Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of physics and chemical-abundance uncertainties on the properties of lower-mass stars that are used as standard candles

Abstract The distances to old stellar populations have traditionally been derived from three standard candles: the luminosity of the red-giant-branch tip, the absolute magnitudes of RR Lyrae stars, and the colour–magnitude-diagram loci of nearby subdwarfs. The distance-modulus uncertainties that are associated with these methods are still at the level of ±0.10–0.15 mag. Current stellar models are able to satisfy these age-independent constraints to well within their error bars, which are mainly owing to the uncertainties in the distances of the calibrating objects and, directly or indirectly, to chemical-abundance uncertainties. The impact of varying the physics and the assumed abundances in stellar models on the aforementioned standard candles is discussed, as is the use of the giant-branch bump luminosity to constrain the distance scale.
An Autonomous Underwater Vehicle Simulation With Fuzzy Sensor Fusion for Pipeline Inspection

Underwater pipeline inspection is an important topic in off-shore subsea operations. Remotely operated vehicles (ROVs) can play an important role in multiple application areas including military, ocean science, aquaculture, shipping, and energy. However, using ROVs for inspection is not cost-effective, and the fixed leak detection sensors mounted along the pipeline have limited precision. Although the cost can be significantly reduced by applying autonomous underwater vehicles (AUVs), the unstable current, low visibility, and loss of GPS signal make the navigation of AUVs underwater very challenging. Previous studies have been conducted on coordinate-based, vision-based, and fusion-based navigation algorithms. However, the coordinate-based algorithms suffered from the denial of GPS signals while the vision-based methods typically relied on terrain and landscape knowledge that required collection prior to the mission. As a result of these issues, a navigation system for an AUV that incorporates vision and sonar sensors is presented in this article. In a robot operating system (ROS)/Gazebo-based simulation environment, the AUV had the ability to find and navigate toward the pipeline and continuously traverse along its length. Additionally, with a chemical concentration sensor mounted on the AUV, the system demonstrated the capability of inspecting the pipeline and reporting the leak point with a resolution of 3 m along the pipeline.
High-density electromyography as a method for estimating laryngeal muscle activity: a preliminary study

Current methods for monitoring laryngeal muscle function include techniques such as intramuscular electromyography, external laryngeal palpation, and laryngeal endoscopy. Although these methods have provided much information about muscle activation and function during voice production, they are invasive, uncomfortable, and subjective. The objective of this work is to explore the use of the high-density electromyography (HDsEMG) as a non-invasive alternative that can potentially provide objective information on the activity of the laryngeal muscles during speech. with a focus on the cricothyroid muscle (CT). From this set of signals, it is possible to decompose the electromyography signal, providing indirect information on the spatial recruitment and firing rates of motor units (MU) within the muscle. It is hypothesized that the use of MU firing rate and recruitment will allow for a better estimation of muscle activation compared to traditional methods. A high-density wireless HDsEMG equipment (Sessantaquattro, OT Bioelettronica) is used with a 64-channel electrode grid, which are centered on the CT muscle. Preliminary results of a case study illustrated that it was possible to obtain the rates and firing trains of 4 motor units. Future work will explore how HDsEMG applied to the larynx has the potential to improve diagnostic and therapeutic follow-up of pathologies of laryngeal function.
COVID-19 Vaccine Booster Shot Preserves T Cells Immune Response Based on Interferon-Gamma Release Assay in Inflammatory Bowel Disease (IBD) Patients on Anti-TNFα Treatment

Immune-modifying treatment in inflammatory bowel disease (IBD) impairs the humoral response. The role of T lymphocytes in this setting is still unclear. This study aims to assess if a booster shot (third dose) of BNT162b2 mRNA COVID-19 vaccine enhanced the humoral response and elicited cellular immunity in IBD patients on different immuno-therapy regimens compared to healthy controls (HCs). Five months after a booster dose, serological and T-cell responses were assessed. The measurements were described using geometric means with 95% confidence intervals. The differences between study groups were assessed by Mann–Whitney tests. Seventy-seven subjects (n = 53 IBD patients and n = 24 HCs), who were fully vaccinated and not previously SARS-CoV-2 infected, were recruited. Regarding the IBD patients, 19 were affected by Crohn’s disease and 34 by ulcerative colitis. During the vaccination cycle, half of the patients (53%) were on stable treatment with aminosalicylates, and 32% were on biological therapy. No differences in antibody concentrations between IBD patients and HCs, nor T-cell responses, were found. Stratifying IBD patients based on the type of treatment (anti-TNFα agents vs. other treatment regimens), a decrease only in antibody titer (p = 0.008), but not in cellular response, was observed. Even after the COVID-19 vaccine booster dose, the TNFα inhibitors selectively decreased the humoral immune response compared to patients on other treatment regimens. The T-cell response was preserved in all study groups. These findings highlight the importance of evaluating T-cell immune responses following COVID-19 vaccination in a routine diagnostic setting, particularly for immunocompromised cohorts.
An empirical bias–variance analysis of DECORATE ensemble method at different training sample sizes

DECORATE (Diverse Ensemble Creation by Oppositional Relabeling of Artificial Training Examples) is a classifier combination technique to construct a set of diverse base classifiers using additional artificially generated training instances. The predictions from the base classifiers are then integrated into one by the mean combination rule. In order to gain more insight about its effectiveness and advantages, this paper utilizes a large experiment to study the bias–variance analysis of DECORATE as well as some other widely used ensemble methods (such as bagging, AdaBoost, random forest) at different training sample sizes. The experimental results yield the following conclusions. For small training sets, DECORATE has a dominant advantage over its rivals and its success is attributed to the larger bias reduction achieved by it than the other algorithms. With increase in training data, AdaBoost benefits most and the bias reduced by it gradually turns to be significant while its variance reduction is also medium. Thus, AdaBoost performs best with large training samples. Moreover, random forest behaves always second best regardless of small or large training sets and it is seen to mainly decrease variance while maintaining low bias. Bagging seems to be an intermediate one since it reduces variance primarily.
COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19

COVID-19 has taken a huge toll on our lives over the last 3 years. Global initiatives put forward by all stakeholders are still in place to combat this pandemic and help us learn lessons for future ones. While the vaccine rollout was not able to curb the spread of the disease for all strains, the research community is still trying to develop effective therapeutics for COVID-19. Although Paxlovid and remdesivir have been approved by the FDA against COVID-19, they are not free of side effects. Therefore, the search for a therapeutic solution with high efficacy continues in the research community. To support this effort, in this latest version (v3) of COVID-19Base, we have summarized the biomedical entities linked to COVID-19 that have been highlighted in the scientific literature after the vaccine rollout. Eight different topic-specific dictionaries, i.e., gene, miRNA, lncRNA, PDB entries, disease, alternative medicines registered under clinical trials, drugs, and the side effects of drugs, were used to build this knowledgebase. We have introduced a BLSTM-based deep-learning model to predict the drug-disease associations that outperforms the existing model for the same purpose proposed in the earlier version of COVID-19Base. For the very first time, we have incorporated disease-gene, disease-miRNA, disease-lncRNA, and drug-PDB associations covering the largest number of biomedical entities related to COVID-19. We have provided examples of and insights into different biomedical entities covered in COVID-19Base to support the research community by incorporating all of these entities under a single platform to provide evidence-based support from the literature. COVID-19Base v3 can be accessed from: https://covidbase-v3.vercel. app/. The GitHub repository for the source code and data dictionaries is available to the community from: https://github.com/91Abdullah/covidbasev3.0.
Multiphoton microscopy imaging of collagen fiber layers and orientation in the tympanic membrane

Greater understanding of tympanic membrane (TM) biomechanics has the potential to guide future advances in medical technology related to its surgical repair (myringoplasty). The pars tensa of the TM is a composite structure with two collagen fiber layers that provide the main scaffolding for the TM. The external layer is arranged in an approximately radial configuration, and the other is arranged in an approximately circumferential configuration. A more detailed knowledge of collagen fiber orientation and volume fraction could greatly improve existing mechanical simulations of the TM. To address this, we employed multiphoton microscopy (MPM) imaging of the TM in two modalities: second harmonic generation (SHG) and two-photon fluorescence (TPF). The unique spectral signature of SHG allows selective imaging of collagen fibers. TPF also produces images of fibrillar-type collagen but lacks the specificity of SHG. Both the SHG and TPF images show patterns of collagen organization in the TM that match expected results with respect to both orientation and size. Through MPM, we intend to accurately determine the collagen fiber layer thickness, density, and orientation as a function of radial position and quadrant location.
Birational Geometry of Plane Curves

The purpose of this paper is to study curves on rational surfaces from the viewpoint of birational geometry. We begin by recalling basic notions and elementary results of birational geometry of plane curves (see [4], [5] and [8]). Let $C$ be a curve on a surface $S$ . Here by curves and surfaces we mean projective irreducible varieties of dimension 1 and 2, respectively, which are defined over an algebraically closed field of characteristic zero. We shall study such pairs $(S, C)$ . Two pairs $(S, C)$ and $(S_{1}, C_{1})$ are said to be birationally equivalent if there exists a birational map $f:S\rightarrow S_{1}$ such that the proper image $f[C]$ of $C$ by $f$ coincides with $C_{1}$ . Here the proper image $f[C]$ is by definition the closure of the image $f(x)$ of the generic point $x$ of $C$. When there is no danger of confusion, we say that $C$ is birationally equivalent to $C_{1}$ as imbedded curves if two pairs $(S, C)$ and $(S_{1}, C_{1})$ are birationally equivalent. A pair $(W, D)$ is said to be non-singular, if both $W$ and $D$ are non-singular. In this case, we have complete linear systems $|m(D+K_{W})|$ for any $m>0$ , where $K_{W}$ indicates a canonical divisor of $W$. The dimension diml $m(D+K_{W})|+1$ depends on both
Analysis and Optimization of Hardware Impaired FD Rician-Faded mMIMO Systems

We consider a full duplex (FD) multi-cell massive multi-input-multi-output (mMIMO) network, wherein FD mMIMO base-stations (BSs) serve multiple FD user equipments (UEs) on the same time-frequency resource. We derive closed-form uplink and downlink spectral efficiency (SE) expressions by considering i) radio-frequency impairments at the BSs and the UEs; ii) dynamic-resolution analog-to-digital converter/digital-to-analog converter (ADC/DAC) architecture at the BSs and low-resolution ADC/DAC at the UEs; and iii) spatially-correlated Rician channels. We optimize the non-convex global energy efficiency metric for this FD system by using the minorization-maximization (MM) framework, which transforms the optimization into a sequence of surrogate concave problems. We construct a novel surrogate function to exploit the MM framework. We numerically characterize the effect of FD interference on Rayleigh- and Rician-faded mMIMO networks, and show the higher immunity of the latter to the FD interference. We also show the SE gain provided by the dynamic ADC/DAC architecture which allows us to judiciously choose ADC/DAC resolution, while reducing the power consumption.
The Design and Evaluation of an Artificial Ear

Abstract : A wideband artificial ear for the calibration of supraaural audiometric earphones was designed and constructed. The device consisted of three acoustically coupled cavities, and was designed to possess the acoustic impedance of an average human ear as seen by a standard supraaural earphone. An acoustic impedance measuring device was developed to aid in the evaluation of this artificial ear. Plots of experimentally determined acoustic impedance of this and other artificial ears are presented and discussed. Comparison of the experimentally determined acoustic impedance of the subject artificial ear with design values showed general agreement. It was concluded that lumped parameter representation of acoustic impedances, and the ability to measure acoustic impedance accurately and rapidly, are valuable tools for the development of complex acoustic systems. (Author)
The impact of COVID-19 on students’ academic performance: The case of the university of Ghana business school

Abstract The unruly consequences of the COVID-19 outbreak have hamstrung higher education institutions. This study aims to investigate the perceived impact of COVID-19 on student learning and academic performance through a qualitative approach. In-depth semi-structured interviews with 30 purposively chosen informants were used. The results indicated that 70% of students perceive a paradigm shift in their learning experience before and after COVID-19. It was discovered that their sociodemographic characteristics influenced 60% of students, and 57% were influenced by their parent’s socioeconomic status, which influenced their academic achievements during the COVID-19 outbreak. The findings revealed that 63% of students had faced numerous challenges during the COVID-19 online learning, affecting their academic performance. The study provides insight into the student academic performance during the covid-19 online education in the Ghanaian context. The study discusses the implications of the findings on higher institutions, government, and parents’ household income and recommendations for future research. Higher education institutions, governments, and parents must purchase licensed e-learning tools and provide students and professors with digital skills training to enhance faculty teaching, student learning, and academic performance.
Numerical coupling models for analyzing dynamic behaviors of electromagnetic actuators

This paper presents two coupling models for analyzing dynamical behaviors of electromagnetic actuators. The first model is based on coupled finite element and parametrization methods. The second one is the transient coupling model, it makes use of an iterative technique for the coupled electric, magnetic and mechanical phenomena. A comparison of those models is given through the calculation of the dynamic behavior of a linear axisymmetrical actuator supplied by capacitor discharge voltage.
Minisodar measurements of rain

Abstract Measurements of raindrop fall velocity spectra have been made with a minisodar. Amplitude calibration of the system enables the calculation of drop size parameters such as number density, water density, and surface area using methods similar to those with Doppler radar studies. The acoustic measurements are at 10 m intervals within 200 m of the surface and benefit from an almost complete separation of droplet velocity spectra from atmospheric vertical velocity spectra. Comparison of parameters with those reported in the literature shows good agreement. It is shown that the chief difficulty with the method is atmospheric attenuation; however, excess attenuation due to scattering from droplets is found to be unimportant.
Quality of vision and outcomes after bilateral implantation of pseudo-non diffracting beam IOL

Purpose To analyze the objective and subjective visual performances of a new hybrid refractive/aspheric extended depth of focus (EDOF) intraocular lens (IOL). Methods In this monocentric prospective study patients with bilateral cataracts underwent cataract surgery and were implanted with a Lucidis IOL (SAV-IOL SA, Neuchâtel, Switzerland) in both eyes, 1 week apart from each other. At 3 months from implantation postoperative evaluations included monocular and binocular uncorrected and distance-corrected distant (4 m), intermediate (80 cm, 67 cm) and near (40 cm) visual acuities (UDVA/DCVA, UI80-67VA/DCI80-67VA, UNVA/DCNVA), binocular defocus curves, halometry, contrast sensitivity and objective quality-of-vision measurements. Also, patients were also asked to complete the national eye institute refractive error quality of life (NEI-RQL-42) questionnaire. Results Twenty-five patients (50 eyes) were included. The mean postoperative binocular UDVA, UI80VA, UI67VA and UNVA were-0.02 ± 0.13, 0.05 ± 0.09, 0.05 ± 0.08 and 0.03 ± 0.1 LogMar, and did not significantly differ from their corrected counterparts. On binocular defocus curves a VA ≥0.05LogMar was found between +0.50 and − 2.50 D of vergence, whereas the mean distance from the central stimulus on halometry was 1.23 ± 0.01. Mean ocular and corneal radical mean square at 4 mm were 0.31 ± 0.28 and 0.19 ± 0.07, respectively; whereas the mean Strehl ratio was 0.2 ± 0.09. Conclusion Lucidis IOLs demonstrated excellent visual performances, especially at close distances while maintain good quality of vision, contrast sensitivity, and overall patient-satisfaction.
Hybrid Feature Selection Algorithm and Ensemble Stacking for Heart Disease Prediction

—In cardiology, as in other medical specialties, early and accurate diagnosis of heart disease is crucial as it has been the leading cause of death over the past few decades. Early prediction of heart disease is now more crucial than ever. However, the state-of-the-art heart disease prediction strategy put more emphasis on classifier selection in enhancing the accuracy and performance of heart disease prediction, and seldom considers feature reduction techniques. Furthermore, there are several factors that lead to heart disease, and it is critical to identify the most significant characteristics in order to achieve the best prediction accuracy and increase prediction performance. Feature reduction reduces the dimensionality of the information, which may allow learning algorithms to work quicker and more efficiently, producing predictive models with the best rate of accuracy. In this study, we explored and suggested a hybrid of two distinct feature reduction techniques, chi-squared and analysis of variance (ANOVA). In addition, using the ensemble stacking method, classification is performed on selected features to classify the data. Using the optimal features based on hybrid features combination, the performance of a stacking ensemble based on logistic regression yields the best result with 93.44%. This can be summarized as the feature selection method can take into account as an effective method for the prediction of heart disease.
The Metagenomic Composition and Effects of Fecal-Microbe-Derived Extracellular Vesicles on Intestinal Permeability Depend on the Patient’s Disease

The composition and impact of fecal-microbe-derived extracellular vesicles (EVs) present in different diseases has not been analyzed. We determined the metagenomic profiling of feces and fecal-microbe-derived EVs from healthy subjects and patients with different diseases (diarrhea, morbid obesity and Crohn’s disease (CD)) and the effect of these fecal EVs on the cellular permeability of Caco-2 cells. The control group presented higher proportions of Pseudomonas and Rikenellaceae_RC9_gut_group and lower proportions of Phascolarctobacterium, Veillonella and Veillonellaceae_ge in EVs when compared with the feces from which these EVs were isolated. In contrast, there were significant differences in 20 genera between the feces and EV compositions in the disease groups. Bacteroidales and Pseudomonas were increased, and Faecalibacterium, Ruminococcus, Clostridium and Subdoligranum were decreased in EVs from control patients compared with the other three groups of patients. Tyzzerella, Verrucomicrobiaceae, Candidatus_Paracaedibacter and Akkermansia were increased in EVs from the CD group compared with the morbid obesity and diarrhea groups. Fecal EVs from the morbid obesity, CD and, mainly, diarrhea induced a significant increase in the permeability of Caco-2 cells. In conclusion, the metagenomic composition of fecal-microbe-derived EVs changes depending on the disease of the patients. The modification of the permeability of Caco-2 cells produced by fecal EVs depends on the disease of the patients.
Evaluation of crop water status of melon plants in tropical semi-arid climate using thermal imaging

ABSTRACT The objective of this study was to analyze the feasibility of using thermal images to estimate the water status of melon plants (Cucumis melo L.) in tropical semi-arid climates. The study was conducted in a randomized block design with a split-plot arrangement. The plots comprised of soil cover (with and without mulching), and subplots were constructed using five irrigation regimes (120, 100, 80, 60, and 40% crop evapotranspiration), with five replicates. The following variables were evaluated: canopy temperature (Tcanopy), leaf water potential, air temperature (Tair), soil moisture, crop yield, and thermal index (ΔT), which is defined as the difference between Tcanopy and Tair. ΔT exhibited high correlations with crop yield and water consumption, indicating that thermography is an efficient tool for identifying the water status of melon plants, which could be employed for proper irrigation scheduling under tropical semi-arid scenarios. Moreover, thermal images identified the beneficial effects of soil cover on leaf water status and crop yield, primarily under moderate deficit irrigation. These results demonstrate that mulching is essential for increasing melon yield and water productivity in tropical regions.
Testing for dependence in the input to a linear time series model

This paper presents a simple test for dependence in the residuals of a linear parametric time series model fitted to non gaussian data. The test statistic is a third order extension of the standard correlation test for whiteness. but the number of lags used in this test is a function of the sample size. The power of this test goes to one as the sample size goes to infinity for any alternative which has non zero bicovariances c e3(r,s)= E[e(t)e(t + r)e(t + s)] for a zero mean stationary random time series. The asymptotic properties of the test statistic are rigorously determined. This test is important for the validation of the sampling properties of the parameter estimates for standard finite parameter linear models when the unobserved input (innovations) process is white but not gaussian. The sizes and power derived from the asymptotic results are checked using artificial data for a number of sample sizes. Theoretical and simulation results presented in this paper support the proposition that the test wi.