and Spearman's correlation were used to comprehensively assess the associations between the eight inflammatory indicators and muscle mass and strength. Receiver operating characteristic (ROC) curves were used to compare the predictive abilities of the different indices for low muscle mass and muscle strength. Additionally, NHANES data were cross-validated with data from 554 patients at our hospital to evaluate the ability of the systemic immune inflammatory index (SII) to distinguish between low muscle mass and strength.ResultsAfter controlling for all potential confounding factors, multiple logistic regression analysis revealed that apart from the platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and derived NLR (dNLR), the neutrophil-to-monocyte-plus-lymphocyte ratio (NMLR), neutrophil-to-lymphocyte ratio (NLR), SII, systemic inflammation response index (SIRI), and pan-immune-inflammation value (PIV) were significantly negatively correlated with muscle mass and strength. However, NMLR and NLR were significantly associated with changes in muscle mass only in Q4 (P &amp;lt; 0.05). In the stratified analysis by body mass index (BMI), only the SII, NLR, and NMLR were unaffected by BMI. In the cross-validation, the predictive performance of the SII for low muscle mass [area under the curve (AUC) = 0.699, 0.677, and 0.685] and low muscle strength (AUC = 0.857, 0.849, and 0.840) demonstrated a good reference value. RCS and smooth curve fitting analyses indicated that most inflammatory markers were linearly correlated with muscle health (P &amp;lt; 0.05).ConclusionCompared with other inflammatory markers (e.g., PIV and dNLR), the SII demonstrated a more robust predictive ability, was less influence by covariates, and exhibited high generalization performance in internal and external validation. SII may be crucial in identifying “hidden sarcopenia” and the early stages of muscle functional decline.

Blood lead levels and bladder cancer among US participants: NHANES 1999–2018

Background and objectivesPb (lead) is a heavy metal, its carcinogenicity for bladder cancer is still debated, the link between blood lead levels (BLLs) and bladder cancer was investigated in this study.MethodsThis cross-sectional study, using the NHANES (1999–2018) database, explored the relationship between BLLs and bladder cancer among Americans aged 20–85. It employed weighted multivariable logistic regression for analysis. Additionally, subgroup analyses and smoothed curve fitting were also performed.ResultsThis study included a total of 40,486 participants, the body mass index (BMI) of the participants is 28.71 ± 6.68 kg/m2. The average BLL is 0.0858 μmol/L (range: 0—2.96 μmol/L). A fully adjusted model showed that the BLL was associated with bladder cancer (odds ratio [OR] = 2.946, 95% confidence interval [CI] = 1.025 to 8.465, P = 0.047) in people with BMI < 28 kg/m2. However, no difference was found in the BMI ≥ 28 kg/m2 subgroup or in the general population. According to the subgroup analysis of participants with a BMI < 28 kg/m2, blood lead was associated with bladder cancer in the male, nonhypertensive, and < 70-year-old subgroups (p < 0.05) but no significantly different is observed in other subgroups. In addition, we discovered a nonlinear association between the BLLs and bladder cancer risk using a linear regression model.ConclusionIn this cross-sectional study, we found that the degree of correlation between BLLs and the risk of bladder cancer may vary among people with different BMIs. In people with BMI < 28 kg/m2, a higher BLL was independently associated with bladder cancer. However, more experiments are needed to confirm this finding.

Assessing bimodal water retention functions of stony soils using curve fitting and inverse modeling

Assessing bimodal water retention functions of stony soils using curve fitting and inverse modeling

Comparative analysis on the normal vector features of the conventional inverted flame and ultra-lean residual flame

Residual behavior often appears near the flammability limit for lean premixed flames. Insight into it is beneficial to improve the lean premixed combustion performance further. Identifying the normal vector of the residual flame front plays a key role in revealing its structure and evaluating the weights of some main effects quantitatively. For the present residual flame with a high curvature, as the polynomial curve fitting method causes a noticeable error due to the Runge phenomenon, a non-equidistant central difference method is proposed. Subsequently, the normal vectors of the bluff-body stabilized residual flame and conventional inverted flame of 40%H2–60%CH4–air are obtained accurately and their differences are compared quantitatively. It is found that there are significant differences in the normal vector and flow structure features between the conventional inverted flame and residual flame behaviors. The normal vector of the conventional inverted flame always points at the upstream direction. However, the normal vector at the middle section of the residual flame front is almost parallel to the horizontal direction, and it points at the downstream direction next to the residual flame tip. In addition, the flow structure around the residual flame front is revealed. This is the first time the normal vector of the residual flame has been accurately visualized and the difference in normal vector feature between the residual flame and conventional inverted flame revealed. This work provides a universal and accurate method to identify the normal vector of the flame front and new insight into residual flame dynamics.

Relative fat mass (RFM) is linked to testosterone deficiency in adult males

PurposeRelative fat mass (RFM) is a novel obesity assessment metric, and we aim to explore the relationship between RFM and testosterone deficiency in US adult males. MethodsThis study included data from adult males aged 20–59 years from the NHANES 2013–2014 and 2015–2016 cycles. RFM was calculated using a linear equation based on height and waist circumference (WC). Testosterone deficiency was defined as a total serum testosterone level of less than 300 ng/dL. Logistic regression, subgroup analysis, and smooth curve fitting were employed to explore the relationship between RFM and the risk of testosterone deficiency. ResultsThis study included 3243 participants, with 771 diagnosed with testosterone deficiency. Testosterone-deficient individuals exhibited significantly higher RFM levels compared to those with normal testosterone levels (31.23 ± 0.23 vs. 27.16 ± 0.19, P < 0.001). After adjusting for confounding variables, a positive correlation emerged between RFM and testosterone deficiency (OR = 1.16, 95 %CI = 1.11–1.22, P < 0.001). Smooth curve fitting further supported this relationship. Subgroup analysis did not identify any special populations. Receiver operating curve (ROC) analysis results indicated that RFM showed greater effectiveness compared to body mass index (BMI) and WC. ConclusionsElevated RFM levels were found to be linked to the risk of testosterone deficiency. Further studies on RFM hold promise to evaluate and address testosterone deficiency.

Integration of tissue distribution, PK-PD modeling and metabolomics reveals inflammatory-immune response alterations in Gaultheria leucocarpa var. yunnanensis alleviating rheumatoid arthritis.

Gaultheria leucocarpa var. yunnanensis, a distinguished member of the Gaultheria Kalm ex L. in the Ericaceae family, has been traditionally employed in the southwestern regions of China for the efficacious treatment of rheumatoid arthritis (RA). The anti-RA fraction (ARF) derived from Gaultheria leucocarpa var. yunnanensis has been previously demonstrated to effectively alleviate RA in vivo and in vitro. This research endeavor is dedicated to surveying the pharmacokinetic (PK) processes of ARF within plasma and tissues, profiling its metabolites in vivo, discerning the material foundation of its therapeutic efficacy, and delineating its anti-RA mechanisms. The prototype components and metabolites of ARF in plasma and seven tissues of RA rats were analyzed by LC-MSn. Advanced LC-MS/MS and HPLC-DAD methodologies were developed to investigate the plasma PK profiles and tissue distribution characteristics of MSTG-A, MSTG-B, and Gaultherin in both RA model rats and healthy controls. A panel of four cytokines (TNF-α, IL-1, IL-6, and IL-2) was selected as pharmacodynamic (PD) biomarkers and quantified using ELISA. The PK, PD, and PK-PD modeling of ARF were skillfully constructed by combining WinNonlin with Matlab software, enabling a comprehensive analysis of the interrelationships between components and effect markers. A non-targeted plasma metabolomics approach employing LC-QE-MS was utilized to insight into the underlying mechanisms of ARF alleviating RA. The quantity and diversity of identified prototypical components and metabolites of ARF in model rat plasma increased over time. The spleen exhibited the highest number of metabolites and prototypical compounds of ARF. The UPLC-QQQ-MS/MS and HPLC-DAD method were developed and validated for the quantification of three chemical markers in rat plasma and tissues, respectively. Three effective components (MSTG-B, MSTG-A, and Gautherin) demonstrated linear dynamics in plasma and tissues at an oral dosage of 3 g/kg ARF. The PK-PD models involving three components and four inflammatory cytokines aligned with the one company model, demonstrating a linear correlation through compartmental modeling and curve fitting analysis. Significant variations were identified in the concentrations of various amino acids and lipid metabolites among the CON, ARF, and MTX groups in comparison to the MOD group, which are intricately linked to the inflammation-immunity response. The three components displayed favorable bioavailability and were rapidly eliminated in RA rats, collectively exerting an anti-RA effect. The mechanism by which ARF mitigates RA is associated with the modulation of inflammation-immunity related metabolic pathways. The spleen may serve as the target tissue for ARF attenuating RA. These findings provide a robust foundation for rationalizing intervention strategies, elucidating biological mechanisms, and advancing the clinical application of ARF in the amelioration of RA.