Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovery of Biophenols from Olive Vegetation Waters by Carbon Nanotubes

In this work, the possibility of using carbon nanotubes for the treatment of olive vegetation waters (OVWs) was investigated. In general, the disposal of OVWs represents an important environmental problem. The possibility of considering these waters no longer just as a problem but as a source of noble substances, thanks to the recovery of biophenols from them, was tested. In particular, predetermined quantities of olive vegetation waters were treated with carbon nanotubes. The quantities of adsorbed biophenols were studied as a function of the quantities of carbon nanotubes used and the contact time. The experimental conditions for obtaining both the highest possible quantities of biophenol and a purer adsorbate with the highest percentage of biophenols were studied. After the adsorption tests, the vegetation waters were analyzed by UV spectrophotometry to determine, in particular, the variation in the concentration of biophenols. The carbon nanotubes were weighed before and after each adsorption test. In addition, kinetic studies of the adsorption processes were considered. Carbon nanotubes proved their effectiveness in recovering biophenols.
Deep hybrid architectures for diabetic retinopathy classification

ABSTRACT Diabetic retinopathy (DR) is the most severe ocular complication of diabetes. It leads to serious eye complications such as vision impairment and blindness. A computer-aided diagnosis may help in the early detection of this disease, which increases the chances of treating it efficiently. This paper carried out an empirical evaluation of the performances of 28 deep hybrid architectures for an automatic binary classification of the referable diabetic retinopathy, and compared them to seven end-to-end deep learning (DL) architectures. For the hybrid architectures, we combined seven DL techniques for feature extraction (DenseNet201, VGG16, VGG19, MobileNet_V2, Inception_V3, Inception_ResNet_V2 and ResNet50) and four classifiers (SVM, MLP, DT and KNN). For the end-to-end DL architectures, we used the same techniques used for the feature extraction in the hybrid architectures. The architectures were compared in terms of accuracy, sensitivity, precision and F1-score using the Scott Knott test and the Borda count voting method. All the empirical evaluations were over three datasets: APTOS, Kaggle DR and Messidor-2, using a k-fold cross validation method. The results showed the potential of combining deep learning techniques for feature extraction and classical machine learning techniques to classify referable diabetic retinopathy. The hybrid architecture using the SVM classifier and MobileNet_V2 for feature extraction was the top performing architecture and it was classified with the best performing end-to-end architectures in the best clusters of APTOS, Kaggle DR and Messidor-2 datasets with an accuracy equal to 88.80%, 84.01% and 84.05% respectively. Note that the two end-to-end architectures DenseNet201 and MobileNet_V2 outperformed all the hybrid architectures over the three datasets. However, we recommend the use of the hybrid architecture designed with SVM and MobileNet_V2 since it is promising and less time consuming, and requires less parameter tuning compared to the end-to-end techniques.
A New RIS Architecture With a Single Power Amplifier: Energy Efficiency and Error Performance Analysis

Reconfigurable intelligent surface (RIS)-assisted communication have recently attracted the attention of the wireless communication community as a potential candidate for the next 6-th generation (6G) of wireless networks. Various studies have been carried out on the RIS technology, which is capable of enabling the control of the signal propagation environment by network operators. However, when an RIS is used in its inherently passive structure, it appears to be only a supportive technology for communications, while suffering from a multiplicative path loss. Therefore, researchers have lately begun to focus on RIS hardware designs with minimal active elements to further boost the benefits of this technology. In this paper, we present a simple RIS hardware architecture including a single and variable gain amplifier for reflection amplification to confront the multiplicative path loss. The end-to-end signal model for communication systems assisted with the proposed amplifying RIS design is presented, together with an analysis focusing on the capacity maximization and theoretical bit error probability performance, which is corroborated by computer simulations. In addition, the major advantages of the proposed amplifying RIS design compared to its passive counterpart are discussed. It is shown that the proposed RIS-based wireless system significantly eliminates the double fading problem appearing in conventional passive RIS-assisted systems and improves the communication energy efficiency.
In vitro Antimicrobial Activity and the Mechanism of Berberine Against Methicillin-Resistant Staphylococcus aureus Isolated from Bloodstream Infection Patients

Purpose To investigate the antimicrobial activity of berberine and the mechanism by which it combats methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from patients with bloodstream infections. Methods Fifteen clinical MRSA isolates were collected, and their Multi-locus Sequence Types (MLST) were examined. The minimum inhibitory concentration (MIC) and combined antibacterial activity of berberine alone, and when combined with clindamycin and rifampicin separately, were determined. Additionally, two MRSA strains (ST239 and ST5) were selected to perform the time-killing assay and biofilm formation test. Cell wall alterations and cell membrane integrity were measured by confocal laser scanning microscopy (CLSM) and electron microscopy to assess the influence on cell morphology. Results Our data showed berberine was effective against MRSA at MIC values varying from 256 to 64 mg*L−1 for different MLST types. Berberine alone, and when combined with clindamycin and rifampicin separately, displayed excellent antibacterial activity which reduced the bacterial counts by 2lgCFU*mL within 24h and significantly weakened biofilm formation compared with control strain. Additionally, bacterial cytological profiling indicates that berberine destroyed the structure of the cell walls, membrane integrity and further changed the cell morphology with concentration increased. Conclusion In our study, berberine has excellent anti-MRSA activities and has synergistic antibacterial property when combined with clindamycin and rifamycin separately, and the mechanism of activities involves the destruction of cell wall and membrane.
Reliability of Educational Content Videos in YouTubeTM about Stainless Steel Crowns

The purpose of the present study is to evaluate the quality and educational information provided on YouTubeTM about stainless steel crowns (SSC). Videos were searched for on YouTube TM using keywords related to stainless steel crowns in pediatric dentistry in the Google Trends application. A total of 52 videos were available. After exclusion criteria application, 22 videos were selected for the study for analysis. To classify the video content as high or low quality, a scoring system formed of seven parameters was used. For a global evaluation of the video quality, the video information and quality index were applied. Data obtained were analyzed statistically. Only a few videos explained the importance of SSCs. Most of the videos uploaded with a high number of likes were of low quality. Very few videos were of high quality. The content quality and educational quality of videos is poor and incomplete. None of the videos explained the need for the SSC and its benefits in pediatric dentistry.
Incorporating student mobility in studying academic growth in math: comparing several alternative multilevel formulations

ABSTRACT Increasing pupil mobility has led to widespread concern among parents, educators, and policymakers regarding its negative effects on academic performance. An important issue in examining mobility effects in longitudinal school achievement comparisons is providing accurate estimates. The presence of pupil mobility suggests that we should model pupils as belonging to the series of schools attended and not just their first or final school. We discuss several challenges in accounting for student mobility and, because of the presence of mobile pupils, how to represent the contribution of multiple schools attended on estimating academic growth properly. We then contrast several previous longitudinal multilevel models utilized with two cross-classified multiple membership (CCMM) models, which have been proposed to cumulate annual school effects on pupils’ academic growth better given the complexity of the multilevel data structure. We discuss our results in terms of their theoretical and practical implications for research on school academic improvement.
Multistage Adaptive Noise Cancellation Scheme for Heart Rate Estimation From PPG Signal Utilizing Mode Based Decomposition of Acceleration Data

Photoplethysmography (PPG) has recently become a popular method for heart rate estimation due to its simple acquisition technique. However, the main challenge in determining the heart rate from the PPG signals is its high vulnerability to motion artifacts (MA). In this paper, a new scheme is proposed for heart rate estimation through frame selective multistage adaptive noise cancellation (MANC). The frame selective approach determines the specific frames of PPG signal which are significantly interfered with MA, and the MA removal operation is only employed over those specific frames. The MANC scheme is implemented through the Least Mean Square (LMS) algorithm in which instead of the conventional approach of using accelerometer data directly, we propose to utilize mode-based decomposed 3-channel accelerometer data as reference signals independently in a sequential manner. The use of decomposed modes offers high degrees of controllability in the ANC scheme depending on the overlap between the spectra corresponding to MA and heart rate, thereby offers effective denoising. A peak searching algorithm is employed to estimate heart rate-related peaks from the resulting noise-reduced PPG signal. The novelty of the proposed scheme lies in the use of decomposed reference inputs to the MANC algorithm (named as DERMANC scheme) which is accomplished through both empirical mode decomposition (EMD) and variational mode decomposition (VMD). Performance of the proposed EMD and VMD based schemes (E-DERMANC and V-DERMANC) has been tested on a publicly available dataset and very satisfactory results are obtained in terms of estimation accuracy and computational time (0.95 and 1.10 BPM, respectively on 12 recordings) that makes the schemes worthy to be implemented in wearable devices.
Spreading rates of bacterial colonies depend on substrate stiffness and permeability

Abstract The ability of bacteria to colonize and grow on different surfaces is an essential process for biofilm development. Here, we report the use of synthetic hydrogels with tunable stiffness and porosity to assess physical effects of the substrate on biofilm development. Using time-lapse microscopy to track the growth of expanding Serratia marcescens colonies, we find that biofilm colony growth can increase with increasing substrate stiffness, unlike what is found on traditional agar substrates. Using traction force microscopy-based techniques, we find that biofilms exert transient stresses correlated over length scales much larger than a single bacterium, and that the magnitude of these forces also increases with increasing substrate stiffness. Our results are consistent with a model of biofilm development in which the interplay between osmotic pressure arising from the biofilm and the poroelastic response of the underlying substrate controls biofilm growth and morphology.
Learning with digital technology-facilitated empathy: an augmented reality approach to enhancing students’ flow experience, motivation, and achievement in a biology program

ABSTRACT Biology involves the understanding of life concepts and the exploration of life processes. Due to the complexity of life, the learning content of biology is often microscopic, abstract, and complex. In traditional teaching, The non-visualization of abstract concepts, rote memorization of knowledge and low classroom participation tend to make students feel dull and eventually lead to inefficient and low confidence in learning. Augmented reality (AR) superimposes 3D dynamic virtual information into the real world and visualizes abstract concepts to deepen students’ understanding of concepts. In addition, AR supports virtual-real interaction and instant feedback, which helps to stimulate learning interest and reinforce the learning effect. Therefore, the application of AR can solve the problems of traditional biology teaching. This study used a quasi-experimental approach to explore the potential of AR in teaching biology. A total of 81 third grade students were recruited for the study. The experimental group (40 students) was taught with AR, while the control group (41 students) was taught with traditional instruction. The study found that AR instruction significantly increased students’ flow experiences and motivation to learn and reduced their cognitive load. However, there were no significant differences in self-efficacy and academic performance between the two groups.
Analysis of the Autism Spectrum Disorder (ASD) Knowledge of Cuban Teachers in Primary Schools and Preschools

Teachers’ knowledge of autism spectrum disorder (ASD) plays a key role in the successful inclusion of children with ASD in regular schools. The objective of this study was to analyze Cuban teachers’ knowledge of ASD of at inclusive primary schools and preschools and to compare it with the results obtained in previous studies carried out at an international level. To do this, a cross-sectional study was conducted with Cuban teachers from urban and rural areas throughout the country. The sample was selected using a non-probabilistic technique. In total, 131 primary school and preschool teachers participated. Data were collected by applying the Autism Knowledge Questionnaire (AKQ) that measures ASD knowledge. The results indicated that Cuban teachers had an acceptable knowledge regarding ASD (0.57). Primary education teachers (17.58 ± 4.06) showed a higher level of knowledge than preschool teachers (15.35 ± 2.74). Regarding previous training, teachers who claimed to have received some type of specific ASD training (10.88 ± 3.29) made a greater number of errors than teachers who had not received specific training on ASD (8.91 ± 3.06). At the international level, Cuban teachers were observed to have similar knowledge about ASD when compared to active teachers or pre-service teachers from other countries where similar studies have been carried out. The results suggest that the training of Cuban teachers is not yet optimal to educate students with ASD in primary schools and preschools which are open to diversity.
The Early Season Community of Flower-Visiting Arthropods in a High-Altitude Alpine Environment

Simple Summary The knowledge about the flower-visiting arthropods in high-altitude environments is limited, in particular about those occurring on early flowering plants. We characterised the flower visitor community of an early flowering high-altitude Alpine species: Androsace brevis, a vulnerable endemic plant belonging to the Primulaceae family, which grows in the Alps above 2000 m asl and flowers for a very short period immediately after snowmelt. In addition, we tested the effect of temperature, wind speed, and other variables on flower-visiting arthropod activity. We identified dipterans (in particular, anthomyiid flies) and hymenopterans (in particular, ants and parasitoid wasps) as the main flower visitors. Moreover, we assessed that temperature and time (hour of the day) affect the flower visitors’ activity. Our study contributes to defining the composition of high-altitude Alpine flower-visiting arthropod communities and sets the stage for future evaluation of climate change effects on flower-visiting arthropods in high-altitude environments in the early season. Abstract In mountain ecosystems, climate change can cause spatiotemporal shifts, impacting the composition of communities and altering fundamental biotic interactions, such as those involving flower-visiting arthropods. On of the main problems in assessing the effects of climate change on arthropods in these environments is the lack of baseline data. In particular, the arthropod communities on early flowering high-altitude plants are poorly investigated, although the early season is a critical moment for possible mismatches. In this study, we characterised the flower-visiting arthropod community on the early flowering high-altitude Alpine plant, Androsace brevis (Primulaceae). In addition, we tested the effect of abiotic factors (temperature and wind speed) and other variables (time, i.e., hour of the day, and number of flowers per plant) on the occurrence, abundance, and diversity of this community. A. brevis is a vulnerable endemic species growing in the Central Alps above 2000 m asl and flowering for a very short period immediately after snowmelt, thus representing a possible focal plant for arthropods in this particular moment of the season. Diptera and Hymenoptera were the main flower visitors, and three major features of the community emerged: an evident predominance of anthomyiid flies among Diptera, a rare presence of bees, and a relevant share of parasitoid wasps. Temperature and time (hour of the day), but not wind speed and number of flowers per plant, affected the flower visitors’ activity. Our study contributes to (1) defining the composition of high-altitude Alpine flower-visiting arthropod communities in the early season, (2) establishing how these communities are affected by environmental variables, and (3) setting the stage for future evaluation of climate change effects on flower-visiting arthropods in high-altitude environments in the early season.
A Flower-like In2O3 Catalyst Derived via Metal–Organic Frameworks for Photocatalytic Applications

The most pressing concerns in environmental remediation are the design and development of catalysts with benign, low-cost, and efficient photocatalytic activity. The present study effectively generated a flower-like indium oxide (In2O3-MF) catalyst employing a convenient MOF-based solvothermal self-assembly technique. The In2O3-MF photocatalyst exhibits a flower-like structure, according to morphology and structural analysis. The enhanced photocatalytic activity of the In2O3-MF catalyst for 4-nitrophenol (4-NP) and methylene blue (MB) is likely due to its unique 3D structure, which includes a large surface area (486.95 m2 g−1), a wide spectrum response, and the prevention of electron–hole recombination compared to In2O3-MR (indium oxide-micro rod) and In2O3-MD (indium oxide-micro disc). In the presence of NaBH4 and visible light, the catalytic performances of the In2O3-MF, In2O3-MR, and In2O3-MD catalysts for the reduction of 4-NP and MB degradation were investigated. Using In2O3-MF as a catalyst, we were able to achieve a 99.32 percent reduction of 4-NP in 20 min and 99.2 percent degradation of MB in 3 min. Interestingly, the conversion rates of catalytic 4-NP and MB were still larger than 95 and 96 percent after five consecutive cycles of catalytic tests, suggesting that the In2O3-MF catalyst has outstanding catalytic performance and a high reutilization rate.
Explaining party fragmentation at district-level Indonesia

While predominant views within party fragmentation literature suggest the importance of the sociological and institutional hypothesis, the Indonesian case provides a new perspective on the issue at hand. Using district-level elections, this article recognizes the weight of existing perspectives, but posits the need to empirically assess the effect of certain seat apportionment methods in the proportional representation system—a much under-explored argument within the literature. This article shows that Indonesia’s methods for allocating seats, the Hare and Sainte-Laguë methods, have been relatively benign in creating party fragmentation. Yet the latter method has been more favorable for small parties due to its deeper bent toward the disproportionality of votes. Additionally, given that major parties often perform unevenly across district elections, the nature of party competition at local politics has greatly diverged from that of the national arena. This article argues that this diversity has been driven partly by the strong influence of ethnic and geographical dispersion, making it hard for major parties to preside over local politics. Thus the concept of party nationalization hardly exists, and party fragmentation could be the default of the party system at local politics in Indonesia for years to come.
Antecedents of attitudinal loyalty in a telecom service sector: the Nigerian case

Purpose – Although the benefits of customer loyalty are well researched and understood, a clear explication of how customer attitudinal loyalty evolves is lacking. Cultural discrepancies across contexts are also argued as restraining the search for universal and dominant antecedents of loyalty. As a result of the high collectivistic ranking of the Nigerian culture, the purpose of this paper is to explore the antecedents of attitudinal loyalty within the Nigerian telecom market. Design/methodology/approach – This study is based on survey data obtained from 138 informants who are experienced users of telecommunication services in Nigeria. The cross-sectional data were examined for internal consistency using Cronbach α internal consistency measure whereas the proposed hypotheses were tested using a multiple regression technique after conducting series of validation tests to ensure that none of the assumptions of regression was violated. Findings – The results indicate that service reliability and customer co.
Mobile marketing in the 21st century: a partial least squares structural equation modelling approach

Mobile marketing (m-marketing) adoption has not been a preferred selection among consumers although the benefits are tremendous. As the cost of implementing the system can be expensive the study explores on the factors that influence the decision of consumers to adopt m-marketing. Using technology acceptance model (TAM), the framework was extended with social influence (SI), personal innovativeness in information technology (PIIT) and perceived enjoyment (PE). The data was collected from 108 users using self-administered questionnaire and subsequently tested using SmartPLS. Only PIIT is a non-significant construct based on the investigation. The findings bring significant benefits to marketers who wish to integrate m-marketing in their advertising budget. In addition, the study provides unprecedented methods in reaching to mobile consumers.