Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of flipped learning-based smoking cessation intervention education program for nursing students in South Korea

Purpose: The goal of this study was to see how flipped learning affected nursing students in South Korea who were enrolled in a quit smoking intervention education program. The flipped learning-based quit smoking intervention education program was developed to help nursing students implement the intervention. Methods: This quasi-experimental study was conducted using a pretest-posttest design. A total of 52 nursing students, divided into experimental and control groups of 26 each, participated between November and December 2021. The experimental group was instructed in the flipped learning-based quit smoking intervention education program over six sessions. In accordance with flipped learning, each session was composed of pre-class, in-class, and post-class sections. Results: Compared to the control group, the experimental group showed improved beliefs about the health benefits of quitting smoking, as well as positive attitudes and self-efficacy from the quit smoking intervention. The experimental group experienced the greatest increase in student-centered activities and student participation through flipped learning. Conclusion: These results indicate that the flipped learning method was effective in quit smoking intervention education for nursing students. Therefore, it is worthwhile to consider that a quit smoking intervention education program based on flipped learning be included in the regular nursing curriculum.
Discovering Common miRNA Signatures Underlying Female-Specific Cancers via a Machine Learning Approach Driven by the Cancer Hallmark ERBB

Big data processing, using omics data integration and machine learning (ML) methods, drive efforts to discover diagnostic and prognostic biomarkers for clinical decision making. Previously, we used the TCGA database for gene expression profiling of breast, ovary, and endometrial cancers, and identified a top-scoring network centered on the ERBB2 gene, which plays a crucial role in carcinogenesis in the three estrogen-dependent tumors. Here, we focused on microRNA expression signature similarity, asking whether they could target the ERBB family. We applied an ML approach on integrated TCGA miRNA profiling of breast, endometrium, and ovarian cancer to identify common miRNA signatures differentiating tumor and normal conditions. Using the ML-based algorithm and the miRTarBase database, we found 205 features and 158 miRNAs targeting ERBB isoforms, respectively. By merging the results of both databases and ranking each feature according to the weighted Support Vector Machine model, we prioritized 42 features, with accuracy (0.98), AUC (0.93–95% CI 0.917–0.94), sensitivity (0.85), and specificity (0.99), indicating their diagnostic capability to discriminate between the two conditions. In vitro validations by qRT-PCR experiments, using model and parental cell lines for each tumor type showed that five miRNAs (hsa-mir-323a-3p, hsa-mir-323b-3p, hsa-mir-331-3p, hsa-mir-381-3p, and hsa-mir-1301-3p) had expressed trend concordance between breast, ovarian, and endometrium cancer cell lines compared with normal lines, confirming our in silico predictions. This shows that an integrated computational approach combined with biological knowledge, could identify expression signatures as potential diagnostic biomarkers common to multiple tumors.
International benchmarking of longitudinal train dynamics simulators: benchmarking questions

ABSTRACT Longitudinal train dynamics (LTD) simulations have been playing an instrumental role in the development of larger trains, especially freight trains. LTD simulators have been reported from all around the world, but without standards or standard questions to assess the correct implementation of LTD analysis and the state of LTD studies. Under this situation, the Centre for Railway Engineering initiated the International Benchmarking of Longitudinal Train Dynamics Simulators. Eight teams involving 10 institutions from five countries across three continents have participated in the benchmark and submitted their results. This paper describes the benchmarking questions so other researchers will be able to repeat the simulations in the future and benchmark their programs against the current participating software. The question information includes train configurations and characteristics of the wagon connection system, locomotive traction and dynamic brake characteristics, resistance formula, track data, train driving controls and output requirements. The question information will also enable researchers to replicate the benchmark by providing relevant formulas, data sheets, figures and descriptions.
Prevalence of spinal disorders in Saudi population using conventional radiology: Age and gender correlation

Background: Despite its limitations in diagnosing certain spinal cord and spinal column disorders, conventional radiography can be employed as the first imaging modality in patients presenting with spinal disorders caused by bone abnormalities. Material and methods: A retrospective study conducted in Taif City-Kingdom of Saudi Arabia's King Abdul-Aziz Specialist Hospital and King Faisal Hospital from November 2020 to February 2021 to evaluate spinal diseases in Saudi population using conventional X-ray in Al-Taif city. The data was collected after receiving ethical approval from the administration of research and studies in the directorate of health affairs-Taif, and then analyzed using SPSS version 23, descriptive statistics were used to assess the frequency and percentage of disorder, and then Pearson's chi square test was used to correlate the prevalence with age and gender. Results: Scoliosis is the most common spinal disorder among the selected sample (73.4 percent), scoliosis occurs more frequently in females, while transitional lumbosacral vertebrae affect males more than females regardless of the number of females in the study sampling, no There was a substantial relationship found between age, gender, and spinal disorders seen on conventional radiography (p – value > 0.05). Conclusion: The study concluded that the most common spine disorder diagnosed by conventional radiology among selected sample is scoliosis, with the younger age groups are more affected.
SPATIAL PATTERN ANALYSIS THROUGH DISTRIBUTION METRICS

Abstract. Moving from the controversial results on the link between urban structure and performance aspect, this article wants to encourage the development of the independent research on urban structure, and more generally on spatial patterns, at different scales to enable future further correlations with a wider set of performance aspects (environmental, social, economic, medical). The work also exploits the potential of several unsupervised learning algorithms, whose performance and power are increasingly promising and whose use is becoming more widespread in different fields; but for which there are still many challenges concerning the correct application in urban areas and the interpretability of the results. We propose an approach for the creation of new spatial attributes and metrics (features) aiming to quantitatively describe the qualitative distribution of objects (e.g., buildings) in a 2D space. It explores an incremental bottom-up process for the creation of groups of objects (e.g., urban patches) and the evaluation of their physical properties alone and in respect with a sample area at each iteration. The process consists of 7 phases: data preparation, data processing, parameters collection, feature calculation, feature selection, clustering, results comparison. The results can be mainly divided in two. First, the feature selection allowed to extract a minimum set of non-redundant, valid, and consistent features that can explain qualitative distribution aspects of spatial patterns. Second, the comparison between feature-based and neural network clustering, gave useful insights for a preliminary understanding of unsupervised learning techniques internal mechanisms.
Trans-orbital sonographic assessment of optic nerve diameter in a sampled Nigerian population

Background: Studies have reported variants in the dimensions of optic nerve diameter among different ethnic groups, just as other body anatomy differs from regions to regions.Aim: To establish normal range of optic nerve diameter in a sampled Nigerian population, sonographically.Materials and Method: A total of 725 apparently healthy adult subjects (362 males aged 32 to 65 years and 363 females aged 30 to 68 years) were recruited from the South South and South Eastern parts of Nigeria for this prospective descriptive study. The optic nerve diameter (OND) was measured using a high-resolution digital dedicated small-parts real time ultrasound machine (Sonoace 5500; Medicol, Medison, Miami, FL, USA) with a high frequency (10-MHz) linear array transducer. Subjects were in supine position and were asked to keep their eyes closed and still. Coupling gel was placed on the closed eye lid with the transducer softly placed over the upper temporal eyelid in an axial plane. The OND was measured perpendicular to the vertical axis of the scanning plane as a horizontal distance between the two walls of the nerve sheath. The height and weight of the subjects were determined using a meter rule and a weighing scale.Results: The mean optic nerve sheath diameter of males and females was 4.2 ± 0.13 mm. It ranged from 4.0 to 4.45 mm. The optic nerve sheath diameter of males was not significantly different from that of females (p = 0.345). No significant difference between the mean OND of both eyes (p = 0.345). Body mass index and age did not have any association with OND (r = 0.017, 0.034), the data were normally distributed.Conclusion: Optic nerve diameter of apparently normal Nigerian adults ranges from 4.0 to 4.5 mm. Values outside this range may demand further evaluation in the study population.
Discovery of the Earliest Rice Paddy in the Mixed Rice–Millet Farming Area of China

Neolithic rice remains were recovered from a mixed rice–millet farming area in China outside the original centers of rice farming. Whether the rice remains were the result of local cultivation or obtained through trade remains unclear. Rice paddy fields are direct evidence of local cultivation. In this study, phytolith samples from the Zhangwangzhuang site were analyzed. The discriminant function distinguished 17 of 30 samples in the suspected paddy field area as rice paddy fields with an average probability of 74%; The proportion of rice bulliform phytoliths with ≥9 scales indicated that rice (Oryza sativa) was still being domesticated and, moreover, six η-type phytoliths from broomcorn millet (Panicum miliaceum) were identified. These results suggested that the suspected paddy field at Zhangwangzhuang might be the earliest rice paddy field (ca. 6000 cal. BP) in northern China and that mixed farming was practiced here since the early Yangshao period. This study adopted discriminant analysis methods to discover ancient rice paddy fields, observed rice paddy fields outside the core rice origin area, and provided the earliest evidence regarding the development of mixed rice–millet farming in the upper Huai River region.
Is Islamic banking stronger than conventional banking during the Covid-19 pandemic? Evidence from Indonesia

Purpose – We intended to test and compare the durability of Islamic banking and conventional banking during the Covid-19 pandemic in Indonesia. To that end, we first compared their performance before and during the pandemic. Next, we examined the effects of pandemic shocks on the performance of each of them.Methodology – The data covers 80 banks in Indonesia, which were divided into four groups, namely Islamic and conventional commercial banks, and Islamic and conventional rural banks. Each group consisted of 20 banks. Our observation period is 10 quarters, which was divided into two periods, namely the period before the pandemic (Q1-2019 – Q1-2020) and the period during the pandemic (Q2-2020 – Q2-2021). For comparison, we used a paired sample t-test, while testing the effect of shocks using a panel regression model.Findings – Islamic banking outperformed conventional banking, both before and during the Covid-19 pandemic. The Covid-19 pandemic has predominantly shaken conventional banking indicators and has only slightly shaken Islamic banking. However, this does not mean Islamic banks were superior to their conventional counterparts because both were shaken, it's just that conventional banks experienced a bigger shock than their Islamic counterparts.Originality – This is an original study that examines and compares the performance between Islamic and conventional banking using financial ratios during the Covid-19 pandemic.
Quantitative Study on the Law of Surface Subsidence Zoning in Steeply Inclined Extra-Thick Coal Seam Mining

The damage of overlying strata and ground surface caused by the one-time mining space is relatively severe in steeply inclined extra-thick coal seams. The unique law of surface subsidence at these conditions is still missing. Taking Huating Dongxia Coal Mine as the research background, this paper reveals the law-governing effects on rock strata and surface movement and deformation caused by steeply inclined extra-thick coal seam mining with different coal seam dip angles and coal thicknesses by using the methods of surface measurement, theoretical analysis, and numerical simulation. Based on the characteristics of the surface inclination deformation, the surface is divided into four areas along the tendency section line—namely, an outcrop discontinuous deformation area, an overall subsidence area, a gradual subsidence area, and a slight subsidence area. The results show that the influence of the coal seam dip angle on surface subsidence zoning in steeply inclined and thick coal seams is mainly reflected in the affected area range and the form of damage. Coal thickness has a weak effect on the form of rock strata damage and surface movement. Utilizing the influence of the coal seam dip angle and coal seam thickness on the change in the surface subsidence zoning, the calculation formulas for each area range and zoning angle in relation to the coal seam dip angle, coal thickness, mining depth, and vertical stage height are established. The research results can provide a reference to evaluate the influence of mining, especially in steeply inclined extra-thick coal seams.
Comparison of Two Versions of SWAT Models in Predicting the Streamflow in the Xuanmiaoguan Reservoir Catchment

Correct streamflow prediction is critical for determining the availability and efficiency of watershed spatial plans and water resource management. In the Xuanmiaoguan (XMG) Reservoir Catchment, two different versions of the Soil and Water Assessment Tool (SWAT) model are compared to discharge predictions. One version is the Topo-SWAT, in which the overland flow is generated by saturation excess (Dunne) runoff mechanism, while the other is driven by infiltration excess runoff mechanism, i.e., the Regular-SWAT. These SWAT models were calibrated and validated with discharge at daily and monthly steps, and then, the annual runoff volume and spatial distribution of runoff generation areas were also discussed. At the monthly scale, the un-calibrated Topo-SWAT model outperformed the un-calibrated Regular-SWAT model throughout the whole time (2010-2016). The Nash-Sutcliffe efficiency coefficients (NSE) using Topo-SWAT and Regular-SWAT were 0.59, 0.58 for calibration and 0.69, 0.72 for validation for daily streamflow, and 0.69, 0.65 for calibration and 0.73, 0.88 for validation for monthly streamflow, respectively, based on the parameter sensitivity analysis results. There was a 5-year understatement for yearly runoff volume using Regular-SWAT, but a 4-year underestimation using Topo-SWAT, which had a different year in 2015. Regular-SWAT and Topo-SWAT have significantly different geographical distributions of runoff generating locations within the watershed for one occurrence (greater rainfall). The findings reveal the most accurate contributing regions for runoff generation in the research catchment, allowing for more effective implementation of best management techniques (BMPs).
Unifying discrete and integral transforms through the use of a Banach algebra

ABSTRACT A weighted space is introduced and some of its properties are highlighted. This is done with the aim of defining a space such that the transform of a class of functions exists. Certain properties of a new class of discrete and integral transforms are highlighted, including the codomain of the transform being a set of continuous functions and continuity of the operator associated with the space. The shifting and convolution properties are introduced and it is proven that the weighted space is closed under the convolution operation. Several examples which fall in this class of transforms are given, including the Dirichlet series, the Z transform and the Laplace transform. Some conditions are stated which imply that any member of a class of discrete operators is injective. Following this, it is established that the weighted space is a Banach algebra where the convolution is the underlying product.
Sprint Interval Exercise Improves Cognitive Performance Unrelated to Postprandial Glucose Fluctuations at Different Levels of Normobaric Hypoxia

Objective: The aim of our study was to examine cognition response to sprint interval exercise (SIE) against different levels of hypoxia. Research design and methods: 26 recreational active males performed SIE (20 × 6 s of all-out cycling bouts, 15 s of passive recovery) under normoxia (FIO2: 0.209), moderate hypoxia (FIO2: 0.154), and severe hypoxia (FIO2: 0.112) in a single-blinded crossover design. Cognitive function and blood glucose were assessed before and after 0, 10, 30, and 60 min of the SIE. Heart rate (HR), peripheral oxygen saturation (SpO2), and ratings of perceived exertion (RPE, the Borg 6–20-point scale) during each SIE trial were recorded before and immediately after every five cycling bouts, and after 0, 10, 30, and 60 min of the SIE. Results: All the three SIE trials had a significantly faster overall reaction time in the Stroop test at 10 min after exercise as compared to that of the baseline value (p = 0.003, ƞ2 = 0.606), and returned to normal after 60 min. The congruent RT at 10 min after SIE was significantly shorter than that of the baseline (p < 0.05, ƞ2 = 0.633), while the incongruent RT at both 10 min and 30 min were significantly shorter than that measured at baseline (p < 0.05, ƞ2 = 0.633). No significant differences in terms of accuracy were found across the three trials at any time points (p = 0.446, ƞ2 = 0.415). Blood glucose was significantly reduced at 10 min and was sustained for at least 60 min after SIE when compared to pre-exercise in all trials (p < 0.05). Conclusions: Acute SIE improved cognitive function regardless of oxygen conditions, and the sustained improvement following SIE could last for at least 10–30 min and was unaffected by the altered blood glucose level.
Remaining Useful Life Prediction of Aircraft Engines with Variable Length Input Sequences

Remaining useful life (RUL) is the expected remaining operating life of an asset until it can no longer perform its intended function. The 2021 PHM Society Data Challenge posed the problem of estimating the RUL of aircraft engines with various competing failure modes and underlying degradation trajectories. In this work, we describe the approach and solution to the challenge where we map from the multivariate time series sensor readings to the remaining useful life, measured in the remaining number of flight cycles until failure. The proposed solution utilizes a deep convolutional neural network that can take inputs of variable length. Furthermore, we preprocess the data according to a normalization procedure that help reveal the degradation trend that is obfuscated by the continuously varying flight conditions. The normalization procedure involves training a feedforward neural network on a non-degraded subset of the data that maps from the flight conditions to the sensor outputs. The difference between the expected sensor readings and the actual observations is then interpreted as the extent of deviation from normal, i.e., degradation. Finally, we describe the sampling techniques which is designed to reduce the number of non-informative samples fed to the neural network.
Structural Transformation in India: The Role of the Service Sector

Labor productivity growth in India has been the fastest in the service sector. However, there is substantial heterogeneity within manufacturing and services. I disaggregate both sectors into high and low productivity growth sub-sectors. The data show that high productivity growth services grow faster than its manufacturing counterpart, contrary to the experience of industrialized countries. Furthermore, India’s supply of high-skilled workers is larger than that of other countries at similar stages of development. To understand the sources of differences in sectoral labor productivity growth, I construct a five-sector model of structural change with high and low-skilled workers including agriculture, two manufacturing and two service sub-sectors. The calibrated model suggests that the large supply of high-skill workers combined with higher skill intensity in the service sector seem to be behind the services take-off. Furthermore, the data imply that service sub-sectors are gross substitutes while manufacturing sub-sectors are gross complements. This will accelerate productivity growth in services and decelerate productivity growth in manufacturing. ∗I am indebted to Fidel Pérez-Sebastián and Ákos Valentinyi for their guidance, comments, and support. I also thank Javier Andrés Santiago, Luis Franjo, and Francesco Turino for their very helpful comments as well as the audiences of presentations at the University of Alicante and NWSSDTP PhD Conference 2019. Financial support from Spanish Ministry of Science, Innovation, and Universities (ECO2015-70540-P), is gratefully acknowledged. All possible mistakes are my own. †Departamento de Fundamentos del Análisis Económico (FAE), Universidad de Alicante, Campus San Vicente, 03690, Alicante, Spain. Email: r.serrano@ua.es
Advanced Glycations End Products in the Skin as Biomarkers of Cardiovascular Risk in Type 2 Diabetes

The incidence and prevalence of diabetes are increasing worldwide, and cardiovascular disease (CVD) is the leading cause of death among subjects with type 2 diabetes (T2D). The assessment and stratification of cardiovascular risk in subjects with T2D is a challenge. Advanced glycation end products are heterogeneous molecules produced by non-enzymatic glycation of proteins, lipids, or nucleic acids. Accumulation of advanced glycation end products is increased in subjects with T2D and is considered to be one of the major pathogenic mechanism in developing complications in diabetes. Skin AGEs could be assessed by skin autofluorescence. This method has been validated and related to the presence of micro and macroangiopathy in individuals with type 2 diabetes. In this context, the aim of this review is to critically summarize current knowledge and scientific evidence on the relationship between skin AGEs and CVD in subjects with type 2 diabetes, with a brief reference to other diabetes-related complications.