Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of cervicovaginal microbiome on the risk of cervical abnormalities development

The vaginal microbiome has emerged as potentially influencing the natural history of Human Papillomavirus (HPV) infections and their clinical impact. We aimed to characterize the vaginal microbiome in samples from 807 high‐risk HPVs (Hr‐HPV) positive women with a mean age of 41.45 ± 10.79 years who participated in the Regional Cervical Cancer Screening Program from the Northern Region of Portugal. Microbiome analysis was performed with commercial kits for the detection of 21 microorganisms. The most frequent microorganisms were Ureaplasma parvum (52.5%), Gardnerella vaginalis (GV) (34.5%), Atopobium vaginae (AV) (32.6%), Lacto (30.7%), and Mycoplasma hominis (MH) (23.5%). The distribution according to age reveals that MH, Mega1, GV, BVab2, AV, and Mob were more prevalent in women older than 41 years of age (p < 0.050), while Lacto is significantly decreased in this group (23.5% vs. 39.4%, p < 0.001; RR = 0.47). The risk analysis showed that Hr‐HPV‐16/‐18 and Hr‐HPV‐9val genotypes are associated with an increased risk of developing cervical abnormalities, while Lacto (p < 0.001; odd ratio [OR] = 0.33), GV (p = 0.0111; OR = 0.41), AV (p = 0.033; OR = 0.53) and Mob (p = 0.022; OR = 0.29) are associated with protection. Similar results were found for the risk of development atypical squamous cells cannot exclude HSIL/high‐grade squamous intraepithelial lesion. Overall, the multivariate analysis confirmed that lactobacillus and bacteria associated with bacterial vaginosis (GV, AV, and Mob) are associated with protection against the development of cervical abnormalities. This study provides important data to be included in the future management of risk stratification for Hr‐HPV‐positive women.
Vision-Based Autonomous Driving: A Hierarchical Reinforcement Learning Approach

Human drivers have excellent perception and reaction abilities in complex environments such as dangerous highways, busy intersections, and harsh weather conditions. To achieve human-level driving performance, autonomous driving systems require powerful environmental perception systems and the ability to make accurate decisions in difficult situations, enabling vehicles to maintain smooth driving. However, making decisions based on visual perception is still a daunting challenge for autonomous vehicles, also current end-to-end networks and modular frameworks have limitations in effectively addressing perception, decision-making, and control, such as a lack of interpretability and weak generalization ability in complex environments. This paper proposes an elaborate modular pipeline for autonomous driving that effectively integrates semantic perception information, multi-level decision tasks, and control modules. The decision-making module comprehensively considers high-level maneuver selection and low-level motion control in both horizontal and vertical directions. The proposed MP framework is trained end-to-end by a novel hierarchical reinforcement learning method with a new action sampling mechanism. To adapt to the experimental scenarios, we use the CARLA simulation platform to collect data to evaluate the proposed autonomous driving framework and its new training method, considering various environmental factors such as sunny, dusk, and rainy weather. The results show that the framework exhibits smooth and effective driving strategies in different environments and can converge quickly and stably. The method improves learning efficiency and reduces unnecessary coupling and error propagation. Overall, the proposed framework and training method provide new ideas for improving existing autonomous driving systems.
Neonatal Resuscitation Practices in Turkey: A Survey of the Turkish Neonatal Society and the Union of European Neonatal and Perinatal Societies

Objective: Optimal care in the delivery room is important to decrease neonatal morbidity and mortality. We aimed to evaluate neonatal resuscitation practices in Turkish centers. Materials and Methods: A cross-sectional survey consisted of a 91-item questionnaire focused on delivery room practices in neonatal resuscitation and was sent to 50 Turkish centers. Hospitals with <2500 and those with ≥2500 births/year were compared. Results: In 2018, approximately 240 000 births occurred at participating hospitals with a median of 2630 births/year. Participating hospitals were able to provide nasal continuous-positive-airway-pressure/high-flow nasal cannula, mechanical ventilation, high-frequency oscillatory ventilation, inhaled nitric oxide, and therapeutic hypothermia similarly. Antenatal counseling was routinely performed on parents at 56% of all centers. A resuscitation team was present at 72% of deliveries. Umbilical cord management for both term and preterm infants was similar between centers. The rate of delayed cord clamping was approximately 60% in term and late preterm infants. Thermal management for preterm infants (<32 weeks) was similar. Hospitals had appropriate equipment with similar rates of interventions and management, except continuous-positive-airway-pressure and positive-end-expiratory-pressure levels (cmH2O) used in preterm infants (P = .021, and P = .032). Ethical and educational aspects were also similar. Conclusions: This survey provided information on neonatal resuscitation practices in a sample of hospitals from all regions of Turkey and allowed us to see weaknesses in some fields. Although adherence to the guidelines was high among centers, further implementations are required in the areas of antenatal counseling, cord management, and circulation assessment in the delivery room.
FTO Gene Polymorphisms and Their Roles in Acromegaly

The major causes of both morbidity and mortality in patients with acromegaly are cardiovascular diseases (CVDs). The polymorphisms of the fat mass and obesity-associated gene (FTO) are associated with obesity, as well as with an increased risk of CVDs. The aim of the study was to determine the relationship of risk alleles of four FTO gene polymorphisms with selected parameters of lipid and glucose metabolism as well as with IGF-1 and GH levels in the group of patients with acromegaly compared to the control group. The study group consisted of 104 patients with acromegaly and 64 healthy subjects constituting the control group. In the whole acromegaly group, the data reveal that the homozygous for risk allele carriers (rs1421085, rs9930506, rs9939609) as well as carriers of only one risk allele have lower IGF-1 concentrations. In the well-controlled acromegaly group, the homozygous for three risk allele carriers of FTO gene polymorphisms have lower HDL cholesterol concentration (rs1121980, rs1421085, rs993609). In the cured acromegaly group, homozygous risk allele carriers rs9930506 tend to have higher levels of total cholesterol and LDL cholesterol. These associations are not observed in the control group. Conclusion: there is an association between FTO gene polymorphisms and the metabolism of lipids, suggesting that the FTO gene may be associated with higher CVD risk in patients with acromegaly. In addition, there is an association between FTO gene polymorphisms and IGF-1, implying that FTO gene may influence/modify IGF-1 synthesis. Further investigation on a larger scale is required to provide more precise evidence.
An optimal anytime estimation algorithm

In many applications a key step is estimating some unknown quantity ~$mu$ from a sequence of trials, each having expected value~$mu$. Optimal algorithms are known when the task is to estimate $mu$ within a multiplicative factor of $epsilon$, for an $epsilon$ given in advance. In this paper we consider {em anytime} approximation algorithms, i.e., algorithms that must give a reliable approximation after each trial, and whose approximations have to be increasingly accurate as the number of trials grows. We give an anytime algorithm for this task when the only a-priori known property of $mu$ is its range, and show that it is asymptotically optimal in some cases, in the sense that no correct anytime algorithm can give asymptotically better approximations. The key ingredient is a new large deviation bound for the supremum of the deviations in an infinite sequence of trials, which can be seen as a non-limit analog of the classical Law of the Iterated Logarithm.
A lattice-based method for structural analysis

In this paper we revisit the foundations of formal concept analysis for ordered contexts of [4]. From the theoretical point of view, the obtained lattice has proved to be a proper unifying framework for reasoning about different sequential mining tasks: from the discovery of partial orders to the clustering of input sequences. Here we will show how these results on sequences can be naturally extended to the mining of any partial order structure. We empirically validate the approach by testing it on real world data. Our experimental evaluation shows that this lattice-based method is an intuitive tool for analyzing acyclic structures.
Pedagogical Benefits and Practical Concerns of Writing Portfolio Assessment: Suggestions for Teaching L2 Writing

This study aims to investigate Vietnamese students’ perceptions of portfolio assessment and how it affects their writing performance. Furthermore, the study explores problems encountered during the assessment process, which could offer professional support for teachers, particularly novice teachers, when applying this formative assessment to teaching writing. Data was collected through students’ written papers, observations, and semi-structured interviews with a total of thirteen low- and intermediate-level undergraduate students. The findings demonstrate the aspects of the assessment usefulness, namely validity, authenticity, interactive-ness, and impact. Accordingly, the assessment provides students with a comprehensive understanding of academic writing that enhances their writing abilities. In particular, students recognize their common grammatical errors, pay more attention to organizing ideas logically, and develop writing habits throughout the writing process, which have not been carefully addressed in prior education. Nevertheless, there are a number of issues that need to be carefully considered, including idea development, plagiarism knowledge, self- and peer-assessment, and the order of writing steps. In order to improve the reliability and practicality of the assessment, solutions to those concerns are provided.
Incident atrial fibrillation and adverse clinical outcomes during extended follow-up of participants recruited to the remote heart rhythm sampling using the AliveCor heart monitor to screen for atrial fibrillation: the REHEARSE-AF study

Abstract Aims Atrial fibrillation (AF) is an important risk factor for stroke, which is commonly asymptomatic, particularly in older patients, and often undetected until cardiovascular events occur. Development of novel technology has helped to improve detection of AF. However, the longer-term benefit of systematic electrocardiogram (ECG) screening on cardiovascular outcomes is unclear. Methods and results In the original REHEARSE-AF study, patients were randomized to twice-weekly portable electrocardiogram (iECG) assessment or routine care. After discontinuing the trial portable iECG assessment, electronic health record data sources provided longer-term follow-up analysis. Cox regression was used to provide unadjusted and adjusted hazard ratios (HR) [95% confidence intervals (CI)] for clinical diagnosis, events, and anticoagulant prescriptions during the follow-up period. Over the median 4.2-year follow-up, although a greater number of patients were diagnosed with AF in the original iECG group (43 vs. 31), this was not significant (HR 1.37, 95% CI 0.86–2.19). No differences were seen in the number of strokes/systemic embolisms or deaths between the two groups (HR 0.92, 95% CI 0.54–1.54; HR 1.07, 95% CI 0.66–1.73). Findings were similar when restricted to those with CHADS-VASc ≥ 4. Conclusion A 1-year period of home-based, twice-weekly screening for AF increased diagnoses of AF for the screening period but did not lead to increased diagnoses of AF or a reduction in cardiovascular-related events or all-cause death over a median of 4.2 years, even in those at highest risk of AF. These results suggest that benefits of regular ECG screening over a 1-year period are not maintained after cessation of the screening protocol.
Nutrition Information and Visual Attention: Insights from a Meta-Analytical Approach

ABSTRACT The present study investigated how different nutrition information influences consumer attention. This study aims to provide a meta-analytic model to understand nutrition information as a stimulus element for visual attention. This paper explores the literature about nutrition information while debating four divergent questions regarding levels of visual attention, such as: which labeling systems generate the most visual attention? Are there differences in visual attention between vice and virtue nutrition information? Monochromatic create more attention than polychromatic labels? Does the position of the label influence visual attention? The findings contribute additional information to the results on perceived nutrition information from previous studies indicating that consumer attention tends to be increased (reduced) by the non-directive system (directive system), vice nutrition information (virtue nutrition), and nutritional information at the top of the package (nutritional information at the bottom of the package).
Blind Source Deconvolution Based on Frequency Domain Convolution Model Under Highly Reverberant Environments

In order to solve the blind source deconvolution, a convolved mixing process in the time domain is often transformed into an instantaneous mixing model in the frequency domain. However, the model is only an approximated one and thus does not work effectively under highly reverberant environments. By dividing the impulse response properly, Servière has precisely transformed the time-domain convolved mixture to a frequency-domain convolved mixture and has proposed a new FDICA approach available under high reverberation. In the approach, however, the permuation and scaling problems are unresolved as well as the distortion due to whitening. In the present paper, an improved approach without such problems is proposed and is confirmed to be valid in a highly reverberant real environment.
MOBILE-BANKING PENETRATION IN RURAL INDIA: A STUDY BASED ON UTAUT-2 MODEL

Mob-banking technology is still evolving across all the world, but its spread has been uneven. We prefer to focus on factors that influence actual practice and future use intention. Through its uneven mechanical phenomena of mob-payments, India offers us with a suitable arena for analyzing citizens' usage behavior. We try to comprehend adoption backed UTAUT-2 models in accessibility, transactional convenience, profit convenience, and post-benefit convenience as all have a significant influence on mob-banking adoption purpose. The effects of convenience dimensions on mob-banking adoption intention are moderated by perceived hedonistic and perceived utilitarian objectives. In this research trying to find out the which UTAUT-2 factor can affect the mobile banking penetration in rural India and how can improve the penetration rate in rural India and this research also propose a extra factor in UTAUT-2 model and providing the solution.The research's findings can help banks in important elements of online convenience to order via mob-banking platforms
Hyperspectral Image Classification Using a Superpixel–Pixel–Subpixel Multilevel Network

Hyperspectral images (HSIs) often contain irregular ground cover with mixed spectral features and noise, which makes it challenging to identify the ground cover using only pixel features, superpixel features, or a combination of both. To alleviate the above problem, this article proposes a superpixel–pixel–subpixel multilevel (SPSM) network, which compensates for the insufficiencies of the different levels and decreases the information loss. For arbitrary irregular regions, superpixel features are simulated as network nodes using a graph convolutional network (GCN) to capture the spatial texture structure of the HSI, which improves the smooth classification results of local regions while facilitating the identification of different vegetation features in the region. In addition, the global attention module (GAM) learns local regular regions based on pixel-level features to extend the global interactive representation capability and reduce the information loss. To overcome spectral mixing and enhance material discrimination, the normalized attention module (NAM) is used to suppress unimportant subpixel information and identify and remove irrelevant details, thereby improving the identification of critical features that differentiate different materials. Finally, the three features are fused to build an SPSM classification framework to improve robustness to overfitting, reduce computational complexity, and facilitate target recognition. Experimental results on four HSI datasets demonstrate that the method is more capable of recognizing detailed features than other advanced comparison methods.
Increased flexibility of brain dynamics in patients with multiple sclerosis

Abstract Patients with multiple sclerosis consistently show widespread changes in functional connectivity. Yet, alterations are heterogeneous across studies, underscoring the complexity of functional reorganization in multiple sclerosis. Here, we aim to provide new insights by applying a time-resolved graph-analytical framework to identify a clinically relevant pattern of dynamic functional connectivity reconfigurations in multiple sclerosis. Resting-state data from 75 patients with multiple sclerosis (N = 75, female:male ratio of 3:2, median age: 42.0 ± 11.0 years, median disease duration: 6 ± 11.4 years) and 75 age- and sex-matched controls (N = 75, female:male ratio of 3:2, median age: 40.2 ± 11.8 years) were analysed using multilayer community detection. Local, resting-state functional system and global levels of dynamic functional connectivity reconfiguration were characterized using graph-theoretical measures including flexibility, promiscuity, cohesion, disjointedness and entropy. Moreover, we quantified hypo- and hyper-flexibility of brain regions and derived the flexibility reorganization index as a summary measure of whole-brain reorganization. Lastly, we explored the relationship between clinical disability and altered functional dynamics. Significant increases in global flexibility (t = 2.38, PFDR = 0.024), promiscuity (t = 1.94, PFDR = 0.038), entropy (t = 2.17, PFDR = 0.027) and cohesion (t = 2.45, PFDR = 0.024) were observed in patients and were driven by pericentral, limbic and subcortical regions. Importantly, these graph metrics were correlated with clinical disability such that greater reconfiguration dynamics tracked greater disability. Moreover, patients demonstrate a systematic shift in flexibility from sensorimotor areas to transmodal areas, with the most pronounced increases located in regions with generally low dynamics in controls. Together, these findings reveal a hyperflexible reorganization of brain activity in multiple sclerosis that clusters in pericentral, subcortical and limbic areas. This functional reorganization was linked to clinical disability, providing new evidence that alterations of multilayer temporal dynamics play a role in the manifestation of multiple sclerosis.
Nonparametric Regression: Optimal Local Bandwidth Choice

SUMMARY Kernel estimators of a regression function are investigated. The bandwidths are locally chosen by a data-driven method based on the minimization of a local cross-validation criterion. This method is shown to be asymptotically optimal with respect to local quadratic measures of errors. Monte Carlo experiments are presented, and finally the method is applied to some data of medical interest.
Internal gravity waves in massive stars. II. Frequency analysis across stellar mass

Stars with masses above 1.6 solar masses generally possess convective cores and radiative envelopes, which allows the propagation of outward-travelling internal gravity waves. We have studied the generation and propagation of IGWs in such stars using two-dimensional, fully nonlinear hydrodynamical simulations with realistic stellar reference states from the one-dimensional stellar evolution code, Modules for Stellar Astrophysics. Compared to previous similar works, this study utilises radius-dependent thermal diffusivity profiles for 5 different stellar masses at the middle of main sequence: 3 - 13 solar masses. From the simulations, we find that the surface perturbations are larger for higher masses, but no noticeable trends are observed for the frequency slopes with different stellar masses. The slopes are also similar to the results from previous works. We compare our simulation results with stellar photometric data from a recent survey and find that for frequency intervals above 8 microHz, there is a good agreement between the temperature frequency slopes from the simulations and the surface brightness variations of these observed stars, indicating that the brightness variations are caused by core-generated IGWs.
A New Unified Theory of Trigger Point Formation: Failure of Pre- and Post-Synaptic Feedback Control Mechanisms

The origin of the myofascial trigger point (TrP), an anomalous locus in muscle, has never been well-described. A new trigger point hypothesis (the new hypothesis) presented here addresses this lack. The new hypothesis is based on the concept that existing myoprotective feedback mechanisms that respond to muscle overactivity, low levels of adenosine triphosphate, (ATP) or a low pH, fail to protect muscle in certain circumstances, such as intense muscle activity, resulting in an abnormal accumulation of intracellular Ca2+, persistent actin-myosin cross bridging, and then activation of the nociceptive system, resulting in the formation of a trigger point. The relevant protective feedback mechanisms include pre- and postsynaptic sympathetic nervous system modulation, modulators of acetylcholine release at the neuromuscular junction, and mutations/variants or post-translational functional alterations in either of two ion channelopathies, the ryanodine receptor and the potassium-ATP ion channel, both of which exist in multiple mutation states that up- or downregulate ion channel function. The concepts that are central to the origin of at least some TrPs are the failure of protective feedback mechanisms and/or of certain ion channelopathies that are new concepts in relation to myofascial trigger points.
Moisture Helicity and Its Application in Diagnostic Analysis of a Heavy Rain in Jiang-Huai Basin

A new diagnostic quantity—moisture helicity is derived from the moisture equation,and the difinition of helicity,and its influence factors are analyzed in details by the dimensional analysis.The simulated results by the numerical model MM5 of the rainstorm process on 4th to 5th July 2003 are diagnostically analyzed,and results show that the moisture helicity is well correlated.Both the helicity flux divergence and the humid helical divergence have indication for heavy rain,and the former has better indicating effect for both the location and intensity of heavy rainfall,while the latter is only better correclated with the intensity of heavy rainfall.