Percent Of Variance Research Articles

Designing and Validating a Hereditary Spastic Paraplegia-Specific Quality of Life Rating Scale (HSPQoL)

Patients with Hereditary Spastic Paraplegia (HSP) report reduced quality of life (QoL) compared to the general population. Generic QoL measures do not address disease-specific aspects such as spasticity, access to specialty HSP clinics, and bladder symptoms. We designed and validated a HSP-specific QoL scale (HSPQoL), intended for use in standard clinical settings and clinical trials. HSP-specific items were added to the RAND 36-Item Short Form Health Survey (SF-36) to form HSPQoL. Following literature review/expert input, 23 items were presented to a panel of HSP clinicians, patients, and patient representatives (n = 12) using a modified Delphi process. Items were ranked for clarity and relevance (inclusion criteria: 80% consensus). 21/23 items met the inclusion criteria. Interviews with patients (n = 5) assessed suitability, comprehension, clarity, and response options to additional items. Based on cognitive interview results, items were modified (n=4), removed (n=7), or added (n=3). Sixty-one patients completed the HSPQoL and EQ5D-5L for evaluation of construct validity and 19 patients repeated the HSPQoL for evaluation of test–retest reliability. 15/17 additional items moderately to strongly correlated with pre-existing SF-36 subscores (Spearman correlation 0.319–0.771, p < 0.05). Exploratory factor analyses showed high percentage of variance in the first component (> 45%). HSPQoL demonstrated good internal consistency (Cronbach alpha 0.94), test–retest reliability (ICC 0.957), and convergent validity with EQ5D-5L (r = 0.725). In conclusion, demonstrated validity and reliability of the HSPQoL confirms consideration of its use for assessing specific QoL in individuals with HSP.

A function-based mapping of sensory integration along the cortical hierarchy

Sensory information mainly travels along a hierarchy spanning unimodal to transmodal regions, forming multisensory integrative representations crucial for higher-order cognitive functions. Here, we develop an fMRI based two-dimensional framework to characterize sensory integration based on the anchoring role of the primary cortex in the organization of sensory processing. Sensory magnitude captures the percentage of variance explained by three primary sensory signals and decreases as the hierarchy ascends, exhibiting strong similarity to the known hierarchy and high stability across different conditions. Sensory angle converts associations with three primary sensory signals to an angle representing the proportional contributions of different sensory modalities. This dimension identifies differences between brain states and emphasizes how sensory integration changes flexibly in response to varying cognitive demands. Furthermore, meta-analytic functional decoding with our model highlights the close relationship between cognitive functions and sensory integration, showing its potential for future research of human cognition through sensory information processing.

Hyperspectral Raman imaging with multivariate curve resolution-alternating least square (MCR-ALS) analysis for xylazine-containing drug mixtures

Xylazine, increasingly implicated in illicit opioid overdose deaths, poses a significant public health threat due to its synergistic effects with fentanyl and resistance to naloxone reversal. Despite its rising prevalence, xylazine is not classified as a controlled substance, leading to its exclusion from routine forensic screening. This study introduces a novel analytical method combining Raman hyperspectral imaging with Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to detect xylazine in drug mixtures containing common excipients such as acetaminophen, dipyrone, and mannitol. Utilizing only non-negativity constraints, MCR-ALS successfully resolved the Raman spectrum of xylazine at levels as low as 5 % without reference spectra. The method demonstrated robust performance, with percent variance explained (R²) values of 99.60 %, 99.80 %, and 99.91 % for the drug mixtures containing 25 %, 10 %, and 5 % xylazine, respectively.

Rapid Authentication of Intact Stingless Bee Honey (SBH) by Portable LED-Based Fluorescence Spectroscopy and Chemometrics.

Indonesian stingless bee honey (SBH) of Geniotrigona thoracica is popular and traded at an expensive price. Brown rice syrup (RS) is frequently used as a cheap adulterant for an economically motivated adulteration (EMA) in SBH. In this study, authentic Indonesian Geniotrigona thoracica SBH of Acacia mangium (n = 100), adulterated SBH (n = 120), fake SBH (n = 100), and RS (n = 200) were prepared. In short, 2 mL of each sample was dropped directly into an innovative sample holder without any sample preparation including no dilution. Fluorescence intensity was acquired using a fluorescence spectrometer. This portable instrument is equipped with a 365 nm LED lamp as the fixed excitation source. Principal component analysis (PCA) was calculated for the smoothed spectral data. The results showed that the authentic SBH and non-SBH (adulterated SBH, fake SBH, and RS) samples could be well separated using the smoothed spectral data. The cumulative percentage variance of the first two PCs, 98.4749% and 98.4425%, was obtained for calibration and validation, respectively. The highest prediction accuracy was 99.5% and was obtained using principal component analysis-linear discriminant analysis (PCA-LDA). The best partial least square (PLS) calibration was obtained using the combined interval with R2cal = 0.898 and R2val = 0.874 for calibration and validation, respectively. In the prediction, the developed model could predict the adulteration level in the adulterated honey samples with an acceptable ratio of prediction to deviation (RPD) = 2.282, and range error ratio (RER) = 6.612.

University Governance in the Legal Entrepreneurship of Intellectual Capital Around the Implementation of the SDGs

Aim. The study's objective is to compare a theoretical model of university governance in the COVID-19 era. Since the literature consulted warns of the pandemic's impact on university governance, the factor structure was confirmed. Method. An exploratory, cross-sectional, and correlational study was carried out with a sample of 180 administrators, teachers, and students from a university in central Mexico selected for their participation in the social service system and professional practices in community health institutions. The instrument was evaluated using the Delphi technique in three phases: qualifying, comparative, and reiterative- reconsidered. The University Governance Scale was applied via Zoom session. The data were captured in Excel and processed in JASP. Reliability, validity, adjustment, and residual coefficients were estimated to contrast hypotheses. Results. The three-factor structure was corroborated: identity, reputation, and image. Although the first factor explained the highest percentage of variance, only 12 of 18 indicators correlated with its factors. Conclusions. The study's contribution lies in contrasting the university governance model in a scenario of exposure to COVID-19. Still, the study's limit lies in the non-generalization of the results to the university community.

TMIC-11. THE EFFECTIVENESS OF VALPROIC ACID IN COMBINATION WITH TEMOZOLOMIDE FOR TREATMENT OF HIGH-GRADE GLIOMAS: A SYSTEMATIC REVIEW AND META-ANALYSIS

Abstract BACKGROUND High-grade gliomas (HGGs) rapidly progress with a high recurrence rate and poor prognosis despite standard multimodal treatment. Valproic acid (VPA), a histone deacetylase inhibitor, sensitizes HGG to radiochemotherapy along with having potential anti-cancer mechanisms and augmenting the growth inhibitory effect of Temozolomide (TMZ). This study explores the effectiveness of VPA in combination with TMZ for treating patients with HGG. METHODS A comprehensive literature search was performed on PubMed, Scopus, Embase, and Web of Science databases and identified relevant studies (case-control, cohort, RCTs) comparing the synergistic effect of VPA during TMZ to TMZ without VPA. We investigated median overall survival (OS), Progression-free survival (PFS), and baseline MGMT methylation status to evaluate this relationship. RESULTS Our systematic review encompassed 9 studies involving 4,097 patients with HGGs (seven cohorts, one case-control, and one RCT). The pooled analysis of median OS demonstrated no statistical significance difference between VPA during TMZ and TMZ alone (MD=-3.97; 95%CI=-8.43-0.49; p=0.08). However, sub-analysis showed a statistically significant effect in studies with sample size &amp;lt;100 (MD=-5.06; 95%CI=-9.32,-0.80; p&amp;lt;0.02), and 100-200 (MD=-7.07; 95%CI=-13.15,-1.00; p&amp;lt;0.02), and those conducted before 2015 (MD=-5.62, 95%CI=-9.08,-2.17, p&amp;lt;0.01). On meta-regression analysis, no statistical significance (RC=0.82,95% CI=0.39,-2.03, p=0.18) was observed, indicating that the study year is not associated with the intervention. A separate analysis of 3 studies also showed no significant variance in the baseline percentage of patients without MGMT methylation (log OR=-0.35, 95%CI=-1.02,-0.32, p=0.30) when administering VPA during TMZ treatment (n=67) compared to TMZ alone (n=409). Additionally, VPA during TMZ does not significantly affect PFS (MD=-3.54; 95% CI=-10.18-3.10, p=0.30) compared to TMZ alone. CONCLUSIONS The concurrent use of VPA with TMZ shows no significant effect on OS and PFS, nor does it show any variance in the baseline MGMT methylation status compared to TMZ alone. However, smaller sample sizes show a significant effect. Thus, our findings emphasize the imperative for additional research aimed at refining clinical outcomes.

Consumer style inventory (CSI) re-examined: The case of millennial decision-making style in a developing market

This study investigates the buying styles of young consumers, especially the millennials—Gen Y, and Gen Z whose idiosyncrasies and consumption peculiarities are quite different from the older generations. Besides Sproles and Kendall’s eight (8) consumer-style inventory dimensions, this study presents new dimensions and develops six constructs that define young consumers’ decision-style inventory in a developing market. The study population consisted of all younger consumers—Gen Y, and Gen Z in Lagos State, Nigeria. One hundred and twenty-five (125) respondents were selected randomly across all 20 Local Governments in Lagos State, Nigeria. Factor analyses through varimax rotation, latent root criterion (eigenvalue = 1), screen plot test and the percentage of variance were conducted to determine the significant factors to retain among the variables. The findings clearly showed that newly developed CSI constructs in this study (sexiness, trendiness, global branding, smartness, socialisation and entertainment) were strong and significant among young consumers’ decision-making styles. The six (6) constructs developed showed that the younger consumers’ consumption styles are evolving, becoming sophisticated and relatively dynamic, hence the reliance on Sproles and Kendall’s dimensions to measure the younger consumers’ consumption decision styles will be inadequate in business/behaviour strategy development. The dimensions of entertainment, sexy, social, trendy, smartness and global branding variables are mostly underpinned and dominate considerations in purchase decision styles and behaviours among young consumers.

Assessment of Socioeconomic Vulnerability in Selected Villages of Gosaba Block, Sundarban, India Using an Artificial Neural Network

The Indian Sundarban represent an endangered ecosystem with a distinct biogeographical composition. It is susceptible to natural disasters like storms, floods, and cyclones, hence jeopardizing its socioeconomic systems due to environmental stresses. This study aimed to evaluate the present socioeconomic vulnerability, identify key factors that exacerbate this vulnerability, and validate these factors using an Artificial Neural Network (ANN) prediction model. Researchers also wanted to validate this evaluation with ANN to promote substantive discussions between researchers, local authorities, and stakeholders. Comprehensive reviews and successful adaption plans will improve. The study conducted in selected villages with 160 households in the Gosaba Block, located on the periphery of the Sundarban. The present study employed an integrated vulnerability approach, calculating the exposure, adaptive capacity, and sensitivity index by weighting the initial eigenvalues of each indicator with a variance percentage through principal components analysis (PCA). Based on this criterion, 156 households (97.5%) exhibited an extremely high vulnerability score, while 4 households (2.5%) displayed a moderate vulnerability grade. The villages of Pakhiralay and Lahiripur exhibit significant vulnerability, with a markedly deficient adaptive capacity. The villages of Mathurakhand, Kumirmari, and Satjelia exhibit vulnerability alongside moderate adaptation capacity. All are priority villages, however, Villages with moderate adaptive capacity may become less vulnerable with adequate interventions Proximity to market strongly affects MLP neural networks' assessment of environmental, economic, and social variables' effects on exposure, sensitivity, and adaptive capacity. Respondent age, family size, social network, storm surges, supplementary sources of household income Dwelling years, temperature, embankment failure, and income greatly affect model performance. A policy initiative should prioritize the enhancement existing social and financial capital, facilitate access to local government, and promote community-oriented activities. National disaster, social welfare, and resource management strategies need separate action plans. The national government is also encouraged to decentralize governance to enable local governments to achieve their goals.

Assessment of conservation status of Ferula huber‐morathii: association with population genetic structure and regional climate

Ferula huber‐morathii is an endemic and medicinally important plant. This species is distributed in eight Turkish localities, including three newly identified ones. Its extent of occurrence and area of occupancy is determined to be 3963 km2 and 32 km2 respectively. All localities are characterized by East Mediterranean and sub‐Mediterranean precipitation regimes; however, temperatures increase excessively and precipitation decreases during the flowering period of the species. The population sizes are quite small, and the number of reproducing individuals in some populations is below ten. Analyses of ISSR markers showed the percentage of polymorphic loci to be 94% at the species level and 56% at the population level. The level of genetic differentiation (measured by GST) was 0.37 and the estimated level of gene flow among populations (NM) was 0.84. The percentage of variance occurring within and among populations, determined by AMOVA, was 75% and 25%, respectively. STRUCTURE analysis revealed two genetic clusters of individuals with a geographic structure, similar to that found in UPGMA and an ordination analysis. Some populations turned out to have both low numbers of individuals and low genetic diversity. Since many of the populations are subject to anthropogenic disturbance, the species should remain in the EN category. At the same time, it is suggested that a new in‐situ conservation area should be created around nearby dams, situated in the same climate area as the currently known populations.

Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits.

Plant height can be an indicator of plant health across environments and used to identify superior genotypes. Typically plant height is measured at a single timepoint when plants reach terminal height. Evaluating plant height using unoccupied aerial vehicles allows for measurements throughout the growing season, facilitating a better understanding of plant-environment interactions and the genetic basis of this complex trait. To assess variation throughout development, plant height data was collected from planting until terminal height at anthesis (14 flights 2018, 27 in 2019, 12 in 2020, and 11 in 2021) for a panel of ~500 diverse maize inbred lines. The percent variance explained in plant height throughout the season was significantly explained by genotype (9-48%), year (4-52%), and genotype-by-year interactions (14-36%) to varying extents throughout development. Genome-wide association studies revealed 717 significant single nucleotide polymorphisms associated with plant height and growth rate at different parts of the growing season specific to certain phases of vegetative growth. When plant height growth curves were compared to growth curves estimated from canopy cover, greater Fréchet distance stability was observed in plant height growth curves than for canopy cover. This indicated canopy cover may be more useful for understanding environmental modulation of overall plant growth and plant height better for understanding genotypic modulation of overall plant growth. This study demonstrated that substantial information can be gained from high temporal resolution data to understand how plants differentially interact with the environment and can enhance our understanding of the genetic basis of complex polygenic traits.

Internal Controls and Customer Satisfaction in the Telecommunications Industry in Uganda: A Case of MTN Uganda

Every business organization's success depends on the satisfaction of the customers. Whenever a business is about to start, customers always come “first” and then the profit. Those companies that succeed in fully satisfying their customers will remain in the top position in the market. Today's business company has known that customer satisfaction is the key component for the success of the business, and at the same time, it plays a vital role in expanding the market value. In general, customers are those people who buy goods and services from the market or business that meet their needs and wants. Customers purchase products to meet their expectations in terms of money. The study sought to explain the extent to which Customer Satisfaction in the telecommunications industry is driven by internal controls, using MTN Uganda as a case study. Many in Uganda recognize the importance of customer satisfaction and so have tried to streamline internal controls. However, customer complaints still persist despite efforts to address areas of dissatisfaction. This may be because the majority of them do not effectively operate their internal processes and are not using appropriate strategies to address the challenges. The study was guided by three objectives: To examine the effect of administrative policies on customer satisfaction in the telecommunications industry, To examine the effect of accounting procedures on customer satisfaction in the telecommunications industry and To examine the effect of auditing procedures on customer satisfaction in the telecommunications industry. The study was based on a cross-sectional research design. 230 staff of the company were selected as respondents using a simple random sampling approach, and data was collected using a questionnaire. Findings show that there is a strong, positive relationship between administrative policies and customer satisfaction, there is a strong and positive relationship between accounting procedures and customer satisfaction in the telecommunications industry, and there is a strong and positive relationship between audit procedures and customer satisfaction in the telecommunications industry. The variables entered in the regression model explain an overall 65 percent variance in customer satisfaction at the company. It was recommended that MTN Uganda conduct regular surveys of customers (current and potential) to assess their standing in expectations and satisfaction and identify areas that need critical attention. MTN Uganda should adopt the international customer quality guidelines, and all staff should undergo regular (every three months) refresher training regarding how to handle internal operations in their areas of speciality.

Psychometric properties of the Turkish version of the Vestibular Migraine Patient Assessment Tool and Handicap Inventory.

There are insufficient tools to assist in the diagnosis and treatment of vestibular migraine. Hence, the aim of this study was to perform the Turkish adaptation of the Vestibular Migraine Patient Assessment Tool and Handicap Inventory (VM-PATHI). After the language and content validity was completed, a pilot study was conducted. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to test construct validity, and as a result of the validity analyses, Cronbach's alpha internal consistency coefficient and test-retest analyses were conducted for reliability. In the study, in which 289 participants were evaluated, the Kaiser-Meyer-Olkin coefficient was calculated as 0.903. The percentage of variance explained by the EFA was 67.246% and the range of factor load change was 0.433-0.828. The scale structure was tested with CFA and the model was confirmed with adequate goodness of fit index values. The Cronbach's alpha internal consistency coefficient of the scale was 0.931. The VM-PATHI is a valid and reliable tool for the subjective evaluation of vestibular migraine in Türkiye.

Confirmatory Factor Analysis of the Sustainable Development Goals Derived Gentrification Scale in the Context of the Pandemic

In the context of human development goals, gentrification has emerged as a significant and unpredictable phenomenon amid the ongoing health crisis, potentially impacting the sustainable development goals (SDGs). This study aimed to analyze the theoretical framework of gentrification and its empirical indicators in the unique context of the pandemic, foreseeing potential risk scenarios. A cross-sectional, psychometric, and correlational study was conducted with 100 university students dedicated to the SDGs during the pandemic. The findings revealed the prevalence of two out of seven factors associated with poverty alleviation and institutional justice for peace. Given the observation of seven factors in the current literature, this study recommends expanding the indicators to enhance the variance percentage and aligning the theoretical model with empirical evidence. It underscores the pressing need for collaborative efforts in urban and sustainable development.

A-136 Icteric Interference is not Resolved with Sample Dilution in Serum Creatinine and Total Protein Assays

Abstract Background Icterus is a common endogenous interference that can cause falsely low results for serum creatinine and total protein. It can be defined by elevated unconjugated (indirect) and conjugated (direct) bilirubin levels and is most commonly associated with liver dysfunction. Recent literature suggests that dilutions can be a reliable method to reduce bilirubin interference. The purpose of this study was to determine whether the vendor’s on-board sample dilution can eliminate icteric interference with creatinine and total protein. Methods Creatinine (enzymatic) and total protein interference studies were performed on an automated chemistry analyzer (Roche Diagnostics, cobas c702). Low, mid, and high sample pools for each analyte were divided into four equal volumes. To achieve an icterus index (II) of approximately 40 (approximately 40 mg/dL of bilirubin), one sample pool was spiked with unconjugated bilirubin, and one pool was spiked with conjugated bilirubin. An equal amount of diluent was added into each control pool and remained at an II of approximately 0. The icteric and control samples were measured for conjugated and unconjugated bilirubin, serum indices, and the target analyte. Using the on-board dilution function, the icteric creatinine and total protein pools were diluted using a 1:4 and 1:3 dilution, respectively. All samples were analyzed in triplicate. Percent variance was found by calculating the difference between the average dilution result and control result and then dividing by the average control result. Results Conclusions Only modest alleviation of icteric interference was noted with dilution. The average bias was 10% for creatinine and 24% with total protein, after dilution. The on-board sample dilution is not effective in eliminating icteric interference when measuring both creatinine and total protein.

Identifying modifiable factors associated with neuroimaging markers of brain health.

Brain structural alterations begin long before the presentation of brain disorders; therefore, we aimed to systematically investigate a wide range of influencing factors on neuroimaging markers of brain health. Utilizing data from 30,651 participants from the UK Biobank, we explored associations between 218 modifiable factors and neuroimaging markers of brain health. We conducted an exposome-wide association study using the least absolute shrinkage and selection operator (LASSO) technique. Restricted cubic splines (RCS) were further employed to estimate potential nonlinear correlations. Weighted standardized scores for neuroimaging markers were computed based on the estimates for individual factors. Finally, stratum-specific analyses were performed to examine differences in factors affecting brain health at different ages. The identified factors related to neuroimaging markers of brain health fell into six domains, including systematic diseases, lifestyle factors, personality traits, social support, anthropometric indicators, and biochemical markers. The explained variance percentage of neuroimaging markers by weighted standardized scores ranged from 0.5% to 7%. Notably, associations between systematic diseases and neuroimaging markers were stronger in older individuals than in younger ones. This study identified a series of factors related to neuroimaging markers of brain health. Targeting the identified factors might help in formulating effective strategies for maintaining brain health.

Percentage of variance accounted for in structural equation models: The rediscovery of the goodness of fit index.

This article delves into the often-overlooked metric of percentage of variance accounted for in structural equation models (SEM). The goodness of fit index (GFI) provides the percentage of variance of the sum of squared covariances explained by the model. Despite being introduced over four decades ago, the GFI has been overshadowed in favor of fit indices that prioritize distinctions between close and nonclose fitting models. Similar to R² in regression, the GFI should not be used to this aim but rather to quantify the model's utility. The central aim of this study is to reintroduce the GFI, introducing a novel approach to computing the GFI using mean and mean-and-variance corrected test statistics, specifically designed for nonnormal data. We use an extensive simulation study to evaluate the precision of inferences on the GFI, including point estimates and confidence intervals. The findings demonstrate that the GFI can be very accurately estimated, even with nonnormal data, and that confidence intervals exhibit reasonable accuracy across diverse conditions, including large models and nonnormal data scenarios. The article provides methods and code for estimating the GFI in any SEM, urging researchers to reconsider the reporting of the percentage of variance accounted for as an essential tool for model assessment and selection. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Supplemental Material for Percentage of Variance Accounted for in Structural Equation Models: The Rediscovery of the Goodness of Fit Index

Supplemental Material for Percentage of Variance Accounted for in Structural Equation Models: The Rediscovery of the Goodness of Fit Index

Predictive utility of self-efficacy in early stroke rehabilitation

ABSTRACT Introduction A biopsychosocial approach entailing person-centered factors provides valuable insight to post-stroke rehabilitation potential. The consideration of an individual’s belief in their capabilities, known as self-efficacy, may prove especially informative in the inpatient rehabilitation setting where motor learning often occurs. Objective To assess the predictive utility of self-efficacy in functional independence status change during inpatient rehabilitation. Methods Individuals with stroke admitted to an inpatient rehabilitation facility (IRF) completed an assessment battery near IRF admission and discharge involving motor assessments, participant-reported self-efficacy (Stroke Self-Efficacy Questionnaire), and functional independence status evaluation (sum of self-care and mobility Quality Indicators (QI) from the IRF-Patient Assessment Instrument). Linear regression was performed to determine the predictive performance of self-efficacy on QI change during IRF stay while accounting for age, time post-stroke, and IRF length of stay. Regression procedures were repeated for separate subgroups based on initial motor impairment level. Results Thirty individuals with stroke (14 females, age = 67.0 ± 9.80 years, 10.4 ± 3.46 days post-stroke) were enrolled. Self-efficacy at IRF admission explained a significant percentage of variance in QI Change for the cohort (R2 = 30.7%, p = .001) and for the moderate to severe motor impairment subgroup (n = 12; R2 = 49.9%, p = .010). After accounting for confounders, self-efficacy remained a significant predictor for the cohort (n = 30) model. Discussion Findings generated from this work support the predictive utility of self-efficacy in early post-stroke motor recovery. The inclusion of self-efficacy in a multi-faceted evaluation framework may therefore optimize rehabilitation outcomes by providing therapists with additional knowledge to better tailor an individual’s care.

Induced and natural variation affect traits independently in hybrid Populus.

The genetic control of many plant traits can be highly complex. Both allelic variation (sequence change) and dosage variation (copy number change) contribute to a plant's phenotype. While numerous studies have investigated the effect of allelic or dosage variation, very few have documented both within the same system, leaving their relative contribution to phenotypic effects unclear. The Populus genome is highly polymorphic, and poplars are fairly tolerant of gene dosage variation. Here, using a previously established Populus hybrid F1 population, we assessed and compared the effect of natural allelic variation and induced dosage variation on biomass, phenology, and leaf morphology traits. We identified QTLs for many of these traits, but our results indicate limited overlap between the QTLs associated with natural allelic variation and induced dosage variation. Additionally, the integration of data from both allelic and dosage variation identifies a larger set of QTLs that together explain a larger percentage of the phenotypic variance. Finally, our results suggest that the effect of the large indels might mask that of allelic QTLs. Our study helps clarify the relationship between allelic and dosage variation and their effects on quantitative traits.

Antarctic ice surface properties inferred from Ka and Ku band altimeter waveforms

Altimetry missions designed for ocean monitoring can also evaluate the Antarctic ice sheet’s mass balance by measuring surface height. However, the returned radar echoes (waveforms) have complex shapes influenced by various snow and ice surface properties at multiple scales. Radar altimeters, operating in different modes and frequencies, interact with these surface properties in diverse ways. In this study, we developed a method to assess Antarctic surface properties using data from SARAL/AltiKa and Sentinel-3A & 3B altimeters for June 2021 and January 2023, respectively. We normalized and averaged the observed waveforms in 5 × 5 km2 grid cells. These were then used to create false-color images, with each grid cell’s average power and time gate represented as different ‘bands’. False-color images were analyzed using Principal Component Analysis (PCA) and ISODATA unsupervised classification to identify regions of Antarctica with similar surface properties. We achieved a percent variance of 73% and 84% for the first three Principal Components (PCs), and 96% and 98% for the first ten PCs with the Sentinel-3 and SARAL/AltiKa datasets, respectively. Finally, we analyzed the Ka and Ku band altimeter waveform shapes for each identified class to better understand snow and ice sensitivity to waveforms.