Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of Problem-Based Learning Combined with Computer Simulation on Students’ Problem-Solving and Creative Thinking Skills

This study is aimed to investigate the effectiveness of problem-based learning combined with simulation on students’ problem-solving and creative thinking skills. By employing a quasi-experimental design, this study used essay and problem-based tests as the instruments to evaluate problem-solving and creative thinking skills of 192 students. These students were categorized into three groups: experimental group I (n = 68) receiving instruction using problem-based learning combined with simulation, experimental group II (n = 60) receiving instruction with problem-based learning only, and control group (n = 64) receiving instruction with a conventional method. Using a multivariate analysis of covariance, the results revealed that problem-solving and creative thinking skills taught by problem-based learning combined with simulation were significantly improved as compared to those in experimental group II and control group. In addition, a positive relationship was identified between students’ problem-solving skills and their creative thinking skills. Ultimately, this study shows that instruction using problem-based learning combined with simulation method is much more effective than using either problem-based learning only or a conventional teaching method.
Authentication of Panax ginseng from different regions

Background: Panax ginseng is a type of traditional medicine. Fresh ginseng is one of the most important ingredients used in the medical industry. Fresh ginseng from different regions has different quality and significantly different prices; consequently, widespread adulteration occurs in the commercial market. However, little scientific guidance for determining the origin of fresh ginseng from different regions is available. We proposed a new strategy for identifying fresh ginseng from different regions. Methods: we investigated the content of ginsenoside, and the activity and gene expression of seven key enzymes involved in ginsenoside biosynthesis. HPLC was used to determine the content of ginsenosides. Gene expression was studied using qRT-PCR. HPLC, GC-MS, LC-MS, enzyme-linked immunosorbent assayand colorimetry were used to measure the activities of key enzymes. Results: the gene expression of the key enzymes 3-hydroxy-3-methylglutaryl CoA reductase (HMGR) and dammarenediol synthase (DS) was consistent with the saponin content of fresh ginseng from different regions. The correlation of gene expressions of HMGR and DS, and the content of the ginsenoside Re with total ginsenoside content, was significant. Conclusion: HMGR and DS gene expression and the content of the ginsenoside Re are important for the authentication of ginseng from different regions. Our research provides an important reference for further studies on the regulatory mechanism of the biosynthetic pathway of ginsenosides.
The effect of biofloc and clear water at low and high salinity concentration on growth performance and antioxidant response of wild juveniles of Atlantic white shrimp Penaeus setiferus

The effect of biofloc (BFT) and clear water (CW) at low (ls) and high-water salinity (hs) in wild juveniles of Penaeus setiferus were evaluated. Four treatments were implemented: hsBFT, lsBFT, hsCW, and lsCW. After 45 days, final weight (FW), weight gain (WG), hepatosomatic index (HSI), and survival rate (SR) were evaluated. Antioxidant activity in muscle and hepatopancreas were measured: superoxide dismutase (SOD), catalase (CAT), glutathione-S transferase (GST), lipid peroxidation (LPO), protein oxidation (PO). The FW and SR was low for lsCW (P < 0.05), whereas the WG and HSI was high in hsBFT and lsBFT (P < 0.05). The integrative biomarker response index (IBR) showed differences between muscle (M) and hepatopancreas (HP). Results showed an increase of SOD and CAT measured from HP for lsBFT treatment. For M, CAT and GST were high only in BFT (regardless of the water salinity). LPO determined from M and HP recorded the high values at hs and ls, respectively. The PO determined in HP showed substantial damage in BFT (regardless of the salinity), whereas the same determination from M was only important for lsCW treatment. When the analyses of variance (ANOVA) were performed, SOD, LPO, and PO were significant in response to salinity (P < 0.05). In contrast, for CAT, the higher activity was due to the rearing system and salinity interaction (P < 0.05). Results suggest that BFT could diminish the stress by stimulating the antioxidant system to maintain the redox balance through a higher enzyme activity and decrease damage in the proteins and lipids of the cells.
Online Dynamic Tip-Over Analysis for a Wheeled Mobile Dual-Arm Robot with an Improved Tip-Over Moment Stability Criterion

Tip-over stability analysis is critical for the success of mobile manipulation of the dual arm, especially in the cases that the dual arm or the mobile platform moves rapidly. Due to strong dynamics coupling between the dual arm and mobile platform, online evaluation of dynamic stability of the mobile dual-arm robot still remains challenging. This paper presents an improved tip-over moment stability criterion dealing with the dual arm and mobile platform interaction and proposes an algorithm for calculating the tip-over stability margin of the arm end in the workspace to analyze the dynamic stability of the wheeled mobile dual-arm robot. The simulations on a four-wheeled mobile dual-arm robot validate the correctness and feasibility of the proposed method.
Android Mobile Malware Detection Using Machine Learning: A Systematic Review

With the increasing use of mobile devices, malware attacks are rising, especially on Android phones, which account for 72.2% of the total market share. Hackers try to attack smartphones with various methods such as credential theft, surveillance, and malicious advertising. Among numerous countermeasures, machine learning (ML)-based methods have proven to be an effective means of detecting these attacks, as they are able to derive a classifier from a set of training examples, thus eliminating the need for an explicit definition of the signatures when developing malware detectors. This paper provides a systematic review of ML-based Android malware detection techniques. It critically evaluates 106 carefully selected articles and highlights their strengths and weaknesses as well as potential improvements. Finally, the ML-based methods for detecting source code vulnerabilities are discussed, because it might be more difficult to add security after the app is deployed. Therefore, this paper aims to enable researchers to acquire in-depth knowledge in the field and to identify potential future research and development directions.
Assessment of the Troposphere Products Derived From VMF Data Server With ERA5 and IGS Data Over China

The accurate modeling of zenith troposphere delay (ZTD) is significant for data processing of radio‐space‐geodetic techniques such as GNSS. The delay can be estimated by classic tropospheric models, which need the surface meteorological parameters. Considering the difficulty of obtaining meteorological data caused by various environment factors and the modeling errors in the models themselves, the above methods are often difficult to provide accurate products for GNSS data processing. Based on continuously updated NWP data from the European Centre for Medium‐Range Weather Forecasts (ECMWF), the Vienna Mapping Functions (VMF) data server provides a widely used data‐source for achieving ZTD with two types of models, that is, the discrete (VFM3) and empirical model (GPT3). Little or no accuracy comparison of these two models with different horizontal resolutions in GNSS community has been conducted over China. This study investigates the performance of the models in terms of calculation of ZHD, ZWD and ZTD, using the hourly values derived from the ERA5 and IGS data as references. The results show that the discrete model outperforms the empirical model and the increasing of horizontal resolution can improve the accuracy of the models. The performance of the empirical model in ZHD/ZWD calculation shows obvious influences of latitude changes and land‐sea differences, while the discrete model improves this phenomenon. The empirical distribution function and boxplot well indicate the accuracy differences of the two models in different seasons. We also found that the diurnal variation can only be detected in the ZHD calculation by the discrete model. The ZTD comparison gives the details of the two types of models at GNSS stations.
Business innovations and their key factors: public funding, human capital, and their relationships with the industrial environment

Considering that innovation plays a relevant role in the current business environment, this article investigates the effect of public funding invested in science, technology, and innovation on obtaining innovative results in industrial companies in Colombia. To achieve this purpose, we proposed three hypotheses; the first one is oriented to know if the probability of obtaining innovative results increase when companies receive Public funding for research and development activities, the second one verifies if the probability of obtaining innovative results depends on the qualifications of the human capital. The third one checks out if the probability of obtaining innovative results increases when companies have relationships with their environment institutions. The data from 1989 industrial companies was obtained from the VII Technological Development and Innovation Survey and was analyzed using a logistic regression model that seeks to predict the outcome of a categorical variable from independent variables. The results respond to the hypotheses put forth, indicating positive and significant effects of public aid for R&D in obtaining innovative results and a moderating effect of the qualification of human capital and companies' ability to interact with the different actors within their environment.
Thermal analysis of a moving fin using the radial basis function approximation

In this study, the heat transfer and temperature distribution in a moving fin have been analyzed. The fin velocity was considered constant, and the thermal conductivity coefficient was variable with temperature, and the fin was under the effect of convection, radiation, and conduction heat transfer. The main equation of the problem was solved by the radial basis function method and validated by the numerical 4th‐order Runge–Kutta method. Several parameters such as thermal conductivity parameter from 0 to 1, sink temperature parameter from 0.2 to 0.8, and Nr, Nc, Pe number from 1 to 4, were examined. The outcomes illustrate that increasing the thermal conductivity by 51.5% raises the conduction heat transfers as well as the dimensionless temperature by 3.42%. Moreover, increasing the sink temperature leads to a slow rise in ambient temperature by 22.8% in the maximum state. By raising the Nc and Nr parameters, near 33.3%, the temperature distribution profile is declined by 4% and 10.5%, respectively. And increasing the Pe number by 100% results in a rise in the temperature distribution by about 7%.
FTIR spectroscopy in biomedical research: how to get the most out of its potential

Abstract Fourier Transform Infrared (FTIR) Spectroscopy, in particular ATR-FTIR, is a widely used technique that allows, in a very short time, to screen biological samples and to identify its specific spectral signature, being an important tool for clinical diagnosis and biomarker discovery. FTIR spectroscopy is used to screen cells, tissues and biofluids and is already implemented in biomedicine, mainly in pre-clinical setting. Although the experimental procedure is easy to implement, sample preparation, definition of spectra acquisition parameters and spectral analysis are crucial steps to obtain reliable and reproducible results. However, the selection of experimental conditions for spectral analysis can be a difficult task for researchers because the information is dispersed and often the choice is made in an empirical and inaccurate way. This review gathers and summarizes studies using FTIR in pre-clinical and clinical setting and aims to systematize information and propose some guidelines for FTIR spectroscopy studies of biological samples. This will help new users to prepare samples for FTIR analysis and understand the critical steps to correctly perform spectra pretreatment, preprocessing and statistical analysis and to implement appropriate and evidence-based experimental designs.
Monetary Policy and Personal Income Distribution: A Survey of the Empirical Literature

ABSTRACT The purpose of this paper is to conduct a survey of the recent literature that evaluates, in an empirical way, the distributional impacts of monetary policy. In the first two sessions, we discuss, respectively, the transmission channels of monetary policy to income distribution and the empirical strategies used to measure it. The majority of surveyed papers find that a contractionary monetary policy worsen the income distribution, and that an expansionist policy tends to improve it. Moreover, several papers found that the higher is the redistributive impact of fiscal policy, the lower is the impact of monetary policy on inequality. Another outcome with empirical support is the role of the labor share on total income: the higher is this share, the higher is the impact of monetary policy on inequality. The last point discussed is the asymmetric effects of contractionary and expansionary monetary policy. There is evidence that increases in interest rates have statistically significant effects on income distribution, whereas the effects of reductions in interest rates are not statistically different from zero. This empirical finding goes against the conventional view that the distributional effects of interest rate changes are temporary and likely to net out over the business cycle.
Long-Term Trends of Sea Surface Wind in the Northern South China Sea under the Background of Climate Change

The long-term trends of sea surface wind are of great importance to our understanding of the effects of climate change on the marine environment. In the northern South China Sea (SCS), the long-term changes in coastal sea surface wind are not well-understood. Based on the latest reanalysis (ERA5) data from 1979 to 2019, our analysis showed a decreasing trend in the annual mean wind speed in the coastal area and an increasing trend in the open sea. There was a significant weakening trend in the easterly wind component in the coastal and continental shelf areas, whereas there was an increasing trend in the northerly wind component in the open sea. The Mann–Kendall mutation analysis suggested that there were significant changes in the wind speed and frequency of strong wind. Significant correlations were found between the variation of the wind field and El Niño–Southern Oscillation by wave coherence analysis. The strengthening of the wind stress curl was an important factor for the enhancement of coastal upwelling along the coast of the northern SCS. The wind field plays an important role in modulating the climatic change of significant wave height.
Determination of Cadmium, Copper, Lead, and Zinc in Pilchard Sardines from the Bay of Boumerdés by Atomic Absorption Spectrometry

ABSTRACT Fish are an important human food with increasing consumption in recent decades. Diet is the main route of exposure to heavy metals for human health. For this reason, many studies have been performed on the pollution by heavy metals in different species of fish. Our main objective was to evaluate the pollution by trace metals (Zn, Cu, Pb, and Cd) in sardine muscles collected from the bay of Boumerdés (Algeria). Flame atomic absorption spectroscopy (AAS) was used for the quantification of Cu and Zn. The quantification of Cd and Pb was achieved by graphite furnace (GF) AAS. The analysis revealed the presence of metal trace elements in the muscles of species at concentrations below the thresholds established by national and international regulations.
Large‐Scale Precipitation Systems: Essential Elements of the Madden‐Julian Oscillation

Possible roles of large‐scale precipitation on model simulations of the Madden‐Julian Oscillation (MJO) were investigated using the Large‐scale Precipitation Tracking (LPT) method. Individual LPT systems and eastward propagating MJO LPT systems were identified in both observations and 25 general circulation model (GCM) simulations. LPT systems show dominant eastward propagation over the Indian Ocean in the observation, whereas LPT systems are too stationary in GCM simulations. The MJO statistical signals in the model simulations are represented by the occurence frequencies of LPT systems with a size of ∼4–9 × 106 km2 (∼20–30° in longitude and latitude) and a strength of ∼15–18 mm d−1. Growth rate in size of LPT systems in early stage determines the size of LPT systems, which differentiates the MJO statistical signals among the GCM simulations. Comprehensive diagnostics of MJO simulations in GCMs should include both individual LPT systems as essential elements and the MJO statistical signals.
Characteristics of turbulence over the semi‐fixed desert area north of Xinjiang, China

As the largest fixed and semi‐fixed desert in China, the Gurbantünggüt Desert undergoes a long period of snow cover in the winter and the rapid growth of ephemeral plants in the spring, presenting obvious seasonal changes in the underlying desert surface type, which can lead to variation in the turbulence of the near‐surface boundary layer turbulence over the desert. In this study, gradient tower data and eddy covariance data from 2017 were analysed to investigate the turbulence characteristics of the different surface boundary layers in the hinterland of the Gurbantünggüt Desert. The results indicate that stable atmospheric conditions in the desert occur exclusively during the early morning and at night in the desert, and the onset and duration of this stable state varies seasonally. Two regimes of intermittent turbulence occur during the night, a weak turbulent regime that occurs when the wind speed is less than the threshold and a strong turbulent regime when the wind speed exceeds the threshold, and different wind speed thresholds were observed at each level. These parameters follow a seasonal pattern of summer (July) > spring (April) > autumn (October) > winter (January) in terms of magnitude. The mean turbulence intensities of the along‐wind, cross‐wind and vertical wind are 0.5, 0.47 and 0.14, respectively, with Iu > Iv > Iw. The normalized standard deviation of the wind velocity components (σu, σv and σw) generally satisfies a 1/3 power‐law relation. Our results show that the night‐time turbulence regime classification for the Gurbantünggüt Desert strongly depends on meteorological and orographic features, and the intermittent turbulent events have the non‐stationarity of the flow in common. The results can contribute to the study of land surface processes, climate change and desertification in inland arid desert areas.
An Autonomous Wall Climbing Robot for Inspection of Reinforced Concrete Structures: SIRCAUR

A wall climbing inspection robot has been designed to climb on safety critical concrete structures by adhering to reinforcement steel bars (rebars) using permanent magnets to generate the adhesion forces. Simulation and experimental validation has been performed to determine the optimum flux focusing magnet configurations with the robot operating on 30 to 35mm of concrete cover over rebars arranged in different patterns. The goal of adhesion force optimization is to be able to carry a ground penetrating radar (GPR) sensor which detects rebar corrosion, concrete delamination and concrete cover deterioration. The autonomous robot uses an ultra-wide band (UWB) localisation system and GPR data to control its motion trajectories to avoid regions where there is insufficient density of rebars. Non-destructive testing (NDT) inspection data acquired by GPR is transmitted wirelessly to a ground station for processing and monitoring by NDT technicians.
OM Forum - Pandemics/Epidemics: Challenges and Opportunities for Operations Management Research

We reviewed research papers related to pandemics/epidemics (disease outbreaks of a global/regional scope) published in major operations management, operations research, and management science journals through the end of 2019. We evaluate and categorize these papers. We study research trends, explore research gaps, and provide directions for more efficient and effective research in the future. In addition, our recommendations include the lessons learned from the ongoing pandemic, COVID-19. We discuss papers in the following categories: (a) warning signals/surveillance, (b) disease propagation leading to pandemic conditions, (c) mitigation, (d) vaccines and therapeutics development, (e) resource management, (f) supply chain configuration, (g) decision support systems for managing pandemics/epidemics, and (h) risk assessment.
Eugenol-Derived Biobased Epoxy: Shape Memory, Repairing, and Recyclability

Conventional epoxy polymers are constructed by petro-based resources that are toxic and nonrenewable, and their permanent cross-links make them difficult to be reprocessed, reshaped, and recycled. In this study, a unique eugenol-derived epoxy (Eu-EP) is synthesized, and then vitrimeric materials are prepared by reacting Eu-EP with succinic anhydride (SA) at various ratios (1:0.5, 1:0.75, and 1:1) in the presence of zinc-containing catalysts. All vitrimers exhibit excellent shape changing, crack healing, and shape memory properties. Although vitrimers with 1:0.75 and 1:1 ratios cannot be physically reprocessed, they can be well reprocessed by the chemical method of being simply decomposed in a benign ethanol solution without loading additional catalyst. The collected decomposed polymers can form vitrimers again after exposure at 190 °C for 3 h. This work combines the concepts of vitrimer preparation, chemical recycling, and biobased polymer together, which would bring a feasible way to satisfy the demands .
Why customers have the intention to reuse food delivery apps: evidence from China

PurposeFood delivery apps (FDA) have been widely adopted by customers in online-to-offline (O2O) catering businesses. This study aims to explore the mechanism regarding the stickiness of FDA and indicates why customers have the intention to reuse them.Design/methodology/approachA research model was developed based on the e-commerce system successful model (ECSS model) and social influence theory. Using the data collected from 312 customers who have FDA usage experience via an online survey, the established model was empirically assessed by partial least squares based structural equation model.FindingsThe results show that factors including information quality, ease of use, convenience and various choices perceived by FDA users are significant antecedents of customer satisfaction and perceived value, which in turn positively influence customers' intention to reuse. Besides, informational social influence and normative social influence play important roles in directly or indirectly affecting customers' intention to reuse.Originality/valueThis study extends the e-commerce system success model and enriches the literature regarding stickiness of FDA. Besides, the understanding of social influence in FDA usage has been deepened by addressing its role in the ECSS model based on the features and contexts of such apps.