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PeerJ 2024Eight fossil tetrapod footprints from lake-shore deposits in the Lower Jurassic Moenave Formation at the St. George Dinosaur Discovery Site (SGDS) in southwestern Utah...
Eight fossil tetrapod footprints from lake-shore deposits in the Lower Jurassic Moenave Formation at the St. George Dinosaur Discovery Site (SGDS) in southwestern Utah cannot be assigned to the prevalent dinosaurian (, , , , ) or crocodyliform () ichnotaxa at the site. The tridactyl and tetradactyl footprints are incomplete, consisting of digit- and digit-tip-only imprints. Seven of the eight are likely pes prints; the remaining specimen is a possible manus print. The pes prints have digit imprint morphologies and similar anterior projections and divarication angles to those of , an ichnotaxon found primarily in eolian paleoenvironments attributed to eucynodont synapsids. Although their incompleteness prevents clear referral to , the SGDS tracks nevertheless suggest a eucynodont track maker and thus represent a rare, Early Mesozoic occurrence of such tracks outside of an eolian paleoenvironment.
Topics: Fossils; Utah; Animals; Dinosaurs; Paleontology
PubMed: 38948213
DOI: 10.7717/peerj.17591 -
International Journal on Digital... 2024Due to the growing number of scholarly publications, finding relevant articles becomes increasingly difficult. Scholarly knowledge graphs can be used to organize the...
Due to the growing number of scholarly publications, finding relevant articles becomes increasingly difficult. Scholarly knowledge graphs can be used to organize the scholarly knowledge presented within those publications and represent them in machine-readable formats. Natural language processing (NLP) provides scalable methods to automatically extract knowledge from articles and populate scholarly knowledge graphs. However, NLP extraction is generally not sufficiently accurate and, thus, fails to generate high granularity quality data. In this work, we present TinyGenius, a methodology to validate NLP-extracted scholarly knowledge statements using microtasks performed with crowdsourcing. TinyGenius is employed to populate a paper-centric knowledge graph, using five distinct NLP methods. We extend our previous work of the TinyGenius methodology in various ways. Specifically, we discuss the NLP tasks in more detail and include an explanation of the data model. Moreover, we present a user evaluation where participants validate the generated NLP statements. The results indicate that employing microtasks for statement validation is a promising approach despite the varying participant agreement for different microtasks.
PubMed: 38948004
DOI: 10.1007/s00799-023-00360-7 -
Cureus May 2024A 59-year-old woman, who previously underwent surgery on her left long finger A1 pulley and left small finger distal interphalangeal joint for triggering and mallet...
A 59-year-old woman, who previously underwent surgery on her left long finger A1 pulley and left small finger distal interphalangeal joint for triggering and mallet deformity at another medical facility in March 2021, sought evaluation at an Orthopedics Hand clinic. She presented with limited finger movement, a flexion contracture, and difficulty extending her left long finger. Examination revealed an A2 pulley injury with extensive scar tissue. Subsequently, she underwent surgery to remove the scar tissue and reconstruct the A2 pulley using suture tape anchors. This case highlights the negative outcome following A1 pulley release due to an unintended A2 injury, resulting in significant scarring and an intrinsic plus digit posture. Additionally, it underscores the potential effectiveness of using non-absorbable synthetic sutures to minimize scarring and promote an early range of motion in cases where healing leads to excessive scarring around the flexor tendon sheath.
PubMed: 38947663
DOI: 10.7759/cureus.61250 -
Heliyon Jun 2024The ratio of the index finger (2nd finger) to the ring finger (4th finger) (2D:4D) can give information about harmony between personality and career of individuals. The...
BACKGROUND
The ratio of the index finger (2nd finger) to the ring finger (4th finger) (2D:4D) can give information about harmony between personality and career of individuals. The developing technology makes it difficult to choose a profession.
AIM
This study aims to contribute to the career choice of individuals by analyzing the relationship between the 2D:4D finger digit ratio and personality traits of individuals working in different professions (Educator, Worker, Housewife, Civil servant, Healthcare professional/EWHCH).
METHOD
The participants were three hundred twenty-five individuals living in the province of Malatya. The SPSS 26.0 software was utilized in the data analysis. The p value of 0.05 was accepted as significance level in comparison tests.
RESULTS
A statistically significant difference was determined between the participants, who had the 2D shorter than the 4D in right hand, in terms of professional groups (p < 0.05). In healthcare workers, a low level (r = 0.305) positive correlation was found between right hand 2D4D and both control (r = 0.264) and curiosity and left hand 2D:4D, and a low level (r = 0.255) negative correlation was found between Conscientiousness and right hand 2D:4D in housewives. There was a statistically significant difference between the groups (educator, worker, housewife, civil servant, healthcare professional) in terms of total score of the Five-Factor Personality Inventory (FFPI) and scores of extroversion, agreeableness, conscientiousness, neuroticism, and openness to experience subscales (p < 0.05). A weak positive statistically significant correlation was detected between the healthcare professionals' score of Career Adapt-abilities Scale (CAAS) control subscale and the right-hand 2D:4D ratio. : It is suggested to investigate the 2D:4D ratio over different professional groups. The present study is important since it gives information about personality and associates such information with the 2D:4D ratio.
PubMed: 38947474
DOI: 10.1016/j.heliyon.2024.e32332 -
Frontiers in Big Data 2024Hyperdimensional Computing (HDC) is a brain-inspired and lightweight machine learning method. It has received significant attention in the literature as a candidate to...
INTRODUCTION
Hyperdimensional Computing (HDC) is a brain-inspired and lightweight machine learning method. It has received significant attention in the literature as a candidate to be applied in the wearable Internet of Things, near-sensor artificial intelligence applications, and on-device processing. HDC is computationally less complex than traditional deep learning algorithms and typically achieves moderate to good classification performance. A key aspect that determines the performance of HDC is encoding the input data to the hyperdimensional (HD) space.
METHODS
This article proposes a novel lightweight approach relying only on native HD arithmetic vector operations to encode binarized images that preserves the similarity of patterns at nearby locations by using point of interest selection and .
RESULTS
The method reaches an accuracy of 97.92% on the test set for the MNIST data set and 84.62% for the Fashion-MNIST data set.
DISCUSSION
These results outperform other studies using native HDC with different encoding approaches and are on par with more complex hybrid HDC models and lightweight binarized neural networks. The proposed encoding approach also demonstrates higher robustness to noise and blur compared to the baseline encoding.
PubMed: 38946939
DOI: 10.3389/fdata.2024.1371518 -
Frontiers in Digital Health 2024Recent studies have found that there is scope for communication technologies to increase online social capital. Although studies have linked online social capital and...
INTRODUCTION
Recent studies have found that there is scope for communication technologies to increase online social capital. Although studies have linked online social capital and mental well-being, there is a need to identify the causal pathways within this relationship. This study explores the role of loneliness in the relationship between computer-mediated communication, online social capital and well-being.
METHODS
The study used an online questionnaire and had 217 participants. William's 2006 scale was used to measure individuals' online social capital, and structural equational modelling (SEM) was used to explore the relationship between computer-mediated communication, use, levels of loneliness, online social capital and well-being. This study was conducted remotely during the first COVID-19 lockdown in Ireland.
RESULTS
High levels of online communication mitigated the otherwise negative effects of loneliness on well-being when online interaction fostered online social capital.
CONCLUSION
Overall, the proposed model offers qualified support for the continued analysis of technology-mediated communication as a potential source for building online social capital and improving the well-being of particular individuals with high levels of loneliness.
PubMed: 38946729
DOI: 10.3389/fdgth.2024.1289451 -
Frontiers in Digital Health 2024Heart rate variability biofeedback (HRVB) is a well-studied intervention known for its positive effects on emotional, cognitive, and physiological well-being, including...
INTRODUCTION
Heart rate variability biofeedback (HRVB) is a well-studied intervention known for its positive effects on emotional, cognitive, and physiological well-being, including relief from depressive symptoms. However, its practical use is hampered by high costs and a lack of trained professionals. Smartphone-based HRVB, which eliminates the need for external devices, offers a promising alternative, albeit with limited research. Additionally, premenstrual symptoms are highly prevalent among menstruating individuals, and there is a need for low-cost, accessible interventions with minimal side effects. With this pilot study, we aim to test, for the first time, the influence of smartphone-based HRVB on depressive and premenstrual symptoms, as well as anxiety/stress symptoms and attentional control.
METHODS
Twenty-seven participants with above-average premenstrual or depressive symptoms underwent a 4-week photoplethysmography smartphone-based HRVB intervention using a waitlist-control design. Laboratory sessions were conducted before and after the intervention, spaced exactly 4 weeks apart. Assessments included resting vagally mediated heart rate variability (vmHRV), attentional control via the revised attention network test (ANT-R), depressive symptoms assessed with the BDI-II questionnaire, and stress/anxiety symptoms measured using the DASS questionnaire. Premenstrual symptomatology was recorded through the PAF questionnaire if applicable. Data analysis employed linear mixed models.
RESULTS
We observed improvements in premenstrual, depressive, and anxiety/stress symptoms, as well as the Executive Functioning Score of the ANT-R during the intervention period but not during the waitlist phase. However, we did not find significant changes in vmHRV or the Orienting Score of the ANT-R.
DISCUSSION
These findings are promising, both in terms of the effectiveness of smartphone-based HRVB and its potential to alleviate premenstrual symptoms. Nevertheless, to provide a solid recommendation regarding the use of HRVB for improving premenstrual symptoms, further research with a larger sample size is needed to replicate these effects.
PubMed: 38946728
DOI: 10.3389/fdgth.2024.1337667 -
The Clinical Neuropsychologist Jun 2024To generate normative data (ND) for executive functions tests in the Waranka minority population of Ecuador. Four-hundred participants aged 6-17 completed the...
To generate normative data (ND) for executive functions tests in the Waranka minority population of Ecuador. Four-hundred participants aged 6-17 completed the Symbol-Digit Modalities Test (SDMT), Trail-Making Test (TMT), Modified-Wisconsin Card Sorting Test (M-WCST), and Test of Colors-Words (STROOP). Scores were normed using multiple linear regressions, including age, age, natural logarithm of mean parent education (MPE), sex, bilingualism, and two-way interactions as predictors. Age by MPE and Age by MPE interactions arose for SDMT, so that children with illiterate parents scored lower than those with literate parents. Girls scored higher in SDMT. All TMT and M-WCST scores were influenced by age. Age by MPE interaction was found for TMT-A, so that children with higher MPE went faster; and age by bilingualism interaction for TMT-B, so that more bilingual children needed less time. Stroop-Word and Color were influenced by age by MPE interaction, so that children, while older, scored higher, especially those with higher MPE. Also, age by sex interaction arose, so that girls increased scores curvilinearly while boys linearly. Word-Color was influenced by age, while Stroop-interference by age. Age by MPE interaction was found for MCST-Categories and Perseveration, so that perseverations decreased to then increased, especially in those with illiterate parents. M-WCST-Category scores increased to then decrease later on age in children with illiterate parents. Z-scores calculated through indigenous ND were significantly lower than generated through non-indigenous norms. ND for minority populations are critical since Waranka sample performed worse when using non-indigenous norms for z-score calculation.
PubMed: 38946161
DOI: 10.1080/13854046.2024.2367748 -
JAMA Health Forum Jun 2024States resumed Medicaid eligibility redeterminations, which had been paused during the COVID-19 public health emergency, in 2023. This unwinding of the pandemic...
IMPORTANCE
States resumed Medicaid eligibility redeterminations, which had been paused during the COVID-19 public health emergency, in 2023. This unwinding of the pandemic continuous coverage provision raised concerns about the extent to which beneficiaries would lose Medicaid coverage and how that would affect access to care.
OBJECTIVE
To assess early changes in insurance and access to care during Medicaid unwinding among individuals with low incomes in 4 Southern states.
DESIGN, SETTING, AND PARTICIPANTS
This multimodal survey was conducted in Arkansas, Kentucky, Louisiana, and Texas from September to November 2023, used random-digit dialing and probabilistic address-based sampling, and included US citizens aged 19 to 64 years reporting 2022 incomes at or less than 138% of the federal poverty level.
EXPOSURE
Medicaid enrollment at any point since March 2020, when continuous coverage began.
MAIN OUTCOMES AND MEASURES
Self-reported disenrollment from Medicaid, insurance at the time of interview, and self-reported access to care. Using multivariate logistic regression, factors associated with Medicaid loss were evaluated. Access and affordability of care among respondents who exited Medicaid vs those who remained enrolled were compared, after multivariate adjustment.
RESULTS
The sample contained 2210 adults (1282 women [58.0%]; 505 Black non-Hispanic individuals [22.9%], 393 Hispanic individuals [17.8%], and 1133 White non-Hispanic individuals [51.3%]) with 2022 household incomes less than 138% of the federal poverty line. On a survey-weighted basis, 1564 (70.8%) reported that they and/or a dependent child of theirs had Medicaid at some point since March 2020. Among adult respondents who had Medicaid, 179 (12.5%) were no longer enrolled in Medicaid at the time of the survey, with state estimates ranging from 7.0% (n = 19) in Kentucky to 16.2% (n = 82) in Arkansas. Fewer children who had Medicaid lost coverage (42 [5.4%]). Among adult respondents who left Medicaid since 2020 and reported coverage status at time of interview, 47.8% (n = 80) were uninsured, 27.0% (n = 45) had employer-sponsored insurance, and the remainder had other coverage as of fall 2023. Disenrollment was higher among younger adults, employed individuals, and rural residents but lower among non-Hispanic Black respondents (compared with non-Hispanic White respondents) and among those receiving Supplemental Nutrition Assistance Program benefits. Losing Medicaid was significantly associated with delaying care due to cost and worsening affordability of care.
CONCLUSIONS AND RELEVANCE
The results of this survey study indicated that 6 months into unwinding, 1 in 8 Medicaid beneficiaries reported exiting the program, with wide state variation. Roughly half who lost Medicaid coverage became uninsured. Among those moving to new coverage, many experienced coverage gaps. Adults exiting Medicaid reported more challenges accessing care than respondents who remained enrolled.
Topics: Humans; Medicaid; United States; Health Services Accessibility; Adult; Female; Male; Insurance Coverage; Middle Aged; COVID-19; Poverty; Young Adult; Arkansas
PubMed: 38943683
DOI: 10.1001/jamahealthforum.2024.2193 -
Sleep Jun 2024Obstructive sleep apnea (OSA) increases the risk of cognitive impairment. Measures of sleep microarchitecture from EEG may help identify patients at risk of this...
STUDY OBJECTIVES
Obstructive sleep apnea (OSA) increases the risk of cognitive impairment. Measures of sleep microarchitecture from EEG may help identify patients at risk of this complication.
METHODS
Participants with suspected OSA (n=1142) underwent in-laboratory polysomnography and completed sleep and medical history questionnaires, and tests of global cognition (Montreal Cognitive Assessment, MoCA), memory (Rey Auditory Verbal Learning Test, RAVLT) and information processing speed (Digit-Symbol Coding, DSC). Associations between cognitive scores and stage 2 NREM sleep spindle density, power, frequency and %-fast (12-16Hz), odds-ratio product (ORP), normalized EEG power (EEGNP) and the delta:alpha ratio were assessed using multivariable linear regression (MLR) adjusted for age, sex, education, and total sleep time. Mediation analyses were performed to determine if sleep microarchitecture indices mediate the negative effect of OSA on cognition.
RESULTS
All spindle characteristics were lower in participants with moderate and severe OSA (p≤0.001, versus no/mild OSA) and positively associated with MoCA, RAVLT and DSC scores (false discovery rate corrected p-value, q≤0.026), except spindle power which was not associated with RAVLT (q=0.185). ORP during NREM sleep (ORPNREM) was highest in severe OSA participants (p≤0.001) but neither ORPNREM (q≥0.230) nor the delta:alpha ratio were associated with cognitive scores in MLR analyses (q≥0.166). In mediation analyses, spindle density and EEGNP (p≥0.048) mediated moderate-to-severe OSA's negative effect on MoCA scores while ORPNREM, spindle power and %-fast spindles mediated OSA's negative effect on DSC scores (p≤0.018).
CONCLUSION
Altered spindle activity, ORP and normalized EEG power may be important contributors to cognitive deficits in patients with OSA.
PubMed: 38943546
DOI: 10.1093/sleep/zsae141