Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic image selection scheme utilizing comments for insertion of images into weblogs

This paper presents a scheme which utilizes comments given to images on an image-sharing site in order to obtain an appropriate image for insertion into poem-like weblogs (blogs) as a way to represent their atmosphere (impression). The result shows that utilizing comments is effective. To achieve this purpose, there are two issues: how impression words are extracted from blogs and how images representing the impression words are obtained. Assuming that it is important to obtain images representing the impression words, this paper focuses on only the latter issue. We hypothesize that comments and tags extracted from an image-sharing site can be adequate for obtaining images corresponding to impression words at low cost. In particular, utilizing comments can be more appropriate for the image search with impression words than utilizing tags because the impression words are often used in comments. Therefore, we propose a scheme which utilizes comments to obtain appropriate images. In order to investigate the effectiveness of utilizing comments, conformance between impression words and the images was evaluated. The rating for conformance is 3.5 on a scale of 1 to 5 when utilizing comments, which is 0.6 higher than when utilizing tags.
Probabilistic Measurement of Attributes: A Logit Analysis by Generalized Least Squares

The Rasch latent trait model is derived from a double exponential error theory similar to that utilized for random utility models in choice theory. This formulation imbues multi-attribute measurements with an important probabilistic interpretation; namely, that the brand measurement is the log odds for the brand being rated above the mid-point on a particular attribute scale. Hence, one may compare brand measurements across attributes and construct multi-attribute configurations such as that illustrated. In addition to this theoretical underpinning for rating scale theory, the present paper establishes a statistical inference for survey rating scales based upon generalized least squares. An important advantage of the present GLS analysis stems from its capability of testing various hypotheses concerning brand configurations in multi-attribute spaces.
Elements of the Transformation of Preschool Curriculum and Educational Practices

The development of a curriculum poses a challenge for theoreticians, practitioners and educational policy makers. The official curriculum of a country represents the guidelines that should serve as the basis on which practices are developed in educational institutions. However, every institution modifies and applies the curriculum differently. The level of a practitioner’s professional development, as well as the culture of the educational institution in question profoundly influence the manner in which the curriculum is evolving in a particular educational institution. For that reason, it is especially important to facilitate access to systematic and high-quality professional development for preschool teachers, so that they are capable of developing the curriculum in line with the challenges of our time and contemporary scientific findings on early childhood education and care. The practice of many preschool teachers in Croatia reflects an outdated understanding of educational work involving children, and the official curriculum does not have much of an impact on that fact. Despite the fact that the practices of individual preschool teachers, even within the same institution, can differ significantly, there are certain shared traditionalisms that represent a burden for practice in Croatian preschools, and that are not easily removed. In order to gradually remove them, i.e., replace them with more contemporary methods of educating children, it is necessary to first become aware of them, as it is precisely the lack of awareness that such traditionalisms exist that causes them to remain a part of the practice.
Optical determination of the direct bandgap energy of lead iodide crystals

The optical bandgap energy of lead iodide PbI2, grown by Bridgman’s method, is obtained by photoacoustic spectroscopy. Due to its potential applications, as a room temperature, semiconductor material detector, which may be used as a photocell, or as a x‐ and γ‐ray radiation detector, the physical properties of PbI2 have attracted much attention. We computed, by different methods the bandgap energy. We found the energy in a range 2.301±0.038⩽〈Eg〉⩽2.359±0.037 eV.
Improvement in Heart Failure Self-Care and Patient Readmissions with Caregiver Education: A Randomized Controlled Trial

Caregivers support heart failure (HF) self-care with little HF education. The purpose of this study was to evaluate the effectiveness of a caregiver-only educational intervention aimed at improving caregiver self-efficacy, perceived control, and HF knowledge, as well as patient self-care and 30-day cardiac readmission. In total, 37 patients and their caregivers were randomly assigned to a control condition or a caregiver-only educational intervention with telephone follow-up. Outcomes included patient 30-day cardiac readmission, patient self-care, caregiver self-efficacy, caregiver perceived control, and caregiver HF knowledge. Linear mixed model, Kaplan–Meier, and Cox regression analyses were used to determine the effects of the intervention on outcomes. Self-care maintenance (p = 0.002), self-care management (p = 0.005), 30-day cardiac readmission (p = 0.003), and caregiver perceived control (p < 0.001) were significantly better in the intervention group. The results suggest that interventions targeting caregiver HF education could be effective in improving HF patients’ 30-day cardiac readmissions, patient self-care, and caregiver perceived control.
Topical vanadate improves tensile strength and alters collagen organisation of excisional wounds in a mouse model

Wound dehiscence, oftentimes a result of the poor tensile strength of early healing wounds, is a significant threat to the post‐operative patient, potentially causing life‐threatening complications. Vanadate, a protein tyrosine phosphatase inhibitor, has been shown to alter the organisation of deposited collagen in healing wounds and significantly improve the tensile strength of incisional wounds in rats. In this study, we sought to explore the effects of locally administered vanadate on tensile strength and collagen organisation in both the early and remodelling phases of excisional wound healing in a murine model. Wild‐type mice underwent stented excisional wounding on their dorsal skin and were divided equally into three treatment conditions: vanadate injection, saline injection control and an untreated control. Tensile strength testing, in vivo suction Cutometer analysis, gross wound measurements and histologic analysis were performed during healing, immediately upon wound closure, and after 4 weeks of remodelling. We found that vanadate treatment significantly increased the tensile strength of wounds and their stiffness relative to control wounds, both immediately upon healing and into the remodelling phase. Histologic analysis revealed that these biomechanical changes were likely the result of increased collagen deposition and an altered collagen organisation composed of thicker and distinctly organised collagen bundles. Given the risk that dehiscence poses to all operative patients, vanadate presents an interesting therapeutic avenue to improve the strength of post‐operative wounds and unstable chronic wounds to reduce the risk of dehiscence.
Machine Learning Methods for Predicting the Popularity of Movies

The movie industry has grown into a several billion-dollar enterprise, and there is now a ton of information online about it. Numerous machine learning techniques have been created by academics and can produce effective classification models. In this study, different machine learning classification techniques are applied to our own movie dataset for multiclass classification. This paper's main objective is to compare the effectiveness of various machine learning techniques. This study examined five methods: Multinomial Logistic Regression (MLR), Support Vector Machine (SVM), Bagging (BAG), Naive Bayes (NBS) and K-Nearest Neighbor (KNN), while noise was removed using All K-Edited Nearest Neighbors (AENN). These techniques all utilize previous IMDb dataset to predict a movie's net profit value. The algorithms predict the profit at the box office for each of these five techniques. Based on the dataset used in this paper, which consists of 5043 rows and 14 columns of movies, this study evaluates the performance of all seven machine learning techniques. Bagging outperformed other machine learning techniques with a 99.56% accuracy rate.
Using Dynamic Structural Equation Modeling to Examine Between- and Within-Persons Factor Structure of the DASS-21

The recent integration of traditional time series analysis and confirmatory factor analysis techniques allows researchers to evaluate the psychometric properties of measurement instruments at between- and within-persons levels while accounting for autoregressive dependencies. The current study applies a dynamic structural equation modeling (SEM) latent factor analysis (i.e., DSEM-CFA) to a sample of 333 individuals who completed the DASS-21 at their regular therapy sessions. The results of the DSEM-CFA illuminate the reliability, invariance, and structural features of each DASS-21 subscale both between and within persons. The results suggest that the DASS-21 reliably measures depression, anxiety, and stress symptoms when evaluating differences between persons, but does not reliably assess within-persons fluctuations in symptoms over time. The results also suggest that currently accepted methods of modeling sensitivity to change within an instrument are likely lacking and the DSEM-CFA provides insight into reliability within and between persons, which is extremely important for instruments used across time.
Investigation of Microstructure, Residual Stress, and Hardness of Ti-6Al-4V after Plasma Nitriding Process with Different Times and Temperatures

The residual stress and hardness generated by the nitriding process are important parameters for increasing the bending fatigue strength to Ti-6Al-4V. Therefore, this research is focused on the analysis of residual stress and hardness, including surface morphology and microstructure generated by the nitriding process at different times and temperatures. The plasma nitriding at temperatures of 750 °C and 800 °C with times of 5 h and 10 h were selected in this research. After plasma nitriding, the material would have residual compressive stress and higher hardness, including changes in the surface morphology and microstructure. The results also indicated that higher temperature and processing times generated more surface roughness and thickness in the compound layer, resulting in higher surface hardness. Moreover, higher time and temperature could generate deeper residual compressive stress and case depth hardness. This research revealed maximum hardness in the cross-sectional analysis of 643 HV and residual compressive stress of −65.3 MPa. In conclusion, the depth of the residual stress and case depth hardness were well compatible with the depth of the diffusion layer of plasma-nitrided Ti-6Al-4V, which confirmed the effect of plasma nitriding.
Another Interpretation of the Disk-Line Profile for the Seyfert 1 Galaxy MCG-6-30-15

The Seyfert 1 galaxy MCG−6-30-15 is a representative object possessing a “disk-line” (a broad and skewed feature around 5–7 keV in an X-ray spectrum). Using the longest MCG−6-30-15 observation with ASCA, Matsumoto et al. (2003, PASJ, 55, 615) found an interesting time-variability: the RMS variability as a function of a time-bin-width decreases more rapidly in the disk-line energy band (5.0–6.6 keV) than those in the other energy bands, as the time-bin-width increases from ∼ 104 s to ∼ 105 s. In this paper, we argue that this energy-dependent change in the RMS variability as a function of the time-bin-width is difficult to be reproduced by simply considering the variability of a “disk-line”, but that the RMS variability of the continuum component should have an energy-dependent evolution associated with the time-bin-width change. Such an energy-dependent variability of the continuum component can be realized by introducing absorption components with the typical variation time scale longer than that of the continuum. In this interpretation, a significant part of the broad excess feature in 5–7 keV is considered to be the result of a transparent spectral window of the warm absorbers.
Quality Characteristics and Acceptance Intention for Healthcare Kiosks: Perception of Elders from South Korea Based on the Extended Technology Acceptance Model

This study aimed to perform a path analysis to understand the effects of quality characteristics on perceived usefulness, perceived ease to use, involvement, and acceptance intention of healthcare kiosks in elderly using the extended technology acceptance model. We performed structural equation modeling (SEM) with data from 300 elderly. The following results were obtained. Firstly, elderly’s perceived quality characteristics of healthcare kiosks had a partial positive effect on perceived usefulness. Secondly, elderly’s perceived quality characteristics of healthcare kiosks had a partial positive effect on perceived ease to use. Thirdly, elderly’s perceived ease to use healthcare kiosks had a partial positive effect on perceived usefulness. In addition, elderly’s perceived usefulness of healthcare kiosks had a positive effect on acceptance intention. Lastly, elderly’s perceived ease to use healthcare kiosks had a positive effect on acceptance intention.
The asymmetric 4.8 hour X-ray modulation of Cygnus X-3 - Model light curves and inferred orbital parameters

We show that the 4.8 hour X-ray light curve of Cygnus X-3, as observed by the Einstein (HEAO 2) X-Ray Observatory in 1978 December, can be quantitatively described by several models proposed for this source, under the assumption that the heat binary orbit of Cyg X-3 is elliptic. We infer orbital parameters for Cyg X-3 from these models. We find that the cocoon model for Cyg X-3 implies an apparent size for the X-ray star's companion which is larger than that of its critical lobe; we suggest that the emission of a dense stellar wind by the companion could lead to this situation, and we discuss some characteristics of such a hybrid wind-cocoon model.
An In-Silico Evaluation of Anthraquinones as Potential Inhibitors of DNA Gyrase B of Mycobacterium tuberculosis

The World Health Organization reported that tuberculosis remains on the list of the top ten threats to public health worldwide. Among the main causes is the limited effectiveness of treatments due to the emergence of resistant strains of Mycobacterium tuberculosis. One of the main drug targets studied to combat M. tuberculosis is DNA gyrase, the only enzyme responsible for regulating DNA topology in this specie and considered essential in all bacteria. In this context, the present work tested the ability of 2824 anthraquinones retrieved from the PubChem database to act as competitive inhibitors through interaction with the ATP-binding pocket of DNA gyrase B of M. tuberculosis. Virtual screening results based on molecular docking identified 7122772 (N-(2-hydroxyethyl)-9,10-dioxoanthracene-2-sulfonamide) as the best-scored ligand. From this anthraquinone, a new derivative was designed harbouring an aminotriazole moiety, which exhibited higher binding energy calculated by molecular docking scoring and free energy calculation from molecular dynamics simulations. In addition, in these last analyses, this ligand showed to be stable in complex with the enzyme and further predictions indicated a low probability of cytotoxic and off-target effects, as well as an acceptable pharmacokinetic profile. Taken together, the presented results show a new synthetically accessible anthraquinone with promising potential to inhibit the GyrB of M. tuberculosis.
DPGCN Model: A Novel Fault Diagnosis Method for Marine Diesel Engines Based on Imbalanced Datasets

The class imbalance problem is prevalent in the condition monitoring (CM) data of marine diesel engines. That significantly deteriorates the diagnostic performance of a data-driven fault diagnosis. In this article, a novel fault diagnosis method named graph convolutional network (GCN) based on the distance and probability topological graphs (DPGCN) model is proposed for solving the problem of imbalanced classification. First, the collected CM dataset is transformed into two topological graphs—the distance topological graph and the probability topological graph—by exploring the similarity between samples from the linear and nonlinear relationships. Graph learning is then introduced to learn and extract the correlation between adjacent samples in addition to the samples’ own features, which provides more topological information for this imbalanced classification task. After multilayer graph learning, two feature embeddings based on samples’ features and topological graphs are learned, and a self-attention mechanism substantially fuses these two embeddings into one combination embedding to derive deeper correlation information for the fault diagnosis. The collected dataset of a marine diesel engine shows that the proposed DPGCN model can improve the classification accuracy and stability under the imbalanced datasets.
Vortex stripping and the erosion of coherent structures in two‐dimensional flows

This paper studies the erosion of a monotonically distributed vortex by the joint action of inviscid stripping, induced by an externally imposed adverse shear, and viscous diffusion, either in the form of Newtonian viscosity or hyperviscosity. It is shown that vortex erosion is greatly amplified by the presence of diffusion; abrupt vortex breakup or gradual quasi‐equilibrium evolution depend crucially on the strain to peak vorticity ratio and on the Reynolds number. Peculiar, unexpected effects are observed when hyperviscosity is used in place of Newtonian viscosity.
An evidence review and nutritional conceptual framework for pre-eclampsia prevention

Abstract Pre-eclampsia is a serious complication of pregnancy, and maternal nutritional factors may play protective roles or exacerbate risk. The tendency to focus on single nutrients as a risk factor obscures the complexity of possible interactions, which may be important given the complex nature of pre-eclampsia. An evidence review was conducted to compile definite, probable, possible and indirect nutritional determinants of pre-eclampsia to map a nutritional conceptual framework for pre-eclampsia prevention. Determinants of pre-eclampsia were first compiled through an initial consultation with experts. Second, an expanded literature review was conducted to confirm associations, elicit additional indicators and evaluate evidence. The strength of association was evaluated as definite relative risk (RR) < 0·40 or ≥3·00, probable RR 0·40–0·69 or 1·50–2·99, possible RR 0·70–0·89 or 1·10–1·49 or not discernible RR 0·90–1·09. The quality of evidence was evaluated using Grading of Recommendations, Assessment, Development and Evaluation. Twenty-five nutritional factors were reported in two umbrella reviews and twenty-two meta-analyses. Of these, fourteen were significantly associated with pre-eclampsia incidence. Higher serum Fe emerged as a definite nutritional risk factors for pre-eclampsia incidence across populations, while low serum Zn was a risk factor in Asia and Africa. Maternal vitamin D deficiency was a probable risk factor and Ca and/or vitamin D supplementation were probable protective nutritional factors. Healthy maternal dietary patterns were possibly associated with lower risk of developing pre-eclampsia. Potential indirect pathways of maternal nutritional factors and pre-eclampsia may exist through obesity, maternal anaemia and gestational diabetes mellitus. Research gaps remain on the influence of household capacities and socio-cultural, economic and political contexts, as well as interactions with medical conditions.
Hyperbolic distributions in finance

Distributional assumptions for the returns on the underlying assets play a key role in valuation theories for derivative securities. Based on a data set consisting of daily prices of the 30 DAX shares over a three-year period, we investigate the distributional form of compound returns. After performing a number of statistical tests, it becomes clear that some of the standard assumptions cannot be justified. Instead, we introduce the class of hyperbolic distributions which can be fitted to the empirical returns with high accuracy. Two models based on hyperbolic Levy motion are discussed. By studying the Esscher transform of the process with hyperbolic returns, we derive a valuation formula for derivative securities. The result suggests a correction of standard Black-Scholes pricing, especially for options close to expiration.
Box–Behnken Design Used to Optimize the Simultaneous Quantification of Amitriptyline and Propranolol in Tablet Dosages by RP-HPLC-DAD Method and Their Stability Tests

This study’s goal is to use a Box–Behnken design [BBD] methodology to create a new reverse-phase high-performance liquid chromatography diode-array detection [RP-HPLC-DAD] method for the simultaneous quantification of Amitriptyline and Propranolol in tablet dosages. The amitriptyline and propranolol standard drug peaks were obtained using a C-18 column with a dimension of 4.6 × 100 mm and a particle size packing of 2.5 µm at the retention time of 5.328 and 7.48 min, respectively. The mobile phase composition was a 75:25 mixture of methanol and 0.1 percent orthophosphoric acid, flowing at 1.0 mL/min at 26 °C. The peaks were identified at 257 nm after injecting 20 µL of the sample. An assay of the marketed tablets was performed, and the result was 101.33 and 99.4% for amitriptyline and propranolol, respectively, when compared to the standard calibration curve. Forced degradation investigations, such as acid, base, H2O2, and neutral condition, were performed. The results for both medications in term of % degradation were as follows: amitriptyline (16.07, 91.92, 26.98, and 0.64) and propranolol (15.84, 11.52, 9.09, and 3.62). According to the ICH criteria, the findings of the validation parameters were within an acceptable range. The new RP-HPLC-DAD method with BBD application is easy, accurate, and time-saving.
The Impact of the COVID-19 Pandemic on Lifestyle and Wellbeing of Children, Adolescents and Their Parents: A Qualitative Study

Prior studies have shown that changes in daily structure and habits due to the COVID-19 pandemic affected the lifestyle and wellbeing of families. This study aimed to obtain in-depth information on children’s and adolescents’ experiences regarding their lifestyle and wellbeing during the pandemic. Semi-structured interviews with fifteen families were carried out between May and November 2021. Directed content analysis was used to analyze the transcripts and fundamental qualitative description to describe the results. Children and adolescents revealed an overall unhealthier lifestyle and decreased wellbeing. These negative effects were even larger in adolescents and children with overweight or psychosocial complaints. Our results revealed that parents were actively involved in maintaining a normal daily structure. Furthermore, diet changes were inconsistent and dependent on food availability. An increase in screen time was experienced as inevitable, and external influences were necessary to keep children and adolescents active. Almost no effects were reported on physical health, whereas negative emotions were experienced in varying degrees. Moreover, the decrease in social interactions was reported as the most negative effect of the pandemic. The above-mentioned insights may contribute to the development of preventive measures to promote a healthy lifestyle and wellbeing of children and adolescents during future pandemics.