Linear Regression Fit Research Articles

Increasing intensity directly increases the perceived warmth of primary colors.

There is a long history of linking the perceptions of temperature and color (the "Hue-heat hypothesis"): red (R) and yellow (Y) are often considered warm, whereas blue (B) and green (G) are cool. Past studies, however, have largely used relatively broad-band light at a fixed intensity to test these relations. We tested whether increasing the intensity of highly saturated primary colors would lead to a concomitant change in the perceived temperature of those colors. 20 young healthy participants (M = 24.80±3.53 years; 45% female; 5% Hispanic; 45% non-White) with normal color vision were tested. An optical system with a Xenon-arc light source, chromatic filters (peak l = 465, 530, 572, 652nm), and a circular neutral density wedge to vary intensity were used (5 intensity levels). Temperature perception was assessed using an ordinal scale from - 5 (coolest) to + 5 (warmest). The order of the colors used and the intensity levels were varied randomly. Considering the average across intensity levels, B (-1.87) and G (+ 1.09) were considered the coolest, whereas Y (+ 2.1) and R (+ 3.75) were considered the warmest colors. All colors, however, warmed with increasing intensity. A linear regression fit to the averaged data across luminance explained the majority of the variance: B (r2 = 0.78), Y (r2 = 0.93), G (r2 = 0.98), and R (r2 = 0.92). Consistent with past data, our results show that color is significantly linked with temperature perception. Increasing the luminance of colors, however, strongly shifts the perception toward increased warmth.

Seismic performance and calculation method for plastic hinge length of RC pier reinforced with UHPC

Piers are highly vulnerable load-bearing components, and their seismic performance determines the integral seismic resistance of bridges to a certain degree. They play crucial roles in evacuation during earthquakes and post-earthquake rescue. The manner in which piers meet the seismic performance requirements after reinforcement has become a popular research topic. In this study, ultra-high-performance concrete (UHPC) and HTRB600E high-tensile reinforcements were used to expand the cross section of a cast-in-place square pier with severe bending damage. The earthquake-resistant behaviour indicators of the pier were compared and analysed by conducting pseudo-static tests on a reinforced concrete pier before and after reinforcement. These indicators included the hysteretic curve, skeleton curve, energy dissipation curve, rigidity degradation, residual displacement, and pier body curvature. Based on the results of the seismic reinforcement quasi-static tests, a finite element model (FEM) of the bridge pier was constructed using the ABAQUS software, and the accuracy of the FEM was averaged. The impact of the reinforcement layer height, thickness, longitudinal strength and axial compression ratio on the equivalent plastic-hinge length of the reinforced pier was analysed, and the formula for the equivalent plastic-hinge length of the reinforced pier was obtained based on multiple linear regression fitting. The analysis results demonstrated that the broadened section method, utilising UHPC and high-tensile reinforcement, significantly enhanced the flexural capacity, energy dissipation, and first rigidity of the bridge pier. The earthquake-resistant behaviour of pier was effectively restored and improved, and the seismic reinforcement effect was significant. The equivalent plastic hinge length of the pier after reinforcement is proportional to the height of the reinforcement layer, the thickness of the reinforcement layer, the strength of the longitudinal reinforcement, and inversely proportional to the axial compression ratio.

U-shaped Association Between Weight-Adjusted-Waist Index and Arterial Stiffness Among Adult Hypertensive Patients: A Population-Based Study in the United States.

The weight-adjusted-waist index (WWI) is an innovative measure of obesity that appears to surpass body mass index (BMI) in assessing lean body mass and fat mass. This study aimed to evaluate the relationship between WWI and AS in hypertensive adults in the United States. The study included 9753 adults diagnosed with hypertension from the National Health and Nutrition Examination Survey (NHANES), which spanned the years 2007-2016. WWI was calculated by dividing waist circumference (in cm) by the square root of body weight (in kg), and arterial stiffness (represented by estimated pulse wave velocity [ePWV]) was analyzed as the outcome. Weighted multiple linear regression and smooth curve fitting were used to test for linear and nonlinear associations. Threshold effects were determined using a two-part linear regression model. Additionally, subgroup analyses and interaction tests were conducted to gain a more in-depth understanding of the observed associations. The mean WWI of the participants was 11.32 ± 0.76. After multivariable adjustment, WWI showed a significant nonlinear association with ePWV, with a U-shaped association observed between the two. Specifically, WWI below the threshold of 10.23 was negatively associated with arterial stiffness (β = -0.39, 95% CI: -0.54 to -0.25), while WWI above the threshold of 10.23 was positively associated with arterial stiffness (β = 0.04, 95% CI: 0.01-0.07). To conclude, the present findings imply that maintaining WWI within an optimal range could reduce AS in hypertensive individuals and potentially decrease cardiovascular risk. However, this observation needs to be confirmed in large clinical trials.

A-332 Identifying At-Risk Patients Pre-IV Contrast Administration via POCT Creatinine Measurement

Abstract Background The use of intravenous iodinated contrast in computerized tomography studies is associated with a small risk of acute kidney injury. Pre-existing chronic kidney disease is a recognized factor and assessment of renal function prior to contrast administration is essential. This study assessed the ability of the Abbott iSTAT creatinine assay to correctly identify IV-contrast patient risk using lab-based eGFR as the gold standard. Methods This was a retrospective study comparing POCT creatinine (whole blood, Abbott iSTAT enzymatic) and lab creatinine (plasma, Beckman Coulter AU5800 Jaffe) results on simultaneous samples collected in the emergency department. Anonymised data records were extracted from the laboratory database for 2020-2023. IV contrast risk was calculated using eGFR (CKD-EPI 2021) and classified as high risk (HR: eGFR < 30 mL/min/1.73 m2), moderate risk (MR: eGFR 30-59) and low risk (LR: eGFR >=60) as per the Royal Australian and New Zealand College of Radiologists 2018 guidelines, using the Beckman-based eGFR as the gold standard. Results 132 paired samples patients were available for analysis (61% male, average age 69 y (23-98), 70% Chinese, eGFR (iStat) 3-143, eGFR (Beckman) 3-121 mL/min/1.73 m2). The proportions of Beckman-based eGFR HR:MR:LR cases were 53:39:40. The prevalence of HR/MR cases was 70%. The diagnostic performance of the iSTAT-based eGFR to accurately identify HR/MR patients was: sensitivity 93.5%, specificity 95%, PPV 97.7%, NPV 86.4%, accuracy 93.9%. For different Beckman-derived eGFR categories, the mean difference in eGFR (iSTAT - Beckman), 95% lower limit of agreement (LOA) and upper LOA was: <30 mL/min/1.73 m2: -1.0, -3.2, -1.1; 30-60 mL/min/1.73 m2: 0.9, -13.3, 15.1; >60 mL/min/1.73 m2: 1.6, -16.8, 20.1. Linear regression fit (Passing-Bablok): CKD-EPI Beckman = 1.193 + 0.9773 CKD-EPI iSTAT. Correlation coefficient was 0.981. Kappa for the 3 categories of risk classification was 0.814. Conclusions The iSTAT creatinine assay could reliably identify patients at medium/high risk of acute kidney injury following intravenous contrast administration. Performance was best for low and high risk patients with 100% of high risk patients being correctly identified. It is a useful screening test but differences in eGFR of up to 20 mL/min/1.73 m2 may be seen between the Beckman and iSTAT eGFR values at higher levels, meaning numeric eGFR results are not interchangeable.

Reduction characteristics and mechanism of mechanically activated iron ore powder by lignin

As a primary constituent of renewable biomass fuel, lignin can be effectively utilized as a reducing agent in the ironmaking process, thereby significantly mitigating CO2 emissions throughout the procedure. This study meticulously evaluates the impact of lignin on the reduction of iron ore powder across diverse levels of mechanical activation through thermogravimetric analysis. It elucidates the intricate reduction mechanism at play. The reduction process is characterized by two pivotal stages: the initial reduction of pyrolysis gases followed by the reduction of fixed carbon, which predominantly drives the transformation of iron ore powder. While mechanical activation exhibits a negligible influence on the first stage, it exerts a pronounced effect on the second. An extended activation time elevates the depth of reduction in the latter stage. Furthermore, the heating rate plays a crucial role in the reduction process, with slower rates favoring the reduction of pyrolysis gases and faster rates boosting carbon fixation reduction. Enhanced activation durations lead to improve linear regression fits for the reduction reaction data. Utilizing the carbon gasification model for iron ore powder treated with 480 min of activation yields a calibration variance of 0.99, with the derived activation energy of 48.75 kJ/mol aligning closely with empirical values. This research provides a thorough analysis of the reduction kinetics and mechanism, underscoring the transformative potential of lignin as a reducer in ironmaking processes, thus contributing to the development of sustainable, low-carbon technologies.

Experimental study of interception effect by submerged dam on microplastics

Submerged dam can alter microplastic (MP) transport, and act as a sink for MPs. In this paper, we investigated the interception rates of Polyvinyl chloride (PVC) and Polystyrene (PS) by an artificial submerged dam in a flow flume at first, and found that most of the un-intercepted PVC and PS particles by the dam accumulated behind it under the subcritical (Fr < 1) and turbulent (Re > 500) flows. PVC particles behind the dam mainly concentrated within two dam widths, and the concentration of PS particles decreased with the distance behind the dam lengthening. Then, we performed linear regression fitting and Redundancy Analysis (RDA) between the interception rates collected in 162 experiment tests and environmental factors, including flow velocity, distance to dam and MP concentration. The results showed that the interception rate of PVC and PS particles increased with the distance to dam lengthening, but decreased with the flow velocity and MP concentration heightening. RDA revealed that the interception rate was influenced by flow velocity, distance to dam, and MP concentration from the most to the least. Our findings are believed to contribute to understanding the mechanism of the interception effect of submerged dam on microplastics.

Di-2-ethylhexyl phthalate (DEHP) exposure increase female infertility

This study explores the relationship between Di-2-ethylhexyl phthalate (DEHP) exposure and female infertility. The analysis included 998 female participants aged between 18 and 44 years. We analyzed data from the National Health and Nutrition Examination Survey (2013–2018) using multiple logistic regression and generalized linear models to assess the impact of DEHP on infertility. Additionally, we employed curve fitting and two-piecewise linear regression models to investigate potential nonlinear correlations, conducting subgroup analyses based on age, BMI, alcohol consumption, smoking status, hypertension, and diabetes. Our results, after adjusting for confounders, revealed a positive association between DEHP exposure and infertility. This association was significant whether DEHP was treated as a continuous variable (odds ratio OR = 1.28, 95 % confidence interval CI: 1.08–1.52, P = 0.0072) or as a categorical variable (P for trend = 0.0038). A non-linear relationship was identified, with an inflection point at − 3.35 (∑DEHP = 0.0981 × 10−9 mol/mg creatinine). Effect sizes were 1.55 (1.01–2.36) on the left side of the inflection point and 0.73 (0.43–1.23) on the right side. Subgroup analysis indicated that the correlation was consistent across stratified variables. In conclusion, our findings suggest a non-linear association between DEHP exposure and female infertility, with a positive correlation within a specific dose range, but no further increase in risk beyond a certain threshold.

Intercomparison of sensible and latent heat flux measurements from combined eddy covariance, energy balance, and Bowen ratio methods above a grassland prairie

We present a comparison of four different methods of measuring sensible (H) and latent (LE) heat fluxes for a year over a mixed grass prairie ecosystem in the Nebraska SandHills [eddy covariance (EC), energy balance/Bowen ratio (EBBR), residual energy (RES), modified Bowen ratio (MBR) methods]. Additionally, we developed a set of quality control criteria for each method and present a simplification to the traditional EBBR setup. Using EC as reference, all methods yielded similar estimates of yearly H (regression slopes (m) ~ 2% from unity; HEC > HEBBR, HRES, and HMBR). For yearly LE, EBBR and RES yielded similar estimates with EC (m ~ 2% from unity; LEEC < LEEBBR and LERES), while a larger bias was found from MBR (m ~ 8% from unity; LEEC > LEMBR). At shorter time scales (~ hourly), moderate scatter was found about linear regression fits for H between EBBR and EC (R2 = 0.81), with smaller scatter between RES and MBR, and EC (R2 = 0.91). For LE, smaller scatter was also measured between EC, and EBBR and RES (R2 = 0.89 and 0.87, respectively), with the larger scatter between EC and MBR (R2 = 0.65). This suggests methods other than EC may be well suited to longer-term applications (≥ yearly), but have larger uncertainty on individual measurements.

Cardiometabolic index is associated with increased bone mineral density: a population-based cross-sectional study.

Osteoporosis is a multifactorial bone disease in which lipid metabolism plays an important role. Bone Mineral Density (BMD) measured by Dual-energy X-ray Absorptiometry (DXA) is a critical indicator for diagnosing osteoporosis. The cardiometabolic index (CMI) is a novel metric that combines two quantitative indicators of blood lipids-triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C). This study explores the association between CMI and BMD and seeks to elucidate the role of lipid metabolism in the context of bone health. Based on the data of the National Health and Nutrition Examination Survey (NHANES) 2017-March 2020-pre-pandemic, weighted multiple linear regression and smooth curve fitting were used to study the relationship between CMI and femoral BMD. Stratified analyses were also conducted for age, gender, BMI, ethnicity, diabetes and hypertension status. And, the saturation threshold effect of CMI was further analyzed using a two-stage linear regression model. This study enrolled a total of 1,650 participants (48.7% males), with an average age of 63.0 ± 8.6 years. After adjusting for multiple confounding factors, CMI was positively correlated with total femur BMD, trochanter BMD, and intertrochanter BMD, while the correlation with femur neck BMD was not statistically significant. In the fully adjusted model, each unit increase in CMI was associated with a 0.026 (g/cm2) increase in total femur BMD, a 0.022 (g/cm2) increase in trochanter BMD, and a 0.034 (g/cm2) increase in intertrochanter BMD. Subjects in the highest quartile of CMI had a 0.034 (g/cm2) increase in total femur BMD, a 0.035 (g/cm2) increase in trochanter BMD, and a 0.039 (g/cm2) increase in intertrochanter BMD in the fully-adjusted model compared to those in the lowest quartile. In addition, saturation was observed between CMI and total femur BMD, trochanter BMD and intertrochanter BMD, with saturation thresholds of 1.073, 1.431 and 1.073, respectively. CMI is strongly associated with BMD, indicating its potential relevance in bone metabolism. However, the role of CMI in the context of bone health, especially regarding osteoporosis risk, requires further investigation in large-scale prospective studies.

Associations between life's essential 8 and femoral neck bone mineral density among adults: A national population-based study.

Osteoporosis represents a significant public health issue, impacting both health outcomes and economic costs. This research investigates how cardiovascular health, as indicated by the LE8 score, correlates with bone mineral density (BMD). Data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018 were analyzed in this cross-sectional analysis, including 9018 subjects following the exclusion of individuals lacking BMD or LE8 data. The LE8 score, comprising factors such as diet, physical activity, smoking status, sleep quality, body mass index, lipid profiles, blood glucose, and blood pressure, was used to evaluate cardiovascular health. BMD was determined through dual-energy X-ray absorptiometry (DXA). Relationships between the LE8 scores and BMD at the femoral neck were assessed using linear regression and smooth curve fitting techniques. Enhanced LE8 scores were linked to improved BMD at the femoral neck. Notably, a 10-point increment in the LE8 score was associated with a rise in BMD by 0.04 g/cm² [β = 0.04, 95% CI: 0.03-0.05]. The data indicate a strong positive association between cardiovascular health, as measured by LE8, and BMD. These results support the development of holistic health strategies that promote cardiovascular health to potentially improve bone density.

Validation of a Demography-Based Adaptive QTc Formula using Pediatric and Adult Datasets Acquired from Humans and Guinea Pigs.

A variety of QT rate-correction (QTc) formulae have been utilized for both clinical and research purposes. However, these formulae are not universally effective, likely due to significant influences of demographic diversity on the QT-HR relationship. To address this limitation, we proposed an adaptive QTc (QTcAd) formula that adjusts to subject demographics (i.e., age). Further, we compared the efficacy and accuracy of the QTcAd formula to other widely used alternatives. Using age as a demographic parameter, we tested the QTcAd formula across diverse age groups with different heart rates (HR) in both humans and guinea pigs. Utilizing retrospective human (n=1360) and guinea pig electrocardiogram (ECG) data from in-vivo (n=55) and ex-vivo (n=66) settings, we evaluated the formula's effectiveness. Linear regression fit parameters of HR-QTc (slope and R²) were utilized for performance assessment. To evaluate the accuracy of the predicted QTc, we acquired epicardial electrical and optical voltage data from Langendorff-perfused guinea pig hearts. In both human subjects and guinea pigs, the QTcAd formula consistently outperformed other formulae across all age groups. For instance, in a 20-year-old human group (n=300), the QTcAd formula successfully nullified the inverse HR-QT relationship (R²=5.1E-09, slope=-3.5E-05), while the Bazett formula (QTcB) failed to achieve comparable effectiveness (R²= 0.20, slope=0.91). Moreover, the QTcAd formula exhibited better accuracy than the age-specific Benatar formula (QTcBe), which overcorrected QTc (1-week human QT: 263.8±14.8 ms, QTcAd: 263.8±7.3 ms, p=0.62; QTcBe: 422.5±7.3 ms, p<0.0001). The optically measured pseudo-QT interval (143±22.5 ms, n=44) was better approximated by QTcAd (180.6±17.0 ms) compared to all other formulae. Furthermore, we demonstrated that the QTcAd formula was not inferior to individual-specific QTc formulae. The demography-based QTcAd formula showed superior performance across human and guinea pig age groups, which may enhance the efficacy of QTc for cardiovascular disease diagnosis, risk stratification, and drug safety testing. Corrected QT (QTc) is a well-known ECG biomarker for cardiovascular disease risk stratification and drug safety testing. Various QT rate-correction formulae have been developed, but these formulae do not perform consistently across diverse datasets (e.g., sex, age, disease, species). We introduce a novel QTc formula (QTcAd) that adapts to demographic variability, as the parameters can be modified based on the characteristics of the study population. The formula (QTcAd = QT + (|m|*(HR-HR mean )) - includes the absolute slope (m) of the linear regression of QT and heart rate (HR) and the mean HR of the population (HR mean ) as population characteristics parametersˍUsing datasets from both pediatric and adult human subjects and an animal model, we demonstrate that the QTcAd formula is more effective at eliminating the QT-HR inverse relationship, as compared to other commonly used correction formulae.

Past, present and future changes in the annual streamflow of the Lancang-Mekong River and their driving mechanisms

The rapid development of the Greater Mekong Subregion (GMS) makes it essential to understand the major mechanisms controlling the streamflow, especially for the Lancang-Mekong River (abbr. Mekong River). We used instrumental annual streamflow data (1960–2007) from Chiang Saen hydrological station and several gridded hydroclimatic datasets to explore the hydroclimatic evolution of the Mekong River, together with its driving mechanisms. We found that changes in the Mekong streamflow are consistent with precipitation changes, and the Mekong is thus a precipitation-dominated river that is susceptible to the effects of ongoing climate change. The instrumental record of Mekong annual streamflow is closely related to hydroclimatic changes, especially those related to moisture, within the area from the Hengduan Mountains to the Chiang Saen Station. Based on these gridded records, we extended the Mekong annual streamflow record to cover 1891–2021 using nested multiple linear regression fitting. The fitted streamflow explained up to 57.6 % of the instrumental changes and it indicates that the major 2019 drought was not unique over the past century. Despite extremely low precipitation and high temperatures, it is likely that the effects of drought can be mitigated via hydraulic engineering regulation. Climatological analyses showed that the Mekong annual streamflow is driven by the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), which is consistent with observed quasi-interannual cycles of 3–4 years. A multi-model ensemble of CMIP6 revealed that the Mekong annual streamflow will experience an upward trend in the future, accompanied by the more extreme impacts of ENSO and the IOD.

Parameter estimation of epoxy resin cure kinetics by dynamics DSC data

AbstractThis study focused on determining the curing kinetic parameters of amine‐epoxy resin by performing dynamic DSC tests. The Kissinger and Crane equations were used to determine the activation energy, the pre‐exponential factor, and the reaction order as kinetic parameters for curing. The Ozawa equation was also used to determine the activation energy that changes at different levels of cure during the reaction. The average activation energy obtained by the Ozawa method was compared with the Kissinger activation energy. In addition, the T‐β extrapolation method was used to determine the optimum curing temperature. The kinetic parameters obtained from the Kissinger and Crane equations were used in the nth‐order kinetic model to predict the degree of cure at a given time and temperature. The linear regression fitting method was used in Minitab software to determine the curing parameters. The results were evaluated based on the fitting parameters. This study provides a theoretical basis for the curing mechanisms of epoxy matrix fiber composites used in the manufacture of wind turbine blades.

Inclusivity of thermal performance parameters for evaluation of solar cookers and the necessity of uniformity in the appraisal using generalized test procedure for different designs

Solar cookers play a vital role in decentralized energy solutions. Therefore, their appropriate rating is essential. The present work reviews and emphasizes the usefulness of thermal performance parameters (TPPs) for assessing solar cookers, such as box type, parabolic dish, panel type, Fresnel lens-based, and their hybrids. Although the TPPs are extensively used for testing solar cookers, several research studies depicted ambiguities, non-uniformities, and inconsistencies in their use. Interestingly, Cooker Opto-Thermal Ratio (COR) is one of the most generalized and, hence, useful TPP for the optical and thermal performance evaluation and rating/grading of multiple designs of solar cookers. In view of non-uniformities and inconsistencies found in determining TPPs, current work provides crucial insights into the existing TPPs, including COR, corresponding test standards/protocols, and quantification of test load(s) for solar cookers. Also, this work justifies the appropriate use of the different TPPs for solar cookers, and the usefulness and robustness of COR determined using linear regression fit of experimental data and derivate COR-dependent objective parameters. Finally, it includes insightful information for researchers, designers, and manufacturers on the future research pathways based on COR and corresponding test procedure and provide useful visions to avoid its deceptive, inconsistent, and inappropriate use.

Decomposing PM2.5 concentrations in urban environments into meaningful factors 2. Extracting the contribution of traffic-related exhaust emissions

Vehicle-emitted fine particulate matter (PM2.5) has been associated with significant health outcomes and environmental risks. This study estimates the contribution of traffic-related exhaust emissions (TREE) to observed PM2.5 using a novel factorization framework. Specifically, co-measured nitrogen oxides (NOx) concentrations served as a marker of vehicle-tailpipe emissions and were integrated into the optimization of a Non-negative Matrix Factorization (NMF) analysis to guide the factor extraction. The novel TREE-NMF approach was applied to long-term (2012–2019) PM2.5 observations from air quality monitoring (AQM) stations in two urban areas. The extracted TREE factor was evaluated against co-measured black carbon (BC) and PM2.5 species to which the TREE-NMF optimization was blind. The contribution of the TREE factor to the observed PM2.5 concentrations at an AQM station from the first location showed close agreement (R2=0.79) with monitored BC data. In the second location, a comparison of the extracted TREE factor with measurements at a nearby Surface PARTiculate mAtter Network (SPARTAN) station revealed moderate correlations with PM2.5 species commonly associated with fuel combustion, and a good linear regression fit with measured equivalent BC concentrations. The estimated concentrations of the TREE factor at the second location accounted for 7–11 % of the observed PM2.5 in the AQM stations. Moreover, analysis of specific days known to be characterized by little traffic emissions suggested that approximately 60–78 % of the traffic-related PM2.5 concentrations could be attributed to particulate traffic-exhaust emissions. The methodology applied in this study holds great potential in areas with limited monitoring of PM2.5 speciation, in particular BC, and its results could be valuable for both future environmental health research, regional radiative forcing estimates, and promulgation of tailored regulations for traffic-related air pollution abatement.

Exploring the link: Systemic immune-inflammation index as a marker in endometriosis—Insights from the NHANES 2001–2006 cross-sectional study

Objective The systemic immuno-inflammatory index (SII), a novel immune marker of inflammation, has not been previously associated with endometriosis. The objective of this research is to explore the link between SII and the occurrence of endometriosis. Methods Utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 2001 to 2006, we screened and extracted relevant information from the population. Participants missing data on either SII or endometriosis were excluded. We divided the remaining cohort into quartiles based on SII levels: Q1 (SII &lt; 249, n = 848), Q2 (249 ≤ SII &lt; 604.55, n = 847), Q3 (604.55 ≤ SII &lt; 825.35, n = 847), and Q4 (SII ≥ 852.35, n = 848). Multiple linear regression and smooth curve fitting techniques, were to evaluate the non-linear association between SII and endometriosis. Results The study included 3,390 adults aged 20 to 55. Multiple linear regression analysis revealed a significant positive correlation between SII and endometriosis [3.14, 95% CI (2.22, 4.45), P &lt; 0.01]. This correlation was consistent across subgroups defined by marital status, poverty income ratio, BMI, alcohol consumption, and age at first menstrual period. However, the relationship between SII and endometriosis was significantly modified by age, education, and history of pregnancy in the stratified analyses. The curve fitting indicated an S-shaped curve, with an inflection point at SII = 1105.76. Conclusion The SII may serve as a predictive marker for endometriosis risk among women in the United States, offering a potentially simple and cost-effective approach. However, given the cross-sectional design of this investigation, further validation in prospective studies is necessary.

Vitamin D and Cognitive Performance in Older Adults: A Cross-Sectional and Mendelian Randomization Study.

Cognitive decline is a prevalent health problem in older adults, and effective treatments remain to be produced. Serum vitamin D, a commonly used biochemical marker, is widely recognized as an indicator of various diseases. Existing research has not fully elucidated the relationship between vitamin D and cognitive function. The aim of this study is to investigate the real relationship between vitamin D and cognitive function and to identify indicators that have a strong predictive effect on cognitive decline. At first, we used the dataset of the genome-wide association studies studying vitamin D and cognitive performance to conduct Mendelian randomization analysis. Subsequently, we employed linear regression and smooth curve fitting methods to assess the relationship using the National Health and Nutrition Examination Survey data. Finally, we investigated other predictive features of cognitive performance utilizing a machine learning model. We found that a 1-unit increase in vitamin D is associated with a 6.51% reduction (P < .001) in the risk of cognitive decline. The correlation between vitamin D and cognitive performance is nonlinear, with the inflection point at 79.9 nmol/L (left: β = 0.043, P < .001; right: β = -0.007, P = .420). In machine learning, the top 5 predictors are vitamin D, weight, height, age, and body mass index. There is a causal relationship between vitamin D and cognitive performance. 79.9 nmol/L could be the optimal dose for vitamin D supplementation in the elderly. Further consideration of other factors in vitamin D interventions is necessary.

Thermodynamic performance of SiC-enhanced MicroPCM backfill based on response surface methodology

The functional backfilling in mining achieves synergistic co-mining of deep-earth deposits-geothermal, and the development of functional filling materials with suitable phase change parameters and excellent physicochemical properties is imminent. This study aims to investigate the optimal composition of phase change energy storage backfill material based on MicroPCM. To address the issues of reduced compressive strength and specific heat capacity of MicroPCM-backfill, silicon carbide (SiC) is introduced to prepare MPSC-backfill. Box-Behnken Design (BBD) is proposed to design and analyze according to four factors (ash-sand ratio, slurry concentration, MicroPCM, SiC), three levels (compressive strength, thermal conductivity, specific heat capacity) and three center points. Based on the Response Surface Methodology, the multivariate quadratic polynomial model was used to perform multiple linear regression and binomial fitting analysis to explore the optimal ratio. Combined with SEM-EDS (Scanning Electron Microscope with Energy-Dispersive X-ray Spectroscopy) analysis, the following conclusions were drawn. SiC exhibits an overall enhancement of the compressive strength of the backfill, and the thermal conductivity tends to increase almost linearly. The specific heat capacity grows in a small amount of silicon carbide doping, but excessive amounts lead to a decrease, with an overall limited impact. The addition of SiC does not affect the phase change ability of MicroPCM. And within a certain range of added quantities, it optimizes specific heat capacity, thermal conductivity, and compressive strength. Experimental validation based on the obtained optimal composition shows errors within a 5% margin, indicating the response model's good accuracy and predictability. High and low-temperature cyclic tests confirm the long-term thermal energy storage stability of MPSC-backfill during phase change cycles.

Association between family income to poverty ratio and nocturia in adults aged 20 years and older: A study from NHANES 2005-2010.

Nocturia, the most common lower urinary tract symptom (LUTS), significantly impacts socioeconomic factors and individuals' quality of life and is closely related to many diseases. This study utilized data from NHANES 2005-2010 to explore the relationship between family income to poverty ratio (PIR) and the presence of nocturia symptoms in adults aged 20 or older in the United States. Data from the National Health and Nutrition Examination Survey (NHANES) in 2005-2010, including 6,662 adults aged 20 or older, were utilized for this cross-sectional study. The baseline data was used to display the distribution of each characteristic visually. Multiple linear regression and smooth curve fitting were used to study the linear and non-linear correlations between PIR and nocturia. Subgroup analysis and interaction tests were conducted to examine the stability of intergroup relationships. Out of the 6,662 adult participants aged 20 or older, 1,300 households were categorized as living in poverty, 3,671 households had a moderate income, and 1,691 households were classified as affluent. Among these participants, 3,139 individuals experienced nocturia, representing 47.12% of the total, while 3,523 individuals were nocturia-free, constituting 52.88% of the total population. After adjusting for all other covariates, it was found that PIR was significantly negatively correlated with nocturia (OR: 0.875, 95%CI: 0.836-0.916 P<0.0001). This trend persisted when PIR was divided into three groups (PIR <1, PIR 1-4, PIR > 4) or quartiles. There was a non-linear negative correlation between PIR and nocturia. Our findings indicated that lower PlR was associated with a higher risk of nocturia in adults aged 20 or older in the United States. These findings highlight the importance of considering socioeconomic factors in preventing and managing nocturia. Nonetheless, further exploration of the causal nexus between these factors was precluded due to the constraints of a cross-sectional design.

Autonomous Tumor Signature Extraction Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study.

Accurate, reliable, non-invasive assessment of patients diagnosed with prostate cancer is essential for proper disease management. Quantitative assessment of multi-parametric MRI, such as through artificial intelligence or spectral/statistical approaches, can provide a non-invasive objective determination of the prostate tumor aggressiveness without side effects or potential poor sampling from needle biopsy or overdiagnosis from prostate serum antigen measurements. To simplify and expedite prostate tumor evaluation, this study examined the efficacy of autonomously extracting tumor spectral signatures for spectral/statistical algorithms for spatially registered bi-parametric MRI. Spatially registered hypercubes were digitally constructed by resizing, translating, and cropping from the image sequences (Apparent Diffusion Coefficient (ADC), High B-value, T2) from 42 consecutive patients in the bi-parametric MRI PI-CAI dataset. Prostate cancer blobs exceeded a threshold applied to the registered set from normalizing the registered set into an image that maximizes High B-value, but minimizes the ADC and T2 images, appearing "green" in the color composite. Clinically significant blobs were selected based on size, average normalized green value, sliding window statistics within a blob, and position within the hypercube. The center of mass and maximized sliding window statistics within the blobs identified voxels associated with tumor signatures. We used correlation coefficients (R) and p-values, to evaluate the linear regression fits of the z-score and SCR (with processed covariance matrix) to tumor aggressiveness, as well as Area Under the Curves (AUC) for Receiver Operator Curves (ROC) from logistic probability fits to clinically significant prostate cancer. The highest R (R > 0.45), AUC (>0.90), and lowest p-values (<0.01) were achieved using z-score and modified registration applied to the covariance matrix and tumor signatures selected from the "greenest" parts from the selected blob. The first autonomous tumor signature applied to spatially registered bi-parametric MRI shows promise for determining prostate tumor aggressiveness.