Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis and Application of Iron Oxide Nanoparticles in Bone Tissue Repair

Nanoparticles play a vital role in bone tissue repair engineering, especially iron oxide nanoparticles (IONPs), which have magnetic properties, semiconductor properties, and nontoxicity at the same time, and their applications in biomedicine have received widespread attention. This review summarizes the excellent performance of IONPs in enhancing scaffold functions, promoting stem cell differentiation, and labeling positioning, in order to understand the research progress and future development trends of IONPs in bone tissue repair engineering, as well as the security issues. Firstly, IONPs can affect the expression of genes and proteins to accelerate the process of biomineralization under a magnetic field. Then, the composite of IONPs and polymers can synthesize a scaffold which can promote the attachment, proliferation, and bone differentiation of stem cells. Furthermore, IONPs can also mark the location of drugs in the body to follow up the process of bone repair. Therefore, extensive research on the manufacturing and application range of IONPs is of great significance to bone tissue repair engineering.
Dynamical Computations of the FitzHugh- Nagumo Equation

The Hodgin-Huxley model is one of the most widely studied biological systems of nonlinear differential equations that is applied to explore nerve cells activities via electrical communications. In this paper we consider some numerical aspects of a simplifi ed version of this model known as the FitzHugh-Nagumo (FHN) equation. Dynamical experiments conducted herein not only confi rm those obtained from earlier studies but also facilitate a better understanding of the qualitative features of the FHN model especially those that initiate the behavior a threshold-triggered excitation media. To this end, methods of dynamical system analysis such as bifurcation and linear stability analysis are deployed to investigate the general qualitative features of an inhibitor-activator system which characterizes the FHN system of equations. Research Article Dynamical Computations of the FitzHughNagumo Equation Okey Oseloka Onyejekwe* The Robnello Unit for Continuum Mechanics Applications and Nonlinear Dynamics, Umuagu, Oshimili South, Asaba, Delta State, Nigeria Received: 16 August , 2021 Accepted: 31 August , 2021 Published: 01 September, 2021 *Corresponding author: Okey Oseloka Onyejekwe, The Robnello Unit for Continuum Mechanics Applications and Nonlinear Dynamics, Umuagu, Oshimili South, Asaba, Delta State, Nigeria, E-mail:
HOW A CONNECTIVE ACTION IS DISRUPTED IN RESTRICTIVE CONTEXTS? THE CASE OF DISMANTLING #RAPE ON PERSIAN TWITTER

Having reduced the cost of political activism, social media has provided room for ordinary citizens to engage in politics, build networks, spread information, and resist oppressive regulation (Howard & Hussain, 2013; Margetts et al., 2016). The ideas of connective action (Bennett & Segerberg, 2012) and hashtag activism (Jackson et al., 2020) are recent endeavors to theorize such transitions. However, the existing literature has overemphasized the positive side of social media platforms, in particular Twitter, in challenging inequalities, as well as in giving voice to marginalized groups (Lindgren, 2019; Wonneberger et al., 2020). While scholars, to a lesser extent, investigated how social media are used to suppress online protest from a normative and more general standpoint (Gunitsky, 2015), the ways that a connective action could be disrupted, e.g., by state actors has not received much scholarly attention yet. This has become particularly important in recent years, as several governments across the globe have adopted new tactics to dismantle connective actions, such as the coordinated dissemination of fake news. This study sheds light on such disruptive processes by investigating how a connective action in the Iranian Twittersphere (revolving around #rape , i.e., Iranian #MeToo) was derailed.
Computer model for tsunami vulnerability using sentinel 2A and SRTM images optimized by machine learning

This study aims to develop a software framework for modeling of tsunami vulnerability using DEM and Sentinel 2 images. The stages of study, are: 1) extraction Sentinel 2 images using algorithms NDVI, NDBI, NDWI, MSAVI, and MNDWI; 2) prediction vegetation indices using machine learning algorithms. 3) accuracy testing using the MSE, ME, RMSE, MAE, MPE, and MAPE; 4) spatial prediction using Kriging function and 5) modeling tsunami vulnerability indicators. The results show that in 2021 the area was dominated by vegetation density between (-0.1-0.3) with moderate to high vulnerability and risk of land use tsunami as a result of the decreasing of vegetation. The prediction results for 2021 show a low canopy density of vegetation and a high degree of land surface slope. Based on the prediction results in 2021, the study area mostly shows the existence of built-up lands with a high tsunami vulnerability risk (more than 0.1). Vegetation population had decreased to 67% from the original areas in 2017 with an area of 135 km2. Forest vegetation had decreased by 45% from 116 km2 in 2017. Land use for fisheries had increased to the area of 86 km2 from 2017 with an area of 24 km2.
Chemistry of hydroperoxycarbonyls in secondary organic aerosol

Abstract Highly oxidized multifunctional compounds (HOMs) formed through gas-phase reactions are thought to account for a significant fraction of the secondary organic aerosol (SOA) formed in low-nitric oxide (NO) environments. HOMs are known to be peroxide-rich and unstable in SOA, however, and their fate once they partition into particles is not well understood. In the study reported here, we identified particle-phase reactions and decomposition products for an α-alkoxy hydroperoxyaldehyde that served as a convenient model for HOMs, and also quantified rate and equilibrium constants for cyclic peroxyhemiacetal formation and the effects of particle acidity and relative humidity on reaction products and timescales for decomposition of peroxide-containing compounds. Sulfuric acid increased the rate of acetal formation and subsequent peroxide decomposition, but the effect was eliminated when aqueous seed particles were used in humid air, indicating that organic/aqueous phase separation can affect the ability of strong acids to catalyze these and other reactions in SOA. The results will be useful for understanding and predicting the atmospheric fate of organic peroxides and the effects of their particle-phase reactions on SOA composition. Copyright © 2018 American Association for Aerosol Research
A quantitative analysis of electronic transport in n- and p-type modulation-doped GaAsBi/AlGaAs quantum well structures

Electronic transport properties of as-grown and thermally annealed n- and p-type modulation-doped GaAsBi/AlGaAs quantum well (QW) structures were investigated. Hall mobility of as-grown, n- and p-type modulation doped QW structures are found from raw experimental data as ∼1414 and 95 cm2 Vs−1 at room temperature. A comparison between reported two-dimensional (2D) electron density determined from the analyses of Shubnikov de Haas oscillations and the 2D Hall electron density indicates a presence of parallel conduction in barrier layer (AlGaAs) and QW layer (GaAsBi) in n-type samples, therefore a parallel channel conduction theory is used to separate the electron mobility in the QW and the barrier layers in n-type modulation doped GaAsBi/AlGaAs QW structure. The extracted electron mobility of the as-grown n-type GaAsBi/AlGaAs QW sample is determined as ∼5975 cm2 Vs−1 at 4.2 K, which is closer to the electron mobility in GaAs. It is found that thermal annealing at lower temperature than growth temperature increases electron mobility of 2D electron gas, while annealing at higher temperature than growth temperature decreases electron mobility. The temperature dependence of the extracted electron mobility using parallel conduction approximation is analytically calculated by considering possible scattering mechanisms. Analysis of temperature-dependent electron mobility shows that the dominant scattering mechanisms are interface roughness (IFR), acoustic, and alloy-potential scatterings at low and intermediate temperature range, and IFR and optical phonon scattering at the high-temperature range in n-type modulation doped GaAsBi/AlGaAs QW structures.
Laboratory Observation of C and O Emission Lines of the White Dwarf H1504+65-like Atmosphere Model

White dwarfs play important roles in stellar evolution and help us gauge the age of our galaxy. The white dwarf H1504+65, the hottest known post-asymptotic giant branch star, is peculiar due to its C- and O-rich but He- and H- deficient atmosphere whose composition cannot be well predicted by current stellar evolution models. The analysis of the elemental abundance and the benchmark of stellar atmospheric models depends heavily on spectral data under cosmic conditions, which are currently extremely scarce. We created a well-defined, uniform, relatively large-scale ∼millimeter plasma sample in the laboratory with a temperature and a C/O ratio similar to those of H1504+65’s atmosphere. The emission spectra with high precision in the range of 10–80 nm were obtained and identified according to databases such as NIST and Kelly. A detailed comparison between our emission lines and the Chandra-observed white dwarf H1504+65 atmosphere’s absorption lines was performed. The stongly isolated O VI lines in the range of 10–13 nm are observed in both cases. We observed a wealth of O V lines in the range of 13–14 nm that cannot be well identified or predicted by models due to the weak flux and also probably due to the blending effect of Fe group elements in the Chandra spectrum. Long-wavelength lines ranging from 14 to 80 nm, which are not observed in the Chandra spectrum because of the high interstellar neutral hydrogen column density, show abundant O IV-V, C IV lines, and strong O VI lines. Moreover, the intensities of the lines at 62.973 and 17.216 nm are analyzed to characterize the plasma temperature.
Influences of climate fluctuations on northeastern North America’s burned areas largely outweigh those of European settlement since AD 1850

There is a pressing need for a better understanding of changing forest fire regimes worldwide, especially to separate the relative effects of potential drivers that control burned areas. Here we present a meta-analysis of the impacts of climate fluctuation and Euro-Canadian settlement on burned areas from 1850 to 1990 in a large zone (>100 000 km2) in northern temperate and boreal forests of eastern Canada. Using Cox regression models, we tested for potential statistical relationships between historical burned areas in 12 large landscapes (reconstructed with dendrochronological data) with climate reconstructions, changes in the Euro-Canadian population, and active suppression (all reconstructed at the decadal scale). Our results revealed a dominant impact of climate fluctuations on forest burned areas, with the driest decades showing fire hazards between 5 to 15 times higher than the average decades. Comparatively, the Euro-Canadian settlement had a much weaker effect, having increased burned areas significantly only during less fire-prone climate conditions. During periods of fire-prone climate, burned areas were maximum independent of fluctuations in Euro-Canadian populations. Moreover, the development of active fire suppression did not appear to reduce burned areas. These results suggest that a potential increase in climate moisture deficit and drought may trigger unprecedented burned areas and extreme fire events no matter the effects of anthropogenic ignition or suppression.
Coordinating Project Complexities in Inter-Organizational Railway Projects – An Operationalization of the Complexity-Response Framework (Part I)

Large-scale inter-organizational transportation projects play a critical role in the design and development of existing and new railway networks. However, in the past, inter-organizational projects have shown shortcomings in effective decision-making and system integration due to an unilateral use of coordination mechanisms. The goal of this work is to provide an operationalization of the complexity-response framework for the Dutch railway project context, thereby extending the coordination mechanisms currently considered. To that end, we conducted design science research to operationalize the complexity-response framework based on an analysis of the specific inter-organization railway context, and evaluate its validity by means of follow-up discussions with project members. The operationalization of the framework can be used to capture and evaluate the coordination mechanisms employed, and identify potential matching coordination responses to the assessed railway system project complexities at the outset of the project. Further research is needed to assess the fit between the coordination responses applied and those proposed.
An Empirical Analysis of the Determinants that Can Boost Next Generation EU'S Effectiveness

The use of Next Generation EU can become one of the main determinants of Spanish economic developments in the coming years. This article analyses the economic impact of the European Regional Development Fund over the last 20 years, on account of the similarity between its goals and those of Next Generation EU and the available information. The findings suggest that those structural reforms that reduce barriers to competition in the product market and some labour market rigidities can scale up the European funds’ expansionary effect (fiscal multiplier) in the medium and long term.
The Effects of Transit Systems on International Trade

In this paper, we estimate the trade effects of a transit system upgrading that streamlines border processing in developing countries. Our empirical approach combines transaction level export data from El Salvador with unique data that distinguishes export flows that were processed on the transit system. Our results indicate that the new transit system lowered regulatory border costs and raised exports. At the low end, our back-of-the-envelope estimate of the return to investment is US$ 3-to-1. This evidence informs a policy covered by the 2013 WTO Agreement of Trade Facilitation.
Pairs-trading under path-dependent cointegration

Continuous-time pairs-trading rules are often developed based on the diffusion limit of first-order autoregressive cointegration models. Empirical identification of cointegration effects is generally made according to discrete-time error correction representation of vector autoregressive (VAR($p$)) processes. We show that the diffusion limit of a VAR($p$) process appears as a stochastic delayed differential equation. Motivated by this, we investigate the dynamic portfolio problem under a class of path-dependent models embracing path-dependent cointegration models as special case. Under certain regular conditions, we prove the existence of the optimal strategy and show that it is related to a system of Riccati partial differential equations. The proof is developed by means of functional It\^{o}'s calculus. When the process satisfies cointegration conditions, our results lead to the optimal dynamic pairs-trading rule. Our numerical study shows that the path-dependent effect has significantly impact on the pairs-trading strategy.
A Novel Filter Architecture With Five Reconfigurable Filtering Functions

In this paper, a reconfigurable filter architecture that is capable of achieving five reconfigurable filtering functions is presented. The proposed architecture simply consists of a frequency tunable low-pass filter (LPF), a frequency tunable high-pass filter (HPF), a transmission line, and four Pin diodes. By setting different on- and off-states of Pin diodes and manipulating the passband cut-off frequencies of the LPF and HPF, more than five reconfigurable filtering functions including reconfigurable bandpass filter (BPF), bandstop filter (BSF), LPF, HPF, and all-stop filter (ASF) can be obtained. To demonstrate the proposed architecture, a filter prototype using microstrip line technology is designed, fabricated, and measured. The measured results show that the designed multifunctional reconfigurable filter not only successfully achieves various filtering functions, but also demonstrates good reconfigurable performance including fully center frequency (CF) and bandwidth (BW) tunability.
COVID-19 Pandemic: Effect on Confidence Levels of Portuguese Towards People of Different Professions

Background The COVID-19 pandemic is emerging in a world where science is highly developed. Nevertheless, science is not the only resource that people resort to when they have difficulties. In this pandemic context, some professions became more relevant, including front-line professionals, such as medical doctors and nurses, and those who may have an indirect role. The aim of this study is to understand whether there is a strengthening of people’s confidence, in politicians, journalists, science-based activities, and in more mystical dimensions. Methods A cross-sectional study was carried out to understand the levels of confidence of the Portuguese population in several professional groups, measured in two pandemic moments. Participants were recruited to participate in the study through online platforms. The sample was randomly collected from the Portuguese population. The sample was composed of 1455 Portuguese people with a mean age of 44 years, and 1080 were female. Results We found high levels of confidence in medical doctors and nurses, as well as in other health professions, science, and education. We detected the opposite trend for politicians and journalists. Measured in two pandemic moments, we found confidence levels in these professionals were lower in September than in July with statistical significance differences [(politicians (t = 3.15, p = 0.00); journalists (t = 2.49, p = 0.01)]. Conclusion It is important to improve a joint action between politicians, journalists, health and science professionals to communicate measures to increase confidence from people. There is a need for the engagement of the population in the adoption of protective measures and contribute to easier control in pandemic situations.
Intelligent Solutions in Chest Abnormality Detection Based on YOLOv5 and ResNet50

Computer-aided diagnosis (CAD) has nearly fifty years of history and has assisted many clinicians in the diagnosis. With the development of technology, recently, researches use the deep learning method to get high accuracy results in the CAD system. With CAD, the computer output can be used as a second choice for radiologists and contribute to doctors doing the final right decisions. Chest abnormality detection is a classic detection and classification problem; researchers need to classify common thoracic lung diseases and localize critical findings. For the detection problem, there are two deep learning methods: one-stage method and two-stage method. In our paper, we introduce and analyze some representative model, such as RCNN, SSD, and YOLO series. In order to better solve the problem of chest abnormality detection, we proposed a new model based on YOLOv5 and ResNet50. YOLOv5 is the latest YOLO series, which is more flexible than the one-stage detection algorithms before. The function of YOLOv5 in our paper is to localize the abnormality region. On the other hand, we use ResNet, avoiding gradient explosion problems in deep learning for classification. And we filter the result we got from YOLOv5 and ResNet. If ResNet recognizes that the image is not abnormal, the YOLOv5 detection result is discarded. The dataset is collected via VinBigData's web-based platform, VinLab. We train our model on the dataset using Pytorch frame and use the mAP, precision, and F1-score as the metrics to evaluate our model's performance. In the progress of experiments, our method achieves superior performance over the other classical approaches on the same dataset. The experiments show that YOLOv5's mAP is 0.010, 0.020, 0.023 higher than those of YOLOv5, Fast RCNN, and EfficientDet. In addition, in the dimension of precision, our model also performs better than other models. The precision of our model is 0.512, which is 0.018, 0.027, 0.033 higher than YOLOv5, Fast RCNN, and EfficientDet.
Investigating Binge-Watching Adverse Mental Health Outcomes During Covid-19 Pandemic: Moderating Role of Screen Time for Web Series Using Online Streaming

Background and Purpose Watching multiple episodes using streaming services, such as Netflix, Hulu, and Youku, has become widespread in recent years. While much attention has been paid to binge-watching, there is, however, a dearth of research on binge-watching and its adverse psychological effects during the COVID-19 pandemic. To the best of our knowledge, less attention has been paid to understanding the multiple influences of binge-watching on binge-watchers during the COVID-19 pandemic. Most of the past studies on this topic mainly underscored the individual’s motivations for binge-watching. Also, past studies were limited and inconclusive as they mostly espoused only the underpinning adverse effects of binge-watching without looking into the association between binge-watching and screen time for web series through online streaming services during the COVID-19 pandemic. Therefore, this study sought to fill this gap by probing the association between binge-watching and psychological aftereffects. Participants and Methods The study employed a cross-sectional research design vis-à-vis the survey method. A sample of 1089 adult respondents was collected through an online administrated questionnaire. Results The findings of this study demonstrated that extensive binge-watching is an antecedent of stress, loneliness, insomnia, depression and anxiety. Furthermore, it was found that screen time on binge-watching could intensify these adverse effects of binge-watching. Interestingly, the moderating effect of screen time on binge-watching was found to be insignificant for stress and loneliness. Conclusion The findings of this study suggest that binge-watching correlates with psychological and mental health symptoms including stress, loneliness, insomnia, depression and anxiety. Hence, this study suggests that consumption of web series through online streaming services related literacy interventions are imperative to help the audience become critical about online streaming content and its comparison to the real social world.