Miracle-dz/UniFAR-FTUs huggingface dataset:
“Fake News Detection Using Machine learning”

Fake news has been a social issue and in the era of digitization, a common man has easy access to all the data shown online. Fake news, one of the biggest problem in new era, is so powerful that it can change ones opinion and can make wrong impact while taking decisions. There are few plugins available on web browsers which give real time information regarding authenticity of news. Selection of algorithms to build these plugins make a huge impact on them. So, the motive is to build a project that would suggest which could be the best algorithm among the three implemented algorithms for further development by the developer. Algorithms being implemented for the comparison are Support Vector Machine, Naive Bayes Algorithm and Logistic Regression Algorithm.
Seismic Response Characteristics of Saturated Sand Deposits Mixed with Tire Chips

With the objective of better and more environmentally friendly recycling methods, many researchers are now examining the use of scrap tires as a new geomaterial. Based on past research, it was clear that tire chips reduce the rise of excess pore-water pressure when subjected to earthquake shaking. Based on such characteristics, online pseudodynamic response tests were conducted in this study on model grounds consisting of either tire chip-mixed sand or alternating layers of sand and tire chips with the aim of clarifying the seismic response characteristics of tire chips and tire chip-sand mixtures. Online testing is a method of feeding soil response characteristics directly from soil samples into a one-dimensional modeling algorithm. The test results showed that when tire chips with low stiffness were either mixed with sand or placed as layers, more significant damping and seismic isolation effects were observed. The presence of tire chips also reduced the accumulation of excess pore-water pressure in the layer, preventing the occurrence of liquefaction. In addition, when tire chips are installed as layers beneath the sand, liquefaction is not generated in the upper sandy layer because the amplitudes of the seismic waves are attenuated. Finally, the effectiveness of tire chips mixed with sand increased as the mix ratio was increased. When they were installed as pure layers, tire chips were more effective when placed at a deeper location or when the layer was thicker.
Assembling three one‐camera images for three‐camera intersection classification

Determining whether an autonomous self‐driving agent is in the middle of an intersection can be extremely difficult when relying on visual input taken from a single camera. In such a problem setting, a wider range of views is essential, which drives us to use three cameras positioned in the front, left, and right of an agent for better intersection recognition. However, collecting adequate training data with three cameras poses several practical difficulties; hence, we propose using data collected from one camera to train a three‐camera model, which would enable us to more easily compile a variety of training data to endow our model with improved generalizability. In this work, we provide three separate fusion methods (feature, early, and late) of combining the information from three cameras. Extensive pedestrian‐view intersection classification experiments show that our feature fusion model provides an area under the curve and F1‐score of 82.00 and 46.48, respectively, which considerably outperforms contemporary three‐ and one‐camera models.
Extending the technology acceptance model: A n investigation o f f actors affecting college students’ downloading of smart phone fitness applications

Technology Acceptance Model (TAM) is widely applied to explain how users come to adopt a new technology. Motivated by the need to have a better understanding of the rapid growth of fitness application s (apps) on smartphones , this study test s a n extension of the TAM model through explain ing how social influence and application characteristics affect college student s’ behavioral intention of downloading fitness applications to their smart phones. Based on a survey and a series of regression analys e s , the results confirm the effect s of two majo r determinants — perceived usefulness and perceived ease of use — on users ’ attitude toward using fitness apps . In addition, the findings show that electronic word of mouth ( eWOM ) and application characteristics significantly influence downloading of f itness apps . Finally, the results underline the crucial role of apps functional features. By adding external factors, the proposed research model fits in the context of fitness apps, and fills the literature gap by identifying how to motivate individuals to download fitness apps. The study provide s researchers and marketers with empirical evidence about college students ’ reasons for selection of fitness apps.
Controlling Output Voltage and Correcting Power Factor Using Fractional PI Controller with Average Current Method in Wireless Energy Transfer

: Single-phase AC/DC converters with Power Factor Correction (PFC) circuit are used as full-wave controlled rectifiers in many power electronics circuits to provide high standards of efficiency and improve power quality. In parallel with the changes in the circuit topologies used, new algorithms are being developed in control methods. In recent years, new control and modeling methods using fractional derivatives and integrals have been developed. In this study, it is aimed to correct the power factor on AC side of the circuit and to keep the output voltage constant at the desired value by using a boost converter for wireless energy transfer. Fractional order PI (FOPI) controller is used to control output voltage and a classical PI controller is used to generate a reference current of boost converter. The Particle Swarm Optimization method was used to optimize the controller coefficients. As a result of the simulation studies, the power coefficient was kept at 0.99
Autologous transplantation of P63+ lung progenitor cells for chronic obstructive pulmonary disease therapy

Adult lung resident stem/progenitor cells, including P63+ progenitor cells, have demonstrated the capacity for regeneration of lung epithelium in preclinical models. Here, we report a clinical trial of intrapulmonary P63+ progenitor cell transplantation in 28 participants with stage II to IV chronic obstructive pulmonary disease (COPD). Autologous P63+ progenitor cells were isolated from the airway basal layer of participants in the intervention group via bronchoscopic brushing, cultured for 3 to 5 weeks, and then transplanted back into the lungs via bronchoscopy at 0.7 × 106 to 5.2 × 106 cells per kilogram of body weight. Twenty patients were evaluable at the end of the study (intervention group, n = 17; control group, n = 3). No grade 3 to 5 adverse events (AEs) or serious AEs occurred. Although bronchoscopy-associated AEs were recorded in participants in the intervention group, other AEs were not substantial different between groups. Twenty-four weeks after transplantation, participants in the intervention group displayed improvement in gas transfer capacity [diffusing capacity of the lung for carbon monoxide (DLCO) change from baseline: +18.2%], whereas the control group experienced a decrease (DLCO change from baseline: −17.4%; P = 0.008). Furthermore, participants in the intervention group showed >30-meter increase in walking distance within 6 minutes. Transcriptomic analysis of progenitor cells isolated from responding and nonresponding individuals in the intervention group showed that higher expression of P63 was associated with treatment efficacy. In conclusion, transplantation of cultured P63+ lung progenitor cells was safe and might represent a potential therapeutic strategy for COPD. Autologous P63+ lung progenitor cells can be expanded and safely transplanted into the airways of patients by bronchoscopy to treat COPD. Editor’s summary Chronic obstructive pulmonary disease (COPD) results in damage to both the airways and the lung parenchyma, but a treatment that potentially reverses this damage in patients has not yet been identified. Building on previous preclinical work, Wang and colleagues conducted an early, open-label clinical trial of autologous P63+ lung progenitor cells for the treatment of patients with COPD. Cells were collected during bronchoscopy, expanded over several weeks, and then were administered back into the patients’ lungs, again by bronchoscopy. The treated group showed improvements in the diffusing capacity of the lung for carbon monoxide and the 6-minute walk distance at 24 weeks’ follow-up, supporting further clinical studies of P63+ lung progenitor cells for the treatment of COPD. —Melissa L. Norton
A Method for Rapid Estimation of Moment Magnitude for Early Tsunami Warning Based on Coastal GPS Networks

The recent great earthquakes of 26 December 2004 (Sumatra, Indonesia, Mw 9.2), 26 February 2010 (Maule, Chile, Mw 8.8), and 11 March 2011 (Tohoku-oki, Japan, Mw 9.0) have once again brought to the forefront the urgent need for early tsunami warning. These warnings mostly rely on magnitude and location of an earthquake. A large/great magnitude subduction-zone earthquake with rupture area extending up to the trench is potentially a tsunamigenic event. The appropriate magnitudes for tsunami warning are those that are based on long-period seismic waves (Abe 1979), e.g. , the moment magnitude, Mw (Kanamori 1977). Recently, W -phase (the long-period wave that arrives between P and S waves) has been used to compute Mw (Kanamori and Rivera 2008; Hayes et al. 2009). This magnitude can be determined in a relatively short time. For example, the first moment tensor solutions of the Tohoku-oki earthquake, based on inversion of W -phase at teleseismic distances, became available in 20 min (Duputel et al. 2011). For this reason, Mw computed from W -phase is especially useful for tsunami alerts at distant sites. It is at local distances that early tsunami warning becomes difficult. Even then, Mw based on inversion of W -phase recorded at regional distances may be useful. Tests show that Mw of Mexican subduction thrust earthquakes, based on W -phase recorded on broadband, regional seismograms, can be estimated in ∼7 min after the occurrence of the event (Perez-Campos et al. 2010). In recent years there has been an increase in GPS stations along the coastal region of some subduction zones. Some of these stations are operated in continuous mode (either in real-time high-rate mode or periodic low-rate download mode), and others in campaign mode. Static displacement vectors obtained from GPS data …
Preschoolers’ cognitive-linguistic performance in different educational contexts

ABSTRACT Purpose: to investigate preschoolers’ cognitive-linguistic performance in different educational settings. Methods: thirty-nine children aged 4:0 to 5:11 years, enrolled in two private preschools from different Brazilian regions, were assessed with the Protocol for the Early Identification of Reading Problems, in the version adapted to preschool - which includes the following tests: alphabet knowledge; metaphonological skills; phonological working memory; rapid automatized naming; silent word reading; and hearing sentence comprehension based on figures. The groups were compared with the Mann-Whitney statistical test, and significant differences were set at p < 0.05. Results: as expected, data revealed different performances between preschoolers from the two schools. The worse results in both were related to rhyme production and rhyme identification, which reveals that phonological awareness is probably not being stimulated in these groups. Participants performed as expected or “under attention” in the other skills. Conclusion: the performances of preschoolers from both schools were identified and classified, revealing differences in cognitive-linguistic performances between the different educational settings. These results ratify the importance of a teaching approach that helps develop cognitive-linguistic skills, early in preschool.
Trace fossils from the Middle and Upper Eocene (Bartonian–Priabonian) molasse deposits of the Pamplona Basin (Navarre, western Pyrenees): palaeoenvironmental implications

An ichnological study was carried out in the Middle–Upper Eocene sedimentary succession of the Pamplona Basin. This succession represents the molasse stage of the western part of the South Pyrenean peripheral foreland basin and extends from deep‐marine turbiditic (Ezkaba Sandstone Formation) to deltaic (Pamplona Marl, Ardanatz Sandstone and Ilundain Marl formations) and marginal marine deposits (Liédena Sandstone Member, Gendulain Formation). The tectonosedimentary evolution of the basin can also be recognized by means of the ichnoassemblages preserved throughout the succession and by the ichnofacies analysis. A total of 23 ichnogenera and at least 28 ichnospecies have been identified. The assemblage of the Ezkaba Sandstone is characteristic of the deep‐sea Nereites ichnofacies. The Ophiomorpha rudis and the Paleodictyon ichnosubfacies can be differentiated in this unit, which are typical of channel axis and off‐axis environments. Trace fossils in the Ardanatz Sandstone and Ilundain Marl formations, with dominance of Thalassinoides and especially Ophiomorpha, could be related to the Cruziana ichnofacies, developed in relatively low‐energy environments, in semicohesive muddy substrates with intercalated silt and sand. The ichnofauna of the Liédena Sandstone Member is composed of bird tracks, and invertebrate horizontal and vertical structures. Microbial mat impressions also occur. The evidence suggests that microbial mats acted as a taphonomic bias favouring the preservation of vertebrate tracks and conditioning the presence of other trace fossils. Consequently, the assignation of this ichnofauna to a specific ichnofacies is tentative, most likely a combination of the Mermia and Scoyenia ichnofacies. Copyright © 2016 John Wiley & Sons, Ltd.
Statitical Testing of Optimality Conditions in Multiresponse Simulation-Based Optimization

This paper derives a novel procedure for testing the Karush-Kuhn-Tucker (KKT) first-order optimality conditions in models with multiple random responses.Such models arise in simulation-based optimization with multivariate outputs. This paper focuses on expensive simulations, which have small sample sizes. The paper estimates the gradients (in the KKT conditions) through low-order polynomials, fitted locally. These polynomials are estimated using Ordinary Least Squares (OLS), which also enables estimation of the variability of the estimated gradients. Using these OLS results, the paper applies the bootstrap (resampling) method to test the KKT conditions. Furthermore, it applies the classic Student t test to check whether the simulation outputs are feasible, and whether any constraints are binding. The paper applies the new procedure to both a synthetic example and an inventory simulation; the empirical results are encouraging.
Identification of non-point source pollution in the Miyun Reservoir watershed

A non-point source(NPS) pollution modeling system,the soil water and assessment tools for the Miyun Reservoir watershed,was used to identify temporal and spatial variations of NPS pollution in the watershed and to evaluate three pollution control scenarios.Soil and nutrient losses predominantly occurs during the flooding season,with nutrient losses during the flooding season reduced in dry hydrological years.Developed areas of agricultural and livestock production are key areas for NPS loadings,while areas covered by forests and grassland contributing less to the NPS loadings.Cutting livestock discharges and reducing fertilizer applications can efficiently reduce total nitrogen and total phosphorous loadings in the Chao River sub-watershed and can partially reduce total phosphorous loadings in the Bai River sub-watershed,but will have little effect in the total nitrogen loadings.Cutting domestic point sources in the towns of Dage and Chicheng will reduce total phosphorous loadings,but will have less effect on total nitrogen loadings.
Discernment of complex lithologies utilizing different scattering and textural components of SAR and optical data through machine learning approaches in Jaisalmer, Rajasthan, India

Abstract. Accurate lithological mapping is a difficult task through standard image processing techniques. We utilize the application of different machine learning (ML) algorithms on dual polarimetric synthetic aperture radar (SAR), optical data, and surface elevation images to map various lithologies in parts of Jaisalmer district of Rajasthan, India. Different SAR-derived textural and decomposition parameters were also used to improve the discrimination of various lithology units. Further, to improve the classification accuracy, different ML-based feature importance models, such as XGboost, decision tree, and random forest were implemented to select the useful bands for the classification of lithology. A total of 14 different ML classifiers were applied, and the best classifier was chosen after comparing their accuracies (overall accuracy, kappa coefficient, F1 score, and ROC-AUC curve) to map the lithology. Out of all of the classifiers used in this study, light gradient boosting machine (lightgbm) performed better in discriminating lithology (OA = 0.80, kappa coefficient = 0.75, and F1 score 0.79). In addition, the AUC values (>0.9 in all lithology units) were obtained for the “lightgbm” model, which is indicative of accurate discrimination of different lithological classes.
An empirical analysis of the factors driving customers’ purchase intention of green smart home products

With the improvement of consumers’ environmental awareness and the popularity of the Internet of Things, green smart home products (GSHPs) are becoming the dominant trend of future home life. This shift not only makes tedious home life easier and more convenient but also helps families save energy and reduce carbon emissions. However, given the impact of the current technological level, the proportion of users who actually purchase GSHPs remains small. Thus, seeking ways to promote the consumption of GSHPs has become an urgent issue. Hence, this study seeks to fill the gap in the existing research on green consumption behavior and obtain a full understanding of the factors influencing the purchase intention of GSHPs. To do so, this work uses task-technology fit theory and considers the actual situation of green smart home consumption to add social-technology fit into the original theoretical basis. In particular, this research focuses on middle- and high-end Chinese consumers who have experience in purchasing GSHPs. Moreover, it aims for an in-depth exploration of the formation mechanism of Chinese consumers’ purchase intention for GSHPs through structural equation modeling. Using survey data collected from 331 green smart home product users in China, the study empirically examines the relationships among autonomy, environmental agility, sense of belonging, and self-actualization, and both task-technology fit and social-technology fit, which are expected to shape the purchase intention of GSHP users. The empirical results provide broad support for our hypotheses. The results of this study offer important contributions to the increasing research on GSHPs consumption and shed light on the importance of both technology characteristics and the needs of users in achieving both task-technology fit and social-technology fit and, ultimately enhancing the users’ intention to purchase GSHPs.
Impact of Technology, Military, and Socio-Economic Welfare on Conflict in Indonesia and Japan

Conflicts are driven by various factors, but over time, conflicts have evolved in nature and complexity. In addition to traditional factors, the emergence of technology has played a significant role in shaping conflicts. Technological advancements also have been a driving force in shaping societies and economies, and impacting various sectors and aspects of life. Our research uses Structural Equation Model (SEM) analysis. We will analyze the direct and indirect impacts of digital connectivity, technology trade, military expenditure and personnel, and socio-economic welfare on conflicts and tensions in Indonesia and Japan. The findings of our study suggest that technology variables such as digital connectivity and technology trade have a positive effect on socio-economic welfare in Indonesia with coefficients 0.311 and 0.457. A similar thing also happened in Japan with coefficients 1.312 and 0.310. However, technology trade can increase conflicts and tensions in Indonesia with coefficients 0.796, and digital connectivity can increase conflicts and tensions in Japan with coefficients 0.761. Additionally, socio-economic welfare significantly reduces conflict in Japan.
Scale invariance in fluvial barforms: implications for interpretation of fluvial systems in the rock record

Understanding the controls on the size and shape of sandstone bodies deposited by fluvial systems is important in the reconstruction of ancient fluvial deposits and construction of quantitative reservoir models. Measurements and analyses of sandbodies from remotely sensed imagery have allowed quantification of width and length ratios of barforms in modern fluvial systems. For bank-attached bars the width:length ratios range between 0.12 and 0.47 (arithmetic mean: 0.25), for lateral bars between 0.19 and 0.42 (arithmetic mean: 0.30), for mid-channel bars between 0.09 and 0.49 (arithmetic mean: 0.28), and for point bars between 0.14 and 0.50 (arithmetic mean: 0.30). The majority of width:length ratios for all bar types range between 0.15 and 0.35. Examination of other parameters such as basin type, planform geometry, apparent stream width, river length, gradient over the investigated area, aggradational or degradational system, tectonic setting and climate do not significantly affect the width:length ratio. Therefore, the bar planform shape, the width:length ratio, can be considered to be scale invariant. The recognition that bar planform shape in fluvial systems is scale invariant will be useful in the construction of subsurface three-dimensional models of fluvial deposits with variable dimensions. Supplementary material: Data tables with information obtained for all of the rivers studied are available at http://www.geolsoc. org.uk/SUP18745.
Computational characterization of structural, optoelectronic and thermoelectric properties of some double half-Heusler alloys X2FeY′Sb2 (X: Hf, Zr ;Y′: Ni, Pd)

ABSTRACT A full-potential linear augmented plane wave (FP-LAPW) has been used to study the structural, electronic, and optical properties of double half-Heusler alloys X2FeY′Sb2 with X≡Zr, Hf and Y′≡Pd, Ni. Electronic band structures and densities of states calculations of the four studied double half-Heusler alloys indicate that they are semiconductors with an indirect gap. The optical spectra of dielectric constants, refractive indices, reflectivity, and light absorption are also discussed. In the energy range of 8–14 eV, the calculated optical properties and mainly the absorption spectrum show very high UV absorption. Additionally, DFT calculations were combined with Boltzmann transport theory to estimate the thermoelectric properties, such as the thermal and electrical conductivity, Seebeck coefficient, and figure of merit (ZT), versus the change of temperature and chemical potential. These alloys possess a suitable band gap for diverse optoelectronic applications, encompassing photovoltaics, UV sensors, and solar cells.