Robust Error Research Articles

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 < 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 < 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 < 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 < 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.

Neural Operator Variational Inference Based on Regularized Stein Discrepancy for Deep Gaussian Processes.

Deep Gaussian process (DGP) models offer a powerful nonparametric approach for Bayesian inference, but exact inference is typically intractable, motivating the use of various approximations. However, existing approaches, such as mean-field Gaussian assumptions, limit the expressiveness and efficacy of DGP models, while stochastic approximation can be computationally expensive. To tackle these challenges, we introduce neural operator variational inference (NOVI) for DGPs. NOVI uses a neural generator to obtain a sampler and minimizes the regularized Stein discrepancy (RSD) between the generated distribution and true posterior in L2 space. We solve the minimax problem using Monte Carlo estimation and subsampling stochastic optimization techniques and demonstrate that the bias introduced by our method can be controlled by multiplying the Fisher divergence with a constant, which leads to robust error control and ensures the stability and precision of the algorithm. Our experiments on datasets ranging from hundreds to millions demonstrate the effectiveness and the faster convergence rate of the proposed method. We achieve a classification accuracy of 93.56 on the CIFAR10 dataset, outperforming state-of-the-art (SOTA) Gaussian process (GP) methods. We are optimistic that NOVI possesses the potential to enhance the performance of deep Bayesian nonparametric models and could have significant implications for various practical applications.

Does gender impact the relationship between perceived value and intentions of use of natural processing models?

Purpose In the era of artificial intelligence, natural language processing (NLP) models are revolutionizing numerous sectors. This research aims to explore the perceived value of them among university students. In particular, it aims to investigate how gender may influence students’ intention to use these models in educational contexts, highlighting potentially significant differences that could inform the implementation and adoption of educational technologies. Design/methodology/approach This study investigates the relationship between perceived value and students' intention to adopt NLP models, considering gender as a moderator. The research involves 562 students from the University of Salerno, in Italy, and uses confirmatory factor analysis to evaluate the reliability and validity of the measurement scales. A regression model with robust errors is used to explore the moderating role of gender on the relationship between perceived value and intentions of use of NLP models. Findings The results reveal a significant positive association between perceived value and intention to use NLP models, confirming that students with higher perceived value are more likely to adopt these technologies. Furthermore, gender moderates this relationship, indicating that females are less prone to use NLP models than male counterparts. Originality/value Research takes on a significant role in the academic field, underlining the importance of adapting teaching practices to the increasingly widespread digitalization. The inclusion of NLP models in university programs emerges as a possible improvement of the learning experience, ensuring cutting-edge education in tune with the needs of the digital society.

COVID-19 Vaccine Hesitancy and Misinformation Endorsement among a Sample of Native Spanish-Speakers in the US: A Cross-Sectional Study.

Research on COVID-19 vaccine hesitancy and misinformation endorsement among Spanish-speaking Americans is limited. This cross-sectional study used a Spanish-language survey from May-August 2021 among 483 Spanish speakers living in the US and Puerto Rico. We applied multivariable Poisson regression with robust error variances to assess the association between independent variables and binary outcomes for vaccine acceptance versus hesitance, as well as misinformation endorsement. Vaccine acceptance was associated with COVID-19 risk perception score (PR = 1.7 high vs. low perceived risk), opinion of government transparency (PR = 2.2 very transparent vs. not transparent), and trust in vaccine information (PR = 1.8 high vs. low). There was also an interaction between time spent on social media and social media as a main source of COVID-19 information (p = 0.0484). Misinformation endorsement was associated with opinion about government transparency (PR = 0.5 moderately vs. not transparent), trust in vaccine information (PR = 0.5 high vs. low trust), social media impact on vaccine confidence (PR = 2.1 decreased vs. increased confidence), distrust vaccines (PR = 1.9 distrust vs. trust), using vaccine information from Facebook (PR = 1.4 yes vs. no), and time spent on social media by those using social media as main source of COVID-19 vaccine information (p = 0.0120). Vaccine acceptance in respondents with high misinformation endorsement scores was 0.7 times those with low scores. These findings highlight the importance of effective information dissemination, the positive role of social media, and government transparency in boosting vaccine uptake among Spanish speakers in the US.

Improved Cupressus sempervirens L. galls for methylene blue removal: adsorption kinetics optimisation using the DA-LS algorithm, characterisation, and machine learning modeling

ABSTRACT In this study, an investigation was conducted on the effectiveness of three bioadsorbents – galbuli of Cupressus sempervirens L. almond shells, and Luffa – for removing methylene blue (MB) from water. Various activation techniques and operational conditions were employed to enhance the adsorption capacity. The study focused on adsorption kinetics and equilibrium capacity. The results showed that microwave-dried galbuli of Cupressus sempervirens L. exhibited the highest adsorption capacity of 38.05 mg/g with an adsorption efficiency of 17.4%. To improve this capacity, the Dragonfly Algorithm-integrated least squares (DA-LS) was proposed to optimise the fitting of 32 adsorption isotherm models, which included a proposed modified Langmuir model. After optimisation, the sixth chemical treatment of Cupressus sempervirens L. reached a Langmuir isotherm qmax value of 84.44 mg/g, suggesting the high efficiency of the bioadsorbent compared to previous studies. Characterisation using microscopy and ATR-FTIR techniques revealed that chemical modifications led to rougher, microporous cellulose fibres and significant changes in the chemical structure, potentially enhancing the surface area and adsorption efficiency. To predict the adsorption capacity, the Support Vector Machine for Regression with DA (SVMR-DA) was utilised, achieving a root mean square error (RMSE) of 1.357 and an R2 of 0.9913. This high accuracy indicates a reliable model with a robust error distribution. These results suggest that Cupressus sempervirens L. can be an effective bioadsorbent for water treatment, with significant potential for industrial application.

Extended Kalman filter-based robust roll angle estimation method for spinning vehicles

Attitude measurement is a basic technique for monitoring vehicle motion states and safety. The spin motion of a vehicle couples the attitude angles with each other, which has an impact on the navigation and control of the vehicle. Global navigation satellite system (GNSS) signals-based roll angle measurement methods are important for vehicle attitude measurement. Most of existing studies use continuous signal power, but the case of loop lock loss leading to discontinuous power reception has not been considered. A robust estimation method for the roll angle based on the Tukey weight function is proposed to improve the measurement accuracy in cases of discontinuous reception. The characteristics of the GNSS signals, the geometric relationship between the signal power and roll angle of the vehicle are discussed. By installing a GNSS receiver with a single patched antenna on a rotating platform with a controllable rolling speed, the proposed method was verified by experiments. The robust estimation errors of different weight functions are analyzed. According to the characteristics of the gross measurement errors, a robust estimation method of multisatellite power observations is proposed to obtain a high-precision and stable estimation of the vehicle roll angle. The results show that the proposed algorithm can improve the accuracy of roll angle estimation even with gross measurement errors. As a result of the experiments, the estimation errors of the algorithm are 6.57° at a confidence level of 68 % and 15.49°at the confidence level of 95 %. In contrast, they are 11.38° and 37.31° for the traditional LS method. Moreover, the estimation accuracy of the algorithm is not significantly correlated with the vehicle rotational speed. Therefore, the vehicle roll angle can be estimated with high accuracy under a variety of rotational speeds.

Clinical outcomes and phenotypes of respiratory failure in older subjects admitted to an acute care geriatric hospital ward.

Respiratory failure (RF) is frequent in hospitalized older patients, but was never systematically investigated in large populations of older hospitalized patients. We conducted a retrospective administrative study based on hospitalizations of a Geriatrics Unit regarding 2014, 2015, and 2016. Patients underwent daily screening for hypoxia. Hospital discharge records were coded through a standardized methodology. RF, defined as documented hypoxia on room air, was always coded, whenever present. We investigated how RF affected clinical outcomes, whether RF grouped into specific comorbidity phenotypes, and how phenotypes associated with the outcomes. RF was coded in 48.6% of the 1,810 hospitalizations. RF patients were older and more frequently had congestive heart failure (CHF: 49 vs 23%), chronic obstructive pulmonary disease (COPD: 27 vs 6%), pneumonia (14 vs 4%), sepsis (12 vs 7%), and pleural effusion (6 vs 3%), than non-RF patients. RF predicted longer length of stay (a-Beta 2.05, 95% CI 1.4-2.69; p < 0.001) and higher in-hospital death/intensive care units (ICU) need (aRR 7.12, 5-10.15; p < 0.001) after adjustment for confounders (linear and Poisson regression with robust error variance). Among RF patients, cerebrovascular disease, cancer, electrolyte disturbances, sepsis, and non-invasive ventilation predicted increased, while CHF and COPD predicted decreased in-hospital death/ICU need. The ONCO (cancer) and Mixed (cerebrovascular disease, dementia, pneumonia, sepsis, electrolyte disturbances, bedsores) phenotypes displayed higher in-hospital death/ICU need than CARDIO (CHF) and COPD phenotypes. In this study, RF predicted increased hospital death/ICU need and longer hospital stay, but also reflected diverse underlying conditions and clinical phenotypes that accounted for different clinical courses.