Best-fit Equation Research Articles

Portable X-ray fluorescence of zinc and selenium with nail clippings-Mother and Infant Nutrition Investigation (MINI).

Zinc and selenium are essential minerals for human nutrition. Reliable biomarkers of zinc status and selenium status in humans are therefore important. This work investigates a novel portable X-ray fluorescence (XRF) method with the ability to rapidly assess zinc and selenium in nail clippings. This approach used a mono-energetic X-ray beam to excite characteristic X-rays from the clippings. Nail clippings were obtained from the Mother and Infant Nutrition Investigation (MINI), a study designed to assess nutrition in a population of women and their breastfed children in New Zealand. Twenty mother-infant pairings were selected to provide nail clippings at two time points (visit 1 at 3 months postpartum; visit 2 at 6 months postpartum). Nail clippings from each mother-infant pairing were divided into three groupings of clippings prior to analysis: those obtained from a big toe of the mother, those from the other toes of the mother, and those from the toes and fingers of the infant. Clippings were prepared and mounted prior to XRF measurement, providing four distinct fragments from each clipping grouping. These fragments were assessed by XRF using a measurement time of either 300 s (visit 1) or 180 s (visit 2). XRF results were determined through both an automated system output and an analysis of the X-ray energy spectrum. Following this assessment of zinc and selenium with the non-destructive XRF method, clippings were measured for zinc and selenium concentration using a "gold standard" technique of inductively coupled plasma mass spectrometry (ICP-MS). Mean ICP-MS concentrations ranged from 122 μg/g to 127 μg/g for zinc, and from 0.646 μg/g to 0.659 μg/g for selenium. Precision, assessed by a relative standard deviation of measurement, was superior for ICP-MS relative to XRF. For both zinc and selenium, XRF results were compared with ICP-MS concentrations. Linear equations of best fit were determined for each comparison between XRF and ICP-MS results. Coefficients of determination (r2) were stronger for zinc (from 0.74 to 0.95) than selenium (from 0.53 to 0.70). A decrease in XRF measurement time from 300 s to 180 s did not appear to adversely affect the correlation between XRF and ICP-MS results. Using the mono-energetic portable XRF method, the correlation of XRF zinc results with ICP-MS zinc concentrations was improved over previous findings, and selenium measurement was reported for the first time. The method may prove useful for future applications to trace element analysis using nail clippings as a biomarker.

Constructing and Validating Estimation Models for Individual-Tree Aboveground Biomass of Salix suchowensis in China

Biomass serves as a crucial indicator of plant productivity, and the development of biomass models has become an efficient way for estimating tree biomass production rapidly and accurately. This study aimed to develop a rapid and accurate model to estimate the individual aboveground biomass of Salix suchowensis. Growth parameters, including plant height (PH), ground diameter (GD), number of first branches (NFB), number of second branches (NSB) and aboveground fresh biomass weight (FW), were measured from 892 destructive sample trees. Correlation analysis indicated that GD had higher positive correlations with FW than PH, NFB and NSB. According to the biological features and field observations of S. suchowensis, the samples were classified into three categories: single-stemmed type, first-branched type and second-branched type. Based on the field measurement data, regression models were constructed separately between FW and each growth trait (PH, GD, NFB and NSB) using linear and nonlinear regression functions (linear, exponential and power). Then, multiple power regression and multiple linear regression were conducted to estimate the fresh biomass of three types of S. suchowensis. For the single-stemmed plant type, model M1 with GD as the single parameter had the highest adj R2, outperforming the other models. Among the 16 constructed biomass-estimating equations for the first-branched plant type, model M32 FW = 0.010371 × PH1.15862 × GD1.250581 × NFB0.190707 was found to have the best fit, with the highest coefficient of determination (adj R2 = 0.6627) and lowest Akaike Information Criterion (AIC = 5997.3081). When it comes to the second-branched plant type, the best-fitting equation was proved to be the multiple power model M43 with PH, GD, NFB and NSB as parameters, which had the highest adj R2 value and best-fitting effect. The stability and reliability of the models were confirmed by the F-test, repeated k-fold cross-validation and paired-sample t-tests. The models developed in this study could provide efficient tools for accurately estimating the total aboveground biomass for S. suchowensis at individual tree levels. The results of this study could also be useful for optimizing the economic productivity of shrub willow plantations.

Development of Allometric Equations to Determine the Biomass of Plant Components and the Total Storage of Carbon Dioxide in Young Mediterranean Argan Trees

Morocco’s argan trees, native to forests, are now cultivated in large orchards within the Argan Biosphere Reserve, transforming “Arganiculture”. These orchards are anticipated to bolster carbon storage, but their precise contribution to carbon storage remains unclear. This study introduces for the first time allometric equations for estimating biomass in different components of argan plants within orchards. A total of 89 plant individuals, aged 2 to 6 years, were collected. Their diameter and total height were measured. The biomass, carbon content, and biomass carbon stock of each component were determined. The best-fit allometric equation incorporates diameter, height, growing years, and root-to-shoot ratio to estimate total biomass (R2 = 0.95). The estimated total carbon biomass stock ranged from 0.01 to 0.82 t CO2 ha−1 for plants, at a density of 200 plants ha−1. Between 2021 and 2023, the average annual carbon sequestration was 0.20 t CO2 ha−1 year−1. This model offers valuable tools for use when species-specific equations during the establishment growing stage are unavailable, enhancing carbon sequestration quantification for more reliable results and informing climate change mitigation strategies. The allometric parameters serve as benchmarks for trees resembling the argan tree. The methodology could be adapted for other forest plants undergoing conversion to orchard cultivation.

Statistical analysis of earth observing data for physicochemical water quality parameters estimation for Lake Beseka, Northern main Ethiopian rift, Ethiopia

ABSTRACT Water quality deterioration in the Main Ethiopian Rift Lakes is one of the problems affecting the health and socioeconomic development of the area. This study was aimed to develop a method to assess the water quality change of Lake Beseka using satellite image reflectance data and observed data. Multi-temporal Landsat imagery and three variables were used to assess the physicochemical environment: pH, EC, and TDS. Linear regression and correlation were accomplished between observed water quality parameters and surface reflectance of different band operations. The best-fitted linear regression equation for pH was found on SWIR1 while for EC and TDS, the blue/green band ratio was highly fitted. The Pearson coefficients of correlation for pH, EC, and TDS were − 0.79, 0.86, and 0.85, respectively. The RMSE and p-value for validation analysis were 0.25/0.005, 548/0.003, and 367/0.004 for pH, EC, and TDS, respectively. The estimated pH, EC, and TDS were higher in the central portion of the lake grouped under brackish water and lower in the southwestern, southern, and northeastern shores. The estimated EC and TDS for the years 2018 and 2021 were relatively lower than in 2007 and 2023. The spatiotemporal lake water variations were due to anthropogenic and geogenic factors including hot springs and groundwater discharge to the lake, water-level rise and depth variation, and evaporation. These findings are helpful for understanding linear regression equations that developed from surface reflectance and observed data, which are essential to estimating and monitoring water quality change in a cost-effective and time-saving manner.

Over the Past Decade, Preoperative Anemia Has Become a Greater Predictor of Transfusions After Total Knee Arthroplasty

BackgroundWith advancements in perioperative blood management and the use of tranexamic acid, the rate of transfusions after total knee arthroplasty (TKA) has substantially decreased. As these principles are refined, other modifiable risk factors, such as preoperative anemia, may play an increasingly important role in transfusion risk for patients undergoing TKA. MethodsA multicenter, national database was utilized to identify patients undergoing TKA from 2010 to 2021. Anemia was defined by World Health Organization definitions as < 12 g/dL for women and < 13 g/dL for men. A predictive model was created using backwards elimination logistic regression to predict transfusion risk, controlling for demographic and medical covariates. The coefficient of anemia was then analyzed for each year. The trend over time was fitted with a best-fit linear regression equation. ResultsThere were 509,117 patients who underwent TKA, and had a mean age of 67 years (range, 18 to 89). There were 57,716 (11%) patients who were anemic preoperatively, and 15,426 (3%) of patients required a transfusion. Rate of transfusion decreased from 10.6% in 2010 to 0.6% in 2021. The odds ratio associated with anemia as a predictor of transfusion increased from 3.1 (95% confidence interval: 2.1 to 4.6) in 2010 to 14.0 (95% confidence interval: 8.9 to 24) in 2021. ConclusionsThe results of this study demonstrate that the importance of preoperative anemia as a predictor of transfusion has increased over the past decade as rates of transfusion have decreased. As perioperative blood management protocols improve, preoperative anemia should be considered an important focus of intervention to reduce the risk of transfusion prior to TKA. Level of EvidenceIII.

A preliminary study on the normal values of the thoracic Haller index in children.

The Haller index (HI) is widely utilized as a quantitative indicator to assess the extent of the pectus excavatum (PE) deformity, which is the most common chest wall abnormality in children. Both preoperative correction planning and postoperative follow-up need to be based on the standard of normal thoracic growth and development. However, there is currently no established reference range for the HI in children. Consequently, the goal of this study was to conduct a preliminary investigation of normal HI values among children to understand thoracic developmental characteristics. Chest computed tomography images obtained from January 2012 to March 2022 were randomly selected from the imaging system of the Children's Hospital of Chongqing Medical University. We divided the images of children into a total of 19 groups: aged 0-3 months (1 group), 4-12 months (1 group) and 1 year to 17 years (17 groups), with 50 males and 50 females, totaling 100 children in each group. HI was measured in the plane where the lowest point of the anterior thoracic wall was located and statistically analysed using SPSS 26.0 software. A total of 1900 patients were included in the study. Our results showed that HI, transverse diameter and anterior-posterior diameter were positively correlated with age (P < 0.05). Using age as the independent variable and HI as the dependent variable, the best-fit regression equations were HI-male = 2.047 * Age0.054(R2 = 0.276, P<0.0001) and HI-female = 2.045 * Age0.067(R2 = 0.398, P<0.0001). Males had significantly larger thoracic diameters than females, and there was little difference in the HI between the 2 sexes. The HI rapidly increases during the neonatal period, slowly increases during infancy and stops increasing during puberty, with no significant differences between the sexes.

Atom pair bond approach: an efficient method for determining the lattice parameters of NiAs-type compounds and comparative analysis with computational databases

Comparison of EOS properties such as lattice parameters, bulk modulus, etc calculated by density functional theory (DFT) with experiments is used, in general, to assess the precision reachable in computations, when using different codes and potentials. DFT calculations using a large number of codes and potentials by different groups, have reported excellent precision (0.02 Å) in the lattice parameters of 71 elements. It is of interest to study the precision levels reachable in compounds of hexagonal NiAs type crystal structure, in which a wide range of electrical conductivity and magnetic order are found to occur. In this study, lattice parameters for 42 intermetallic compounds of the NiAs type structure are determined from internal radii using the Atom Pair Bond method. These values are compared with the lattice parameters reported from the high throughput DFT computational techniques such as AFLOW and Materials Project compilations. Precision in lattice parameters obtainable in the three methods is assessed in comparison with those reported from the experiments. Selection of a set of compounds of same crystal structure brings out the role of differences in the electronic structure of elements involved. In the APB method, lattice parameters are obtained by the best-fit equations defined by radii change in a large number of compounds with a particular structure, and do not involve several approximations, unlike in DFT. It is interesting to see that the simple APB approach could estimate lattice parameters with accuracies comparable to DFT methods.

An initial production assessment of oil and gas in a specific field was carried out using nodal analysis and decline curve analysis

Global petroleum consumption is on the rise, and conventional production from reservoirs is struggling to meet this increasing demand. As a result, it becomes imperative to exploit non-traditional resources. Unconventional resources are often characterized by their exceptionally low permeability. To tap into these resources, horizontal wells are drilled, and multiple hydraulic fractures are employed to establish reservoirs. Achieving economically viable production rates necessitates the efficient flow of hydrocarbons through these hydraulic fractures toward the wellbore. The analysis of production decline involves the examination of historical trends in well and reservoir performance, focusing on plots that display the relationship between production rate and time as well as cumulative production. In the petroleum industry, four techniques are commonly used to assess reserves: decline curve analysis, numerical simulation, material balance, and volumetric analysis. Decline curve analysis, utilizing the least squares method, is particularly effective in fitting a best-fit equation to a set of data points. By calculating the future rate at any desired time and determining reserves from a specific point to an economically viable period, this approach proves valuable for estimating critical parameters such as the initial decline rate (D), initial rate (qi), and the hyperbolic exponent (b). These values can then be graphed over time to illustrate the decline in production rates.

A path analysis investigation into menopausal osteoporosis, sarcopenia risk, and their impact on sleep quality, depressive symptoms and quality of life

PurposeThe objective was to investigate the relationships among disease characteristics, sarcopenia risk, bone function, sleep quality, depressive symptoms, and health-related quality of life in menopausal women. Additionally, we also examined the potential mediating role of coping in the relationship between these factors and health outcomes for individuals with osteoporosis. MethodsIn a cross-sectional approach, 201 participants were referred by a physician from the Family Medicine Department during their outpatient visits at a general hospital in Southern Taiwan. Data collection involved structured one-on-one interviews, and the analysis included descriptive and inferential statistics, along with a structural equation modeling. ResultsThe participants' bone function was strongly positively related to coping, physical and mental quality of life (QOL), and negatively related to sleep quality and depressive symptoms. The duration of osteoporosis was positively related to pain, sarcopenia risk, sleep quality, but negatively related to bone function, physical and mental QOL. This structural framework explains 36% of the variance in depressive symptoms, 25% in sleep disturbances, 54% in mental QOL, and 72% in physical QOL. The best-fit structural equation modeling showed that physical function, exercise, sarcopenia, pain, and coping were significant predictors of depressive symptoms, with coping acting as a mediator in these relationships. ConclusionIndividuals who employed more active coping strategies exhibited fewer depressive symptoms, better sleep quality, and superior physical and mental QOL. Further, individuals with osteoporosis had lower pain levels, less sarcopenia risk, and higher engaged in exercise presentation improved physical and mental QOL. Future longitudinal research holds the promise of providing deeper insights into these complex relationships.

Risk Prediction for Atherosclerotic Cardiovascular Disease With and Without Race Stratification

Use of race-specific risk prediction in clinical medicine is being questioned. Yet, the most commonly used prediction tool for atherosclerotic cardiovascular disease (ASCVD)-pooled cohort risk equations (PCEs)-uses race stratification. To quantify the incremental value of race-specific PCEs and determine whether adding social determinants of health (SDOH) instead of race improves model performance. Included in this analysis were participants from the biracial Reasons for Geographic and Racial Differences in Stroke (REGARDS) prospective cohort study. Participants were aged 45 to 79 years, without ASCVD, and with low-density lipoprotein cholesterol level of 70 to 189 mg/dL or non-high-density lipoprotein cholesterol level of 100 to 219 mg/dL at baseline during the period of 2003 to 2007. Participants were followed up to 10 years for incident ASCVD, including myocardial infarction, coronary heart disease death, and fatal and nonfatal stroke. Study data were analyzed from July 2022 to February 2023. Discrimination (C statistic, Net Reclassification Index [NRI]), and calibration (plots, Nam D'Agostino test statistic comparing observed to predicted events) were assessed for the original PCE, then for a set of best-fit, race-stratified equations including the same variables as in the PCE (model C), best-fit equations without race stratification (model D), and best-fit equations without race stratification but including SDOH as covariates (model E). This study included 11 638 participants (mean [SD] age, 61.8 [8.3] years; 6764 female [58.1%]) from the REGARDS cohort. Across all strata (Black female, Black male, White female, and White male participants), C statistics did not change substantively compared with model C (Black female, 0.71; 95% CI, 0.68-0.75; Black male, 0.68; 95% CI, 0.64-0.73; White female, 0.77; 95% CI, 0.74-0.81; White male, 0.68; 95% CI, 0.64-0.71), in model D (Black female, 0.71; 95% CI, 0.67-0.75; Black male, 0.68; 95% CI, 0.63-0.72; White female, 0.76; 95% CI, 0.73-0.80; White male, 0.68; 95% CI, 0.65-0.71), or in model E (Black female, 0.72; 95% CI, 0.68-0.76; Black male, 0.68; 95% CI, 0.64-0.72; White female, 0.77; 95% CI, 0.74-0.80; White male, 0.68; 95% CI, 0.65-0.71). Comparing model D with E using the NRI showed a net percentage decline in the correct assignment to higher risk for male but not female individuals. The Nam D'Agostino test was not significant for all race-sex strata in each model series, indicating good calibration in all groups. Results of this cohort study suggest that PCE performed well overall but had poorer performance in both BM and WM participants compared with female participants regardless of race in the REGARDS cohort. Removal of race or the addition of SDOH did not improve model performance in any subgroup.

Abstract 16300: Genetic Influences on Cardiovascular Deaths During Various Follow-Up Lengths in the 45-Year Longitudinal Twin Study

Background: Genetic factors are known to affect cardiovascular and coronary heart death. The more deaths occur during the longer follow-up period in a longitudinal study. However, it is unclear whether follow-up lengths affect genetic influences on the mortality from total cardiovascular (CVD) and coronary heart diseases (CHD). Objective: To determine genetic influences on the mortality from CVD and CHD over various years of follow-up in the 45-year longitudinal National Heart, Lung, and Blood Institute (NHLBI) Twin Study. Method: A total of 1024 middle-aged, white male, veteran twins (512 pairs), including 253 monozygotic and 261 dizygotic twin pairs, were initially enrolled during 1969-1973 and then followed up on vital status and causes of death through December 31, 2015. Tetrachoric correlation coefficients were estimated for CHD and CVD death at 20, 30, and 45 years of follow-up, respectively. Genetic and environmental influences on the death were quantified using the best-fitting structural equation model selected with the smallest Akaike's Information Criterion value and the parsimony rule. Results: The age at death ranged from 43.9 to 97.3 years over a 45-year follow-up. Tetrachoric correlation coefficients in dizygotic twins were less than half of that in monozygotic twins over 20, 30, and 45 years of follow-up for CVD but over 20 and 30 years for CHD, respectively. Dominant genetic factors explained 40% (95% CI 5% ~ 68%), 39 % (16% ~ 59%), and 24% (4% ~ 43%) of variation in CVD death over 20, 30, and 45 years of follow-up, respectively, while the remaining variation in CVD death was explained by unique environmental factors during each follow-up period. For CHD death, unique environmental factors explained all variation over 20 and 45 years of follow-up. By contrast, dominant genetic factors explained 26% (95% CI -6% ~ 53%) variation in CHD death over 30 years of follow-up while the remaining variation was explained by unique environmental factors. Conclusion: Dominant genetic factors consistently influence cardiovascular mortality over 20 to 45 years of follow-up, implying a twin study of cardiovascular death can control for genetic confounding during this period.

Prediction equations of the metabolizable energy in corn developed by chemical composition and enzymatic hydrolysate gross energy for roosters

Two experiments were conducted to establish the prediction equations for AME and TME of corn based on chemical composition and enzymatic hydrolysate gross energy (EHGE) in roosters. In experiment 1, eighty 32-wk-old Hy-line Brown roosters with an average body weight of 2.55 ± 0.21 kg were randomly assigned to 10 diet treatments in a completely randomized design to determine AME and TME by the force-feeding method. Each treatment had 8 replicates with 1 bird per replicate. The 10 test diets used in the experiment were formulated with corn (including 96.10%) as the sole source of energy. In experiment 2, the EHGE of 14 corn samples was measured by the computer-controlled simulated digestion system (CCSDS) with 5 replicates of each sample. The average AME and TME values of corn were 14.58 and 16.46 MJ/kg DM, respectively. The EHGE of 14 corn samples ranged from 14.66 to 15.89 (the mean was 15.24) MJ/kg DM. The best-fit equations for corn based on chemical composition were AME (MJ/kg DM) = 14.5504 + 0.1166 × ether extract (EE) + 0.5058 × Ash - 0.0957 × neutral detergent fiber (NDF) (R2 = 0.8194, residual standard deviation (RSD) = 0.0860, P < 0.01) and TME (MJ/kg DM) = 16.0625 + 0.1314 × EE + 0.4725 × Ash - 0.0872 × NDF (R2 = 0.7867, RSD = 0.0860, P < 0.01). The best-fit equations for corn based on EHGE were AME (MJ/kg DM) = 7.8883 + 0.4568 × EHGE (R2 = 0.8587, RSD = 0.0693, P < 0.01) and TME (MJ/kg DM) = 10.0099 + 0.4228 × EHGE (R2 = 0.8720, RSD = 0.0608, P < 0.01). The differences between determined and predicted values from equations established based on EHGE were lower than those observed from chemical composition equations. These results indicated that EHGE measured with CCSDS could predict the AME and TME of corn for roosters with high accuracy.

Metabolic cost and mechanical work of walking in a virtual reality emulator.

The purpose of this study was to investigate the metabolic cost (C), mechanical work, and kinematics of walking on a multidirectional treadmill designed for locomotion in virtual reality. Ten participants (5 females, body mass 67.2 ± 8.1kg, height 1.71 ± 0.07m, age 23.6 ± 1.9years, mean ± SD) walked on a Virtuix Omni multidirectional treadmill at four imposed stride frequencies: 0.70, 0.85, 1.00, and 1.15Hz. A portable metabolic system measured oxygen uptake, enabling calculation of C and the metabolic equivalent of task (MET). Gait kinematics and external, internal, and total mechanical work (WTOT) were calculated by an optoelectronic system. Efficiency was calculated either as WTOT/C or by summing WTOT to the work against sliding frictions. Results were compared with normal walking, running, and skipping. C was higher for walking on the multidirectional treadmill than for normal walking, running, and skipping, and decreased with speed (best-fit equation: C = 20.2-27.5·speed + 15.8·speed2); the average MET was 4.6 ± 1.4. Mechanical work was higher at lower speeds, but similar to that of normal walking at higher speeds, with lower pendular energy recovery and efficiency; differences in efficiency were explained by the additional work against sliding frictions. At paired speeds, participants showed a more forward-leaned trunk and higher ankle dorsiflexion, stride frequency, and duty factor than normal walking. Walking on a multidirectional treadmill requires a higher metabolic cost and different mechanical work and kinematics than normal walking. This raises questions on its use for gait rehabilitation but highlights its potential for high-intensity exercise and physical activity promotion.

Application of Simple Crested Weirs to Control Outflows from Tiles Drainage

Triangular sharp-crested weirs are commonly used to measure low-flow measurements in open channels. The flow over such a V-notch is proportional to the height of water above the weir on the upstream side. Therefore, it is relatively easy to calculate the flow from standard equations by using only recordings of water levels. Thus, these types of weirs can provide inexpensive measurements of flow volumes and resulting nutrient loads from subsurface drainage systems and associated conservation practices. The objective of this study was to develop appropriate weir equations for a 22.5° V-notch weir developed for a new tubular water level control structure in a controlled drainage system (CD). Analyses using this weir, with three typical slope angles of 30°, 45°, and 60°, were also conducted. There were no significant differences in the fitted parameters across the three analyzed slope angles. The coefficient of determination (R2) values were 0.9955, 0.9981, and 0.9980, respectively. However, the best-fitted equation for a 22.5° V-notch weir was for a slope angle of 45°. The flow equation was Q = 0.2235H2.4182, with Q in liters per minute and H in centimeters. This equation can be used for measuring flow through tubular-controlled drainage structures.

Constraining quadratic f(R) gravity from astrophysical observations of the pulsar J0704+6620

We apply quadratic f(R) = R + ϵR 2 field equations, where ϵ has a dimension [L2], to static spherical stellar model. We assume the interior configuration is determined by Krori-Barua ansatz and additionally the fluid is anisotropic. Using the astrophysical measurements of the pulsar PSR J0740+6620 as inferred by NICER and XMM observations, we determine ϵ ≈ ± 3 km2. We show that the model can provide a stable configuration of the pulsar PSR J0740+6620 in both geometrical and physical sectors. We show that the Krori-Barua ansatz within f(R) quadratic gravity provides semi-analytical relations between radial, pr , and tangential, pt , pressures and density ρ which can be expressed as pr ≈ vr 2 (ρ-ρ 1) and pr ≈ vt 2 (ρ-ρ 2), where vr (vt ) is the sound speed in radial (tangential) direction, ρ 1 = ρs (surface density) and ρ 2 are completely determined in terms of the model parameters. These relations are in agreement with the best-fit equations of state as obtained in the present study. We further put the upper limit on the compactness, C = 2GMRs -1 c -2, which satisfies the f(R) modified Buchdahl limit. Remarkably, the quadratic f(R) gravity with negative ϵ naturally restricts the maximum compactness to values lower than Buchdahl limit, unlike the GR or f(R) gravity with positive ϵ where the compactness can arbitrarily approach the black hole limit C → 1. The model predicts a core density a few times the saturation nuclear density ρ nuc = 2.7 × 1014 g/cm3, and a surface density ρs > ρnuc . We provide the mass-radius diagram corresponding to the obtained boundary density which has been shown to be in agreement with other observations.

The Influence of Hydrogen Sulfide on the Optical Properties of Planetary Organic Hazes: Implications for Exoplanet Climate Modeling

Planetary organic hazes can play a significant role in influencing a planet’s radiative balance and climate, with their impact determined by the optical properties of the haze. The optical properties, in turn, are partly influenced by particle composition. Our previous work, Reed et al., demonstrated that trace amounts of hydrogen sulfide (H2S) in haze chemistry can substantially affect the haze’s composition by generating organosulfur compounds and increasing the amount of organic haze produced. However, no study has measured the optical properties of an H2S-influenced organic haze. Here we present results from laboratory experiments measuring the real (scattering, n) and imaginary (absorbing, k) refractive indices of haze analogs produced from photochemistry of gas mixtures composed of 0.1% CH4 and variable H2S (0–10 ppmv) in N2. The optical properties of the aerosol produced were measured in real-time using coupled photoacoustic and cavity ring-down spectroscopy with 405 and 532 nm wavelengths of light. Our findings show that the total extinction of light (scattering plus absorption) by the aerosol increases as a function of H2S mixing ratio. We provide our best-fit equations for predicting n and k at 405 and 532 nm as a function of the sulfur to carbon molar ratio (S:C) of the precursor gas mixture. Further, we demonstrate how these changes in optical properties could alter the transmittance of 405 and 532 nm light through a haze layer. These results have potential implications for modeling the climate, habitability, and spectra for exoplanets exhibiting organic haze.

EFFECT OF STANDARD PENETRATION TEST CORRECTIONS ON THE ESTIMATION OF UNDRAINED SHEAR STRENGTH

This paper evaluated the influence of Standard Penetration Test (SPT) correction factors, namely the hammer energy efficiency, borehole diameter, drill rod length, and sampling method, on the correlations between SPT resistance (SPT-N) and undrained shear strength (Su). Comparisons were made between new equations (with and without SPT corrections), which were derived from soil data collected from Penang Island, Malaysia. The coefficient of determination, Absolute Average Relative Error, Standard Deviation, and Analysis of Variance (ANOVA) were employed as the basis for the assessments. Finally, a comprehensive analysis was carried out to evaluate the relationship between uncorrected ratio (Su/N) or corrected ratio (Su/N60) and Plasticity Index (PI)/Liquidity Index (LI). Based on the results, all correction factors recorded a significant impact on the estimated Su, as the ANOVA calculation suggested that the borehole diameter correction was the most statistically significant. Furthermore, the Su/N and Su/N60 exhibited increasing trends with increased PI and LI, which may be attributed to the soil’s state and behaviour. Additionally, cubic regression is the best-fit equation to correlate the parameters. In summary, this study provided new insights into the influence of correction factors, which can be used to improve the accuracy of the empirical correlations and engineering designs.

Allometric relationships for eight species of 4-5 year old nitrogen-fixing and non-fixing trees.

Allometric equations are often used to estimate plant biomass allocation to different tissue types from easier-to-measure quantities. Biomass allocation, and thus allometric equations, often differs by species and sometimes varies with nutrient availability. We measured biomass components for five nitrogen-fixing tree species (Robinia pseudoacacia, Gliricidia sepium, Casuarina equisetifolia, Acacia koa, Morella faya) and three non-fixing tree species (Betula nigra, Psidium cattleianum, Dodonaea viscosa) grown in field sites in New York and Hawaii for 4-5 years and subjected to four fertilization treatments. We measured total aboveground, foliar, main stem, secondary stem, and twig biomass in all species, and belowground biomass in Robinia pseudoacacia and Betula nigra, along with basal diameter, height, and canopy dimensions. The individuals spanned a wide size range (<1-16 cm basal diameter; 0.24-8.8 m height). For each biomass component, aboveground biomass, belowground biomass, and total biomass, we determined the following four allometric equations: the most parsimonious (lowest AIC) overall, the most parsimonious without a fertilization effect, the most parsimonious without canopy dimensions, and an equation with basal diameter only. For some species, the most parsimonious overall equation included fertilization effects, but fertilization effects were inconsistent across fertilization treatments. We therefore concluded that fertilization does not clearly affect allometric relationships in these species, size classes, and growth conditions. Our best-fit allometric equations without fertilization effects had the following R2 values: 0.91-0.99 for aboveground biomass (the range is across species), 0.95 for belowground biomass, 0.80-0.96 for foliar biomass, 0.94-0.99 for main stem biomass, 0.77-0.98 for secondary stem biomass, and 0.88-0.99 for twig biomass. Our equations can be used to estimate overall biomass and biomass of tissue components for these size classes in these species, and our results indicate that soil fertility does not need to be considered when using allometric relationships for these size classes in these species.

Prediction of body fat percentage: Development and validation of new anthropometric equations

The aim of this study was to test the validity of existing equations, retrieved from the literature, in the Algerian adult population. To develop, and validate, new predictive equations for body fat percentage (%BF) using simple and easy-to-measure anthropometric parameters. This is a cross-sectional study including 877 Algerian adults who underwent a body composition assessment by the direct segmental multi-frequency bioelectrical impedance technique (Inbody-770). Participants were randomly divided into two groups: the development group (n=577) and the validation group (n=300). To develop the equations, multiple linear regression models were analyzed. The predictive performance of the developed equations was compared with the direct technique. The following validation tests were used: Student's t-test for paired samples, correlation, and Bland-Altman diagram. Diagnostic accuracy has also been assessed. Four existing equations were tested, and all showed statically significant bias. Four new equations were developed; all had satisfactory predictive performance, with a correlation coefficient ranging from 0.72 to 0.94 in men and 0.87 to 0.93 in women. The best-fitting equation was based on body mass index, waist-to-hip ratio, and chest circumference. The diagnostic accuracy of this equation was 96.7% in men and 95.3% in women. The newly developed equations based on anthropometric parameters can serve as a simple tool for the accurate prediction of BF% in adult subjects, at both individual and epidemiological levels.

The optimal tibial tunnel placement to maximize the graft bending angle in the transtibial posterior cruciate ligament reconstruction: a quantitative assessment in three-dimensional computed tomography model.

The graft bending angle created by the graft and the tibial tunnel has inevitably occurred during the transtibial posterior cruciate ligament (PCL) reconstruction. However, few studies quantitively analyzed this angle. This study aimed to (I) explore the optimal tibial tunnel placement to maximize the graft bending angle in the PCL reconstruction; (II) reveal the effect of the tibial tunnel placement on the graft bending angle. This was an in-vitro surgical simulation study based on the three-dimensional (3D) computed tomography (CT). A total of 55 patients who took CT scanning for knee injuries were selected (April 2020 to January 2022) from the local hospital database for review. The 3D knee models were established on the Mimics software based on the knees' CT data. Using the Rhinoceros software to simulate the transtibial PCL reconstruction on the 3D CT knee model. The anteromedial and anterolateral tibial tunnel approaches were simulated with different tibial tunnel angle. The graft bending angle and tibial tunnel length (TTL) with different tibial tunnel angles were quantitively analyzed. The graft bending angle in anterolateral approach with a 50° tibial tunnel angle was significantly greater than it in anteromedial approach with a 60° tibial tunnel angle (P<0.001). There was no difference of the graft bending angle between the anterolateral approach with a 40° tibial tunnel angle and the anteromedial approach with a 60° tibial tunnel angle (P>0.05). The graft bending angle showed a strong correlation with the tibial tunnel angle (for anteromedial approach: r=0.759, P<0.001; for anterolateral approach: r=0.702, P<0.001). The best-fit equation to calculate the graft bending angle based on the tibial tunnel angle was Y = 0.89*X + 59.05 in anteromedial tibial tunnel approach (r2=0.576), and was Y = 0.78*X + 80.21 anterolateral tibial tunnel approach (r2=0.493). The graft bending angle and TTL will significantly increase as the tibial tunnel angle becomes greater. Maximizing the tibial tunnel angle (50° tibial tunnel angle) in the anterolateral approach could provide the greatest graft bending angle in the PCL reconstruction. No matter how the tibial tunnel angle is changed in the anteromedial approach, using anterolateral approach might reduce the killer turn effect more effectively than using anteromedial approach.