Robust Error Research Articles

Individual & Joint Associations of Sexual Stigma and Mental Distress with PrEP Uptake, Adherence and Persistence Among US Gay and Bisexual Men

BackgroundSexual stigma, mental health disorders, and socioeconomic disparities present important yet incompletely understood barriers to PrEP adoption among gay men and other men who have sex with men (MSM). This study examines how these factors interact and affect PrEP uptake, adherence, and persistence among MSM. MethodsData from the 2018 and 2019 American Men's Internet Survey cycles, involving 6,907 adult MSM eligible for PrEP, were analyzed. We assessed sexual stigma heterogeneity among this group using latent class analysis and investigated individual relationships between i) stigma class membership, ii) mental distress, and PrEP engagement (past-year use, adherence, and persistence) using Poisson regression with a robust error variance, considering potential variations based on poverty status. The combined associations of sexual stigma and mental distress with PrEP engagement was evaluated using inverse probability weighting. ResultsFour distinct sexual stigma classes were identified, each exhibiting varied associations with PrEP engagement. Associations with mental distress lost statistical significance after adjusting for confounders. However, having both mental distress and sexual stigma was associated with lower past-year PrEP use, with the strongest association observed for those with anticipated healthcare stigma class membership and mental distress (aPR 0.53 [95% CI: 0.37, 0.76]). Sexual stigma accompanied by mental distress was also associated with significantly increased poor PrEP adherence, particularly among those with family and general social stigma class membership (aPR 2.31 [95% CI: 1.08, 4.97]). ConclusionsPsychosocial factors exert synergistic impacts on PrEP engagement among MSM. Tailored interventions addressing these subtleties may effectively optimize PrEP uptake and improve consistency of use among MSM.

Adaptive Arithmetic Coding-Based Encoding Method Toward High-Density DNA Storage.

With the rapid advancement of big data and artificial intelligence technologies, the limitations inherent in traditional storage media for accommodating vast amounts of data have become increasingly evident. DNA storage is an innovative approach harnessing DNA and other biomolecules as storage mediums, endowed with superior characteristics including expansive capacity, remarkable density, minimal energy requirements, and unparalleled longevity. Central to the efficient DNA storage is the process of DNA coding, whereby digital information is converted into sequences of DNA bases. A novel encoding method based on adaptive arithmetic coding (AAC) has been introduced, delineating the encoding process into three distinct phases: compression, error correction, and mapping. Prediction by Partial Matching (PPM)-based AAC in the compression phase serves to compress data and enhance storage density. Subsequently, the error correction phase relies on octal Hamming code to rectify errors and safeguard data integrity. The mapping phase employs a "3-2 code" mapping relationship to ensure adherence to biochemical constraints. The proposed method was verified by encoding different formats of files such as text, pictures, and audio. The results indicated that the average coding density of bases can be up to 3.25 per nucleotide, the GC content (which includes guanine [G] and cytosine [C]) can be stabilized at 50% and the homopolymer length is restricted to no more than 2. Simulation experimental results corroborate the method's efficacy in preserving data integrity during both reading and writing operations, augmenting storage density, and exhibiting robust error correction capabilities.

Association between procrastination and learning strategies in medical students in a hybrid problem-based and lecture-based learning curriculum.

Procrastination is characterized by the deliberate postponement of assigned educational tasks and is correlated with low academic achievement and depression. Concern about procrastination is particularly high among medical students, as it has a strong association with aspects such as low self-efficacy, lack of organization, low intrinsic motivation, inefficient effort regulation and time management problems. On the other hand, it was found that students' use of study strategies is significantly related to better academic results. The relationship between students' tendency to procrastinate and the adoption of effective study strategies remains little explored, leaving a critical space for investigation. This study aims to fill this gap by exploring how procrastination affects the selection and effectiveness of study strategies adopted by students. This cross-sectional study was conducted in Brazil and included medical students from the first to the seventh semester of the Unichrsitus Medical School. The validated procrastination scale and the Learning and Study Strategies Inventory were used. Generalized linear regression multivariate models with robust errors were used to verify the association between the study variables. 447 students participated, 70.2% of whom were female, with an average age of 23years. The domain of "study aids" scored higher among younger students, who self-referred as black and who studied in private schools prior to the Medical School. Higher procrastination scores were statistically associated with higher main idea selection, concentration, time organization and anxiety scores and with lower study aids and study preoccupation scores (p values < 0.05). In addition, active methodology was associated with higher scores in the domains of study aids and time organization. Procrastination is associated with the study strategies used by medical students, which can be modified through training and ultimately improve their performance. Students in traditional models, who are older, white and from public schools may especially benefit from this training.

Enhancing Communication Security in Drones Using QRNG in Frequency Hopping Spread Spectrum

This paper presents a novel approach to enhancing the security and reliability of drone communications through the integration of Quantum Random Number Generators (QRNG) in Frequency Hopping Spread Spectrum (FHSS) systems. We propose a multi-drone framework that leverages QRNG technology to generate truly random frequency hopping sequences, significantly improving resistance against jamming and interception attempts. Our method introduces a concurrent access protocol for multiple drones to share a QRNG device efficiently, incorporating robust error handling and a shared memory system for random number distribution. The implementation includes secure communication protocols, ensuring data integrity and confidentiality through encryption and Hash-based Message Authentication Code (HMAC) verification. We demonstrate the system’s effectiveness through comprehensive simulations and statistical analyses, including spectral density, frequency distribution, and autocorrelation studies of the generated frequency sequences. The results show a significant enhancement in the unpredictability and uniformity of frequency distributions compared to traditional pseudo-random number generator-based approaches. Specifically, the frequency distributions of the drones exhibited a relatively uniform spread across the available spectrum, with minimal discernible patterns in the frequency sequences, indicating high unpredictability. Autocorrelation analyses revealed a sharp peak at zero lag and linear decrease to zero values for other lags, confirming a general absence of periodicity or predictability in the sequences, which enhances resistance to predictive attacks. Spectral analysis confirmed a relatively flat power spectral density across frequencies, characteristic of truly random sequences, thereby minimizing vulnerabilities to spectral-based jamming. Statistical tests, including Chi-squared and Kolmogorov-Smirnov, further confirm the unpredictability of the frequency sequences generated by QRNG, supporting enhanced security measures against predictive attacks. While some short-term correlations were observed, suggesting areas for improvement in QRNG technology, the overall findings confirm the potential of QRNG-based FHSS systems in significantly improving the security and reliability of drone communications. This work contributes to the growing field of quantum-enhanced wireless communications, offering substantial advancements in security and reliability for drone operations. The proposed system has potential applications in military, emergency response, and secure commercial drone operations, where enhanced communication security is paramount.

Fetal growth ultrasound in obese patients for the detection of growth abnormalities.

To examine the impact of maternal obesity on fetal growth abnormalities including fetal growth restriction (FGR) and large for gestational age (LGA) fetuses. Secondary analysis from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b). The study excluded individuals with pregestational or gestational diabetes, chronic hypertension, and other major maternal medical conditions. Ultrasound assessments were performed at 16 - 21 and 22 - 29 weeks of gestation. Our exposure was the presence of pre-pregnancy obesity. Our primary outcome was rates of fetal growth abnormalities identified by ultrasound, defined as FGR (estimated fetal weight [EFW] or abdominal circumference < 10th percentile) or LGA (EFW > 90 th percentile) among obese compared to non-obese women. A secondary analysis was performed after limiting ultrasound performed from 28-29 weeks. To estimate adjusted relative risks (aRR) with 95% confidence intervals (95%CIs), we used generalized linear models with Poisson distribution and log link using robust error variance, adjusting for the predefined covariates. Of 7,354 participants, 1,443 (19.6%) had pre-pregnancy obesity while 5,911 (80.4%) did not. Pre-pregnancy obesity compared with normal weight was associated with an increased risk of fetal growth abnormalities both at 16-21 weeks (16.0% vs. 13.2%; aRR 1.23; 95%CI 1.06-1.42) and 22-29 weeks (16.0% vs. 12.1%; aRR 1.33; 95%CI 1.14-1.54). Furthermore, pre-pregnancy obesity compared with normal weight was associated with an increased risk of LGA both at 16-21 weeks (12.5% vs. 10.3%; aRR 1.24; 95%CI 1.05-1.47) and 22-29 weeks (10.6% vs. 6.9%; aRR 1.66; 95%CI 1.38-2.01). In a secondary analysis limited to the ultrasound 28-29 weeks, both fetal growth abnormalities and LGA were associated with the presence of obesity. In any of the analyses, pre-pregnancy obesity was not associated with FGR compared to normal weight. Maternal obesity is associated with an increased risk of fetal growth abnormalities and LGA fetuses.

A robust adaptive error state Kalman filter for MEMS IMU attitude estimation under dynamic acceleration

Accurate estimation of attitude (pitch, roll) is a prerequisite for ensuring safe navigation during vehicle control execution. In dynamic environments, the presence of acceleration often degrades the accuracy and robustness of attitude estimation using traditional algorithms with Micro-Electro-Mechanical Systems (MEMS) Inertial Measurement Unit (IMU). This paper proposes a robust adaptive error state Kalman filter (RAESKF) algorithm for attitude estimation of MEMS IMU under dynamic acceleration conditions. The RAESKF algorithm decomposes the true attitude Direction Cosine Matrix (DCM) into nominal and error components. An error state Kalman filter is utilized to fuse real-time measurements from MEMS gyroscope and accelerometer, estimating the error component, which is then used to correct the nominal attitude DCM. Furthermore, within the error state Kalman filtering framework, a dynamic acceleration robust adaptive adjustment strategy is implemented. This strategy relies on real-time data monitoring, threshold-based decision-making, and switching mechanisms. It adaptively selects between dynamic acceleration model compensation and online adjustment of the measurement noise covariance matrix. The primary objective of this strategy is to mitigate the impact of disturbance induced by dynamic acceleration on attitude estimation, thereby enhancing the accuracy and robustness. Laboratory rotation experiments have demonstrated that the algorithm improved pitch and roll measurement accuracy by at least 8.81% and 11.69%, respectively, under rotational conditions. In dynamic acceleration conditions, pitch and roll measurement accuracy improved by at least 42.76% and 67.21%, respectively.

Enhancing Erasure Resilience in Reed-Solomon Codes: Theory and Applications in Data Storage Systems

Reed-Solomon (RS) codes are widely utilized in data storage and communication systems due to their robust error detection and correction capabilities. However, traditional RS codes encounter challenges in addressing the increasing data corruption rates demanded by modern storage systems. This paper aims to overcome these limitations by modifying and extending the structure of traditional RS codes, particularly enhancing their recovery capabilities in the face of significant data loss. We begin by reviewing the theoretical foundations of RS codes and existing extension methods and discussing emerging technologies integrated into RS codes. We then present detailed methodologies for RS code encoding, erasure recovery mechanisms, soft decision decoding, and interleaving coding techniques, followed by a series of experiments designed to test the proposed methods. The experimental results indicate that soft-decision decoding outperforms traditional hard-decision decoding under high signal-to-noise ratio conditions, albeit with increased computational complexity as the list of candidate codewords grows. Interleaved Reed-Solomon (IRS) coding offers improved performance under low signal-to-noise ratio conditions but may introduce additional system complexity due to the interleaving and deinterleaving processes. We conclude with a summary of the research findings, a discussion of the study’s limitations, and suggestions for future research directions.

A frequency-independent absorption function surrogate for perfectly matched layer in exterior acoustics

In many engineering applications, the solution of acoustic wave problems in the infinite domain is required over a broad frequency range with densely sampled increments. In order to achieve efficient numerical simulations via a spatial discretization, e.g. finite element method, additional artificial absorbing boundaries are necessary to truncate the computational domain into appropriate bounded sizes. One of the most commonly used non-reflecting techniques to attenuate propagating waves is known as the perfectly matched layer. However, the system matrices arising from the finite element treatment of the Helmholtz equation in the absorbing layers are frequency-dependent, implying that they must be formed and inverted at each frequency of interest. Such a procedure is rather troublesome for frequency sweeps. To address this, a surrogate of perfectly matched layers is proposed, which enables the corresponding system matrices to be independent of the frequency. Moreover, it avoids the use of a relatively large computational domain and relatively thick enclosed layers at low frequencies, thus improving the ability of perfectly matched layers across the entire frequency range. After that, an adaptive projection-based model order reduction scheme is further developed to reduce the computational complexity of exterior acoustic systems. A robust error indicator based on the relative error of two constructed reduced order models is accordingly introduced. The performance of the present solution framework is discussed and compared with other implementation strategies, in the context of multi-frequency solution of two-dimensional test models with single or multiple scatterers.

7669 Higher Serum Uric Acid Levels Are Associated With a Deleterious Metabolic and Inflammatory Profile in Brazilian Adolescents: An Exploratory Cross-Sectional Analysis

Abstract Disclosure: F.Q. Iorra: None. M.P. Guahnon: None. P.G. Rodrigues: None. A.T. Barcelos: None. F.V. Cureau: None. M. Drehmer: None. B.D. Schaan: None. Introduction: The association of high serum uric acid (sUA) with metabolic syndrome (MetS) and its components have been widely studied, but there are still gaps in how this breakdown product of purine metabolism might refine cardiovascular risk assessment and correlate with other cardiovascular disease biomarkers, especially in children and adolescents. Objective: To evaluate if sUA is associated with metabolic syndrome components and inflammatory markers in Brazilian adolescents. Methods: For this cross-sectional study, 786 individuals aged 12 to 17 years old, previously enrolled in the Study of Cardiovascular Risk in Adolescents (ERICA) - a Brazilian nationwide school based study, and who were from the city of Porto Alegre, had their sUA measured from blood samples that were stored in a biorepository. Anthropometric, biochemical and blood pressure data were collected. MetS diagnosis was based on the International Diabetes Federation age-specific criteria (2005), and insulin resistance was assessed by the HOMA-IR. In accordance with a non-parametric distribution, sUA was divided into quartiles (3.7 mg/dL, 4.4 mg/dL, 5.3 mg/dL for the 25th, 50th, and 75th percentiles, respectively) for the analysis. A linear regression model and a Poisson regression model with robust error variance were used, both adjusted for age, sex and skin color. Results: Participants were 14.8 ± 1.5 years-old, predominantly women (61.7%), self-identified as white skin color (72%) and eutrophic (66.9%). Through the linear regression model, significant positive associations were found between high sUA levels and body mass index Z-score, waist circumference, systolic and diastolic blood pressure, total cholesterol, triglycerides, HOMA-IR and C-reactive protein, and significant negative associations were observed for HDL cholesterol and adiponectin. No association was found between sUA and glucose or HbA1c. We also computed a metabolic risk score as the mean Z score of waist circumference, systolic blood pressure, HDL cholesterol (negative Z score), triglycerides and glucose, which was positive related to sUA (β ± SE = 0.13 ± 0.02; p &amp;lt; 0.001). Finally, the Poisson regression model was applied to estimate the prevalence ratios (PR) for MetS and its components, between adolescents with sUA in the 4th quartile to those in the 1st quartile. An association was observed for MetS (PR 6.37, 95% CI 1.39 - 29.21, p 0.017), high waist circumference (PR 4.61, 95% CI 2.55 - 8.36, p &amp;lt; 0.001) and increased triglycerides (PR 4.76, 95% CI 1.47 - 15.44, p 0.009). Conclusion: High sUA levels were associated with a worse metabolic and inflammatory profile, as well as a greater prevalence of MetS and some of its components in adolescents. Therefore, uric acid should be considered as a potential additional marker of cardiovascular risk in this population. Support: CNPq, CAPES, FIPE, FAPERGS. Presentation: 6/1/2024

9193 Higher Serum Uric Acid Levels Are Associated With a Deleterious Metabolic and Inflammatory Profile in Brazilian Adolescents: An Exploratory Cross-Sectional Analysis

Abstract Disclosure: F.Q. Iorra: None. M.P. Guahnon: None. P.G. Rodrigues: None. A.T. Barcelos: None. F.V. Cureau: None. M. Drehmer: None. B.D. Schaan: None. Introduction: The association of high serum uric acid (sUA) with metabolic syndrome (MetS) and its components have been widely studied, but there are still gaps in how this breakdown product of purine metabolism might refine cardiovascular risk assessment and correlate with other cardiovascular disease biomarkers, especially in children and adolescents. Objective: To evaluate if sUA is associated with metabolic syndrome components and inflammatory markers in Brazilian adolescents. Methods: For this cross-sectional study, 786 individuals aged 12 to 17 years old, previously enrolled in the Study of Cardiovascular Risk in Adolescents (ERICA) - a Brazilian nationwide school based study, and who were from the city of Porto Alegre, had their sUA measured from blood samples that were stored in a biorepository. Anthropometric, biochemical and blood pressure data were collected. MetS diagnosis was based on the International Diabetes Federation age-specific criteria (2005), and insulin resistance was assessed by the HOMA-IR. In accordance with a non-parametric distribution, sUA was divided into quartiles (3.7 mg/dL, 4.4 mg/dL, 5.3 mg/dL for the 25th, 50th, and 75th percentiles, respectively) for the analysis. A linear regression model and a Poisson regression model with robust error variance were used, both adjusted for age, sex and skin color. Results: Participants were 14.8 ± 1.5 years-old, predominantly women (61.7%), self-identified as white skin color (72%) and eutrophic (66.9%). Through the linear regression model, significant positive associations were found between high sUA levels and body mass index Z-score, waist circumference, systolic and diastolic blood pressure, total cholesterol, triglycerides, HOMA-IR and C-reactive protein, and significant negative associations were observed for HDL cholesterol and adiponectin. No association was found between sUA and glucose or HbA1c. We also computed a metabolic risk score as the mean Z score of waist circumference, systolic blood pressure, HDL cholesterol (negative Z score), triglycerides and glucose, which was positive related to sUA (β ± SE = 0.13 ± 0.02; p &amp;lt; 0.001). Finally, the Poisson regression model was applied to estimate the prevalence ratios (PR) for MetS and its components, between adolescents with sUA in the 4th quartile to those in the 1st quartile. An association was observed for MetS (PR 6.37, 95% CI 1.39 - 29.21, p 0.017), high waist circumference (PR 4.61, 95% CI 2.55 - 8.36, p &amp;lt; 0.001) and increased triglycerides (PR 4.76, 95% CI 1.47 - 15.44, p 0.009). Conclusion: High sUA levels were associated with a worse metabolic and inflammatory profile, as well as a greater prevalence of MetS and some of its components in adolescents. Therefore, uric acid should be considered as a potential additional marker of cardiovascular risk in this population. Support: CNPq, CAPES, FIPE, FAPERGS. Presentation: 6/1/2024

A comprehensive analysis of fruit, vegetable, and legume consumption and the risk of hypertension: results from the KoGES_CAVAS cohort.

This study aimed to investigate the association between total consumption of fruits (F), vegetables (V), and legumes (L) and their subgroups and hypertension risk in adults aged ≥ 40years in the Cardiovascular Disease Association Study (CAVAS). We analyzed data from 10,325 normotensive participants using cumulative average dietary consumption from repeated food frequency questionnaires during the follow-up. Incidence rate ratios (IRRs) were estimated with a modified Poisson regression model and a robust error estimator to evaluate the association between hypertension risk and total consumption of fruits, vegetables, and legumes, as well as their 17 subgroups. During an average follow-up of 5.20years, 2159 cases of hypertension were recorded. Total consumption of FVL, FV, fruits, vegetables, and legumes showed overall inverse trends with hypertension risk. Considering multiplicity, fruit consumption was inversely associated with hypertension risk in both men (IRR 0.64; 95% CI 0.52-0.79) and women (IRR 0.76; 95% CI 0.64-0.91). Vegetables were inversely associated with hypertension in women (IRR 0.67; 95% CI 0.53-0.86). Most subgroups showed inverse associations, especially in men with overweight/obesity. However, frequent pickled green leafy vegetable consumption was positively associated with hypertension risk in postmenopausal women but not in premenopausal women (Pinteraction = 0.0004). Consumption of FVL, including their subgroups, generally shows inverse associations with hypertension risk. However, caution is advised for recommending pickled vegetables, particularly for postmenopausal women, due to the potential adverse effects of sodium. The benefits of these foods in preventing hypertension are especially pronounced in men with overweight/obesity.

Factor analysis of the feeding and eating in AutiSm Together Assessment

BackgroundAutistic children experience high rates of feeding challenges, negatively affecting their.health, eating patterns, and social eating experiences. The Feeding and Eating in AutiSm Together; FEAST, a caregiver-report questionnaire, was developed to characterize feeding challenges in autistic children ages 2 to 12 years. The purpose of this study is to determine the construct validity of the FEAST assessment using a large national sample of autistic children. MethodA large national sample (N = 396) of caregivers completed the online survey. An ordinal confirmatory factor model using a robust weighted least squares approach validated the four predicted groupings of feeding challenges (sensory processing; behavior; oral.motor skills; and gastrointestinal) with generally strong loadings onto the four distinct.factors. ResultsModel fit statistics indicated good model fit (Robust Root Mean Square Error of.Approximation=.080, Robust Comparative Fit Index =.909, Robust Tucker-Lewis.Index=.901) Findings provide preliminary confirmation of the construct validity of the.FEAST assessment to characterize feeding difficulties for autistic children ages 2–12. Small to medium correlations between all factors indicate items successfully targeted.four unique areas of feeding challenge. For all factors, the largest correlation was with.behavior. ConclusionAssessments developed to address the complex feeding and mealtime challenges for.autistic children are essential to identify and integrate the most appropriate intervention.approaches. FEAST offers researchers and clinicians with a comprehensive and psychometrically sound assessment tool to address autistic children’s unique feeding.challenges.

A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes.

The application of high-throughput chromosome conformation capture (Hi-C) technology enables the construction of chromosome-level assemblies. However, the correction of errors and the anchoring of sequences to chromosomes in the assembly remain significant challenges. In this study, we developed a deep learning-based method, AutoHiC, to address the challenges in chromosome-level genome assembly by enhancing contiguity and accuracy. Conventional Hi-C-aided scaffolding often requires manual refinement, but AutoHiC instead utilizes Hi-C data for automated workflows and iterative error correction. When trained on data from 300+species, AutoHiC demonstrated a robust average error detection accuracy exceeding 90%. The benchmarking results confirmed its significant impact on genome contiguity and error correction. The innovative approach and comprehensive results of AutoHiC constitute a breakthrough in automated error detection, promising more accurate genome assemblies for advancing genomics research.

Customer adoption of Chat GPT for web development and programming assistance in the Zimbabwe tech industry

ChatGPT, an advanced conversational AI model by OpenAI, signifies a significant leap in human-computer interaction. Optimized for dialogue, ChatGPT has the potential to transform web development and programming support. In Zimbabwe, 60% of IT programmers express concerns about UI/UX design, while 70% face challenges in service quality due to software flaws and inadequate testing. This study investigates ChatGPT's application in Zimbabwe's tech industry for web development and programming support, and its impact on organizational performance. Employing an integrated Delone and McLean IS Success Model, the research examines adoption trends, barriers, and benefits of integrating ChatGPT into development workflows.A quantitative approach was utilized, employing survey data and statistical methods. A 5-point Likert Scale survey was distributed to 30 Zimbabwean ICT workers. Data analysis with SmartPLS 3.0 included descriptive and confirmatory factor analyses to assess reliability (Cronbach's alpha, composite reliability) and validity (factor loadings, AVE, HTMT ratio). Results indicate that ChatGPT significantly influences system, information, and service quality, enhancing user satisfaction and organizational benefits, with system quality exerting the strongest impact. Moreover, system quality positively affects organizational performance, though the moderating role of flexible organizational culture was insignificant. Recommendations include enhancing training data tailored to local technological needs, integrating real-time data sources, offering a paid version for updated data, ensuring robust error handling for service quality, providing educational resources, implementing feedback mechanisms, conducting developer training programs, and promoting cross-functional collaboration.

Investigating the psychometric properties of the Persian version of the Quality of Life Questionnaire for Women Infected with HPV (EQUALI-HPV)

IntroductionPeople with human papiloma virus (HPV) struggle with numerous challenges and needs in physical, and psychological aspects of quality of life related to this virus. Several studies have recommended counseling interventions to improve the quality of life for these individuals. There is also a need for standardized and normalized instruments in Iran to evaluate the effect of educational and therapeutic interventions on the quality of life of these patients. Therefore, this study was conducted in gynecological cancer clinics in Kerman and Mashhad to investigate the psychometric properties of the Persian version of the “Quality of Life Questionnaire for Women Infected with HPV”.MethodsThis study cross-sectional study included 580 women infected with HPV referred to Kerman and Mashhad’s gynecologic cancer clinics. The samples were selected using convenience sampling method in 2023. Content validity, face validity, and construct validity were assessed using explanatory factor analysis (EFA) and confirmatory factor analysis (CFA).ResultsThe results of the content validity assessment, which included the Content Validity Index (CVI) and the Content Validity Ratio (CVR), indicated strong content validity. Additionally, qualitatively confirmed face validity, further supports these findings. The results of the EFA revealed that the Persian version of the EQUALI-HPV questionnaire has a 6-factor structure, with 34 items remaining from the 54 items. These 6 factors accounted for 48.9% of the variance and were confirmed by confirmatory factor analysis and using robust root mean square error of approximation (RMSEA = 0.054), comparative fit index (CFI = 0.928), and Tucker-Lewis index (TLI = 0.920). The content validity results showed that all the items had a good validity ratio and index. Cronbach’s alpha and Raykov’s rho were greater than 0.7 for all dimensions.ConclusionThe results showed that the Persian version of the “Quality of Life Questionnaire for Women Infected with HPV” had acceptable validity and reliability and can be utilized to measure the quality of life of these people and conduct psychological studies.

Active longevity and aging: dissecting the impacts of physical and sedentary behaviors on longevity and age acceleration.

To examine the associations of physical activity (PA) and sedentary behavior (SB) with longevity and age acceleration (AA) using observational and Mendelian randomization (MR) studies, and quantify the mediating effects of lipids. In Guangzhou Biobank Cohort Study (GBCS), PA and SB were assessed by the Chinese Version of the International Physical Activity Questionnaire. Longevity was defined as participants whose age at follow-up or at death was at or above the 90th age percentile. AA was defined as the residual resulting from a linear model that regressed phenotypic age against chronological age. Linear regression and Poisson regression with robust error variance were used to assess the associations of total and specific PA in different intensities, and SB with AA and longevity, yielding βs or relative risks (RRs) and 95% confidence intervals (CIs). Two-sample MR was conducted to examine the causal effects. Mediation analysis was used to assess the mediating effects of lipids. Of 20,924 participants aged 50 + years in GBCS, during an average follow-up of 15.0years, compared with low PA, moderate and high PA were associated with higher likelihood of longevity (RR (95% CI): 1.56 (1.16, 2.11), 1.66 (1.24, 2.21), respectively), and also cross-sectionally associated with lower AA (β (95% CI): -1.43 (-2.41, -0.45), -2.09 (-3.06, -1.11) years, respectively). Higher levels of moderate PA (MPA) were associated with higher likelihood of longevity and lower AA, whereas vigorous PA (VPA) showed opposite effects. The association of PA with longevity observed in GBCS was mediated by low-density lipoprotein cholesterol (LDL-C) by 8.23% (95% CI: 3.58-39.61%), while the association with AA was mediated through LDL-C, triglycerides and total cholesterol by 5.13% (3.94-7.30%), 7.81% (5.98-11.17%), and 3.37% (2.59-4.80%), respectively. Additionally, in two-sample MR, SB was positively associated with AA (β (95% CI): 1.02 (0.67, 1.36) years). PA showed protective effects on longevity and AA, with the effects being partly mediated through lipids. Conversely, SB had a detrimental impact on AA. MPA was associated with higher likelihood of longevity and reduced AA, whereas VPA showed adverse effects. Our findings reinforce the recommendation of "sit less and move more" to promote healthy longevity, and highlight the potential risks associated with VPA in the elderly.

Association of in vitro fertilization with severe maternal morbidity in low-risk patients without comorbidities

To determine whether an association exists between invitro fertilization (IVF) and severe maternal morbidity among low-risk pregnant patients. Retrospective cohort study. Academic healthcare system. Low-risk pregnant patients who delivered between January 2019 and December 2022. Low-risk was defined as having an obstetric comorbidity index score of 0. Invitro fertilization. The primary outcome (dependent variable) was any severe maternal morbidity. The secondary outcome was the need for a cesarean delivery. A modified Poisson regression with robust error variance was used to model the probability of severe maternal morbidity as a function of IVF. Risk ratios and their associated 95% confidence intervals (CIs) were computed. An α value of 0.05 was considered statistically significant. A total of 39,668 pregnancies were included for analysis, and 454 (1.1%) were conceived by IVF. The overall severe maternal morbidity rate was 2.4% (n = 949), with the most common indicator being blood transfusion. The overall cesarean delivery rate was 18.8% (n = 7,459). On modified Poisson regression, IVF-conceived pregnancies were associated with 2.56 times the risk of severe maternal morbidity (95% CI, 1.73-3.79) and 1.54 times the risk of having a cesarean delivery (95% CI, 1.37-1.74) compared with non-IVF pregnancies. Invitro fertilization is associated with higher rates of severe maternal morbidity, primarily the need for a blood transfusion, and cesarean delivery in low-risk pregnancies without major comorbidities. Recognizing this association allows healthcare providers to implement proactive measures for better monitoring and tailored postpartum care.

False Discovery Rate Control for Lesion-Symptom Mapping With Heterogeneous Data via Weighted p-Values.

Lesion-symptom mapping studies provide insight into what areas of the brain are involved in different aspects of cognition. This is commonly done via behavioral testing in patients with a naturally occurring brain injury or lesions (e.g., strokes or brain tumors). This results in high-dimensional observational data where lesion status (present/absent) is nonuniformly distributed, with some voxels having lesions in very few (or no) subjects. In this situation, mass univariate hypothesis tests have severe power heterogeneity where many tests are known a priori to have little to no power. Recent advancements in multiple testing methodologies allow researchers to weigh hypotheses according to side information (e.g., information on power heterogeneity). In this paper, we propose the use of p-value weighting for voxel-based lesion-symptom mapping studies. The weights are created using the distribution of lesion status and spatial information to estimate different non-null prior probabilities for each hypothesis test through some common approaches. We provide a monotone minimum weight criterion, which requires minimum a priori power information. Our methods are demonstrated on dependent simulated data and an aphasia study investigating which regions of the brain are associated with the severity of language impairment among stroke survivors. The results demonstrate that the proposed methods have robust error control and can increase power. Further, we showcase how weights can be used to identify regions that are inconclusive due to lack ofpower.

Paternal Preconception Hepatitis B Virus Infection and Risk of Congenital Heart Disease in Offspring

Previous evidence suggests that maternal hepatitis B virus (HBV) infection during prepregnancy or pregnancy is associated with congenital heart diseases (CHDs) in offspring. However, the association of paternal HBV infection with CHDs is not well examined. To explore the association of paternal preconception HBV infection with CHDs in offspring. This retrospective cohort study used propensity score matching of data from the Chinese National Free Preconception Checkup Project (NFPCP) from January 1, 2010, to December 31, 2018. Male participants whose wives were aged 20 to 49 years, were uninfected with HBV, and successfully conceived within 1 year after prepregnancy examination were enrolled. Data were analyzed from March 2023 to February 2024. The primary exposure was paternal preconception HBV infection status, including uninfected, previous infection (both serum hepatitis B surface antigen and hepatitis B envelope antigen negative), and new infection (serum hepatitis B surface antigen positive). Maternal HBV immune status was further classified as immune or susceptible. The main outcome was CHDs, which were collected from the birth defect registration card of the NFPCP. Logistic regression with robust error variances was used to estimate the association between paternal preconception HBV infection and CHDs in offspring. A total of 6 675 540 couples participated in the NFPCP service. After matching husbands with and without preconception HBV infection in a 1:4 ratio, 3 047 924 couples (median age of husbands, 27 years [IQR, 25-30 years]) were included in this study. Of these couples, 0.025% had offspring with CHDs. Previous paternal HBV infection was independently associated with CHDs in offspring (adjusted relative risk [ARR], 1.40; 95% CI, 1.11-1.76) compared with no infection. Similar results were obtained in subgroup analyses according to maternal HBV immune status. Compared with couples with uninfected husbands and susceptible wives, the risk of CHDs in offspring among couples with previously HBV-infected husbands was similar in couples with wives with susceptible immune status (ARR, 1.49; 95% CI, 1.10-2.03) and in those with wives with immunity (ARR, 1.49; 95%CI, 1.07-2.09). A significantly higher CHD risk in offspring was found among couples with newly infected husbands and immune wives (ARR, 1.38; 95% CI, 1.05-1.82), but there was no difference in risk among those with newly infected husbands and susceptible wives (ARR, 0.99; 95% CI, 0.72-1.36). No interactions were found between maternal immune status and paternal HBV infection. In this cohort study using propensity score matching, previous paternal preconception HBV infection was associated with CHD risk in offspring. The findings suggest that personalized reproductive guidance regarding HBV screening and staying free of HBV infection should be provided for both wives and husbands.

Error-Free Arduino Communication: Integrating Hamming Code for UART Serial Transmission

Serial communication is a fundamental method for data transfer in electronic devices, particularly in Arduino-based systems. However, existing protocols, such as Universal Asynchronous Receiver/Transmitter (UART), often lack robust error detection mechanisms, leading to potential data integrity issues. This study aims to address the knowledge gap regarding error detection in UART communication by implementing Hamming Code, a well-established method for detecting and correcting single-bit errors. The research employs a systematic approach, including data encoding before transmission and decoding with error correction at the receiver end. The results demonstrate that the integration of the Hamming Code significantly enhances the reliability of data transmission, reducing error rates and improving overall system performance. The implications of this research extend to various applications requiring high data integrity, such as industrial control systems and Internet of Things (IoT) devices. By providing a practical solution to the challenges of error detection in serial communication, this study contributes to the advancement of reliable communication systems in modern technology.