Miracle-dz/UniFAR-FTUs huggingface dataset:
AI-enabled IoT-Edge Data Analytics for Connected Living

As deep learning, virtual reality, and other technologies become mature, real-time data processing applications running on intelligent terminals are emerging endlessly; meanwhile, edge computing has developed rapidly and has become a popular research direction in the field of distributed computing. Edge computing network is a network computing environment composed of multi-edge computing nodes and data centers. First, the edge computing framework and key technologies are analyzed to improve the performance of real-time data processing applications. In the system scenario where the collaborative deployment tasks of multi-edge nodes and data centers are considered, the stream processing task deployment process is formally described, and an efficient multi-edge node-computing center collaborative task deployment algorithm is proposed, which solves the problem of copy-free task deployment in the task deployment problem. Furthermore, a heterogeneous edge collaborative storage mechanism with tight coupling of computing and data is proposed, which solves the contradiction between the limited computing and storage capabilities of data and intelligent terminals, thereby improving the performance of data processing applications. Here, a Feasible Solution (FS) algorithm is designed to solve the problem of placing copy-free data processing tasks in the system. The FS algorithm has excellent results once considering the overall coordination. Under light load, the V value is reduced by 73% compared to the Only Data Center-available (ODC) algorithm and 41% compared to the Hash algorithm. Under heavy load, the V value is reduced by 66% compared to the ODC algorithm and 35% compared to the Hash algorithm. The algorithm has achieved good results after considering the overall coordination and cooperation and can more effectively use the bandwidth of edge nodes to transmit and process data stream, so that more tasks can be deployed in edge computing nodes, thereby saving time for data transmission to the data centers. The end-to-end collaborative real-time data processing task scheduling mechanism proposed here can effectively avoid the disadvantages of long waiting times and unable to obtain the required data, which significantly improves the success rate of the task and thus ensures the performance of real-time data processing.
Neodymium doped bismuth telluride alloys using chemical reflux method for thermoelectric application

ABSTRACT This work reports synthesis of pure and neodymium (Nd) doped bismuth telluride (Bi2Te3) alloys (Bi2-xNdxTe3, x = 0, 0.5), using reflux method. The X-ray powder diffraction for the as-synthesized Bi2Te3 indicates phase purity and crystallographic structure, and agrees well with the prescribed JCPDS data # 000–60601. The Bi2-xNdxTe3 alloys were characterized by pursuing various imaging and spectroscopic techniques including, scanning electron microscope, and UV-Vis absorption spectroscopy. After Nd doping, the micrographs show formation of a new contrast (white phase) with the prominent (201) plane of a hexagonal crystal structure.
IN VITRO ANALYSIS OF TARTRAZINE GENOTOXICITY AND CYTOTOXICITY

Tartrazine (E 102) is widely used yellow food colorant. It is used in nonalcoholic and sports drinks, spicy chips, jams, jelly and chewing gum and also found in many non-food products like soaps, cosmetics, shampoo, vitamins and some drugs. Tartrazine belongs to the most important and diverse group of synthetic dyes – azo dyes. Their use often creates controversies in the public since some of them are toxic, carcinogenic, mutagenic and cause different disorders or allergic reactions. In this study we aimed to evaluate genotoxic potential of tartrazine in human lymphocytes culture and its cytotoxic potential in human lymphocytes and melanoma GR-M cell line. For testing of its genotoxic and cytotoxic potential in human lymphocyte culture, we used chromosome aberration analysis and cytokinesis-block micronucleus cytome assay. For the analysis of its cytotoxic potential in human melanoma cell culture, we applied trypan blue exclusion assay.
The environmental Risk Factors Significant to Anopheles Species Vector Mosquito Profusion, P.falciparum, P.vivax Parasite Development, and Malaria Transmission, Using Remote Sensing and Gis: Review Article

The prevalence of spatial distribution and the seasonal variation of malaria epidemics in India have beenmost significantly determined by the environmental variables including climate, landscape, and the manmade factors. The risk factors are acting as decisive factors on the development of Anopheles genusmosquitoes. The landscape environments (slope, altitude, land use / land covers), human settlementsproximity to permanent water bodies of mosquito breeding habitats (lake, pool, streams, rivers, tanks etc),agricultural wet rice cultivation land, land use dynamics, population density, urbanization, increase of manwater resource projects. The coefficient model of climate determinants (rainfall and temperature) with themosquito abundance are highly associated with the Normalized Difference Vegetation Index (NDVI) valuederived from multispectral satellite data, and is useful in the assess the ground situation of Anophelinemalaria vector mosquito larval abundance 7 days in advance in the wet irrigation rice fields using remotelysensed data. The result of logistic regression model provides the spatial agreement between the observedand predicted values of larval index within buffer zones 2.5 KM around the trap location in the wetcultivation rice fields much appropriate for Anopheline vector mosquito breeding. However, transmissionof Plasmodium vivax requires a minimum average temperature 15.0°C and transmission by Plasmodiumfalciparum, requires a minimum average temperature of 19.0°C. The P.vivax vector requires 15 to 25 daysto complete the parasite development cycle within the temperature range between 15°C to 20°C, the relativehumidity for both species requires range between 55% to 80% and its life cycle may be completed within 6to 10 days, if the temperature range remains within 25°C to 30°C. Multivariate analysis could be predictedaccurately the relative abundance of malaria vectors breeding habitats suitability and epidemics. The malariacases in the endemic districts and the relative abundance of the malaria vectors are directly controlled by theclimate variables with >85 % accuracy.
Multidrug-Resistance and Virulence-Related Properties of Diarrheagenic Escherichia Coli in Urban River: A Possible Source and Dissemination of Human Infections

The presence of multi-drug resistant (MDR) E. coli harboring virulence pathotypes in aquatic systems is a public health concern due to an increase number of cases of infections and outbreaks in industrialized and developing countries. The aim of the present study was to evaluate the microbiological quality of Joana river, located at Rio de Janeiro, by analyzing E. coli bacteria contamination and to investigate virulence properties and MDR profiles by phenotypic and genotypic methods, including bacterial interaction with Caco-2 cells. A total of 34 E. coli were identified by MALDI-TOF and 20 E. coli were characterized as MDR when submitted to antimicrobial susceptibility test. Evaluation by multiplex-PCR of MDR E. coli demonstrated the presence of virulence pathotypes: EHEC (stx1, stx2, eae genes), STEC (stx2 gene) and EIEC/STEC (stx2, iaL genes). Virulence potential was demonstrated by the ability to adhere and survive within Caco-2 cells of MDR E. coli pathotypes (n = 4). In conclusion, this study demonstrates the presence of diarrheagenic MDR E. coli in river water at Rio de Janeiro. The possibility of aquatic environment dissemination of antimicrobial resistance and human contamination leading to community and nosocomial infections due to virulent MDR E. coli water-borne pathogens is a matter of concern.
Promoting the Faith: Examining Megachurches’ Audience-Centric Advertising Strategies on Social Media

Abstract Megachurches have a reputation for savvy use of digital media; however, little is known about their advertising strategy or which strategies elicit engagement. By assessing megachurches’ promotional content on social media, this study draws on the devotional campaign framework to examine audience-centric engagement strategies: God–Congregant, Church–Congregant, and Intra-Congregational. The quantitative content analysis of Facebook and Instagram posts from 15 megachurches in five countries revealed that megachurches used the combination God–Congregant & Church–Congregant engagement strategies, as well as the singular Church–Congregant engagement strategy, the most often. Yet, audiences engaged significantly more with posts using the God–Congregant engagement strategy when compared to all other strategies. The use of engagement strategies and engagement received on posts varied according to geographical location and cultural differences, suggesting there may be a cultural aspect to what earns engagement from followers. Advertisers looking to increase online engagement should focus their efforts on persuasive messages that include the object-audience engagement strategy. This study advances advertising theory on engagement by suggesting that engagement is contingent upon the engagement strategy utilized as well as the specific region’s norms around the brand and community.
Token-Based Authentication Framework for 5G MEC Mobile Networks

MEC technology provides a distributed computing environment in 5G mobile networks for application and service hosting. It allows customers with different requirements and professional competencies to use the services offered by external suppliers. We consider a service access control framework on 5G MEC networks that is efficient, flexible, and user-friendly. Its central element is the MEC Enabler, which handles AAA requests for stakeholders accessing services hosted on the edge servers. The JSON Web Token (JWT) open standard is a suitable tool for the MEC Enabler to manage access control credentials and transfer them securely between parties. In this paper, in the context of access control, we propose the token reference pattern called JSON MEC Access Token (JMAT) and analyze the effectiveness of its available protection methods in compliance with the standard requirements of MEC-hosted services in 5G networks.
The Knowledge, Attitude and Practices of Allied Healthcare Professionals and Nurses towards Blood Sugar Level Measurement (BSL) for Non-Diabetic Patients in Pre- and Post-Surgery

Hypoglycemia complications in pre-and post-surgery are common among hospitalized patients with or without diabetes mellitus (DM) and associated with undesired treatment outcomes (1,2,3). That derived our incentive to conduct this “cross-sectional study of total 102 randomly selected respondents” aims to assess the knowledge, attitude, and practices among allied healthcare professionals and nurses towards BSL measurement for hospitalized nondiabetic patients in pre-and post-surgery. Data for this study was obtained in a questionnaire-based format from respondents. The questionnaire includes questions on demographical data, participant’s knowledge, attitude (reaction towards some hypoglycemic signs and symptoms), and evaluation of participant’s practices. Analysis shows that 74.5% of participants were aware of hypoglycemia complications, and 20.5% had some knowledge, while the rest (4.9%) were not aware. 72.5% of the participants showed the right attitude towards the signs and symptoms of hypoglycemia. The rest of the participants (27.5%) were not able to distinguish between the signs and symptoms of cardiac complications and hypoglycemic complications. We found that 68.6% of the participants followed the guidelines of BSL measurement at their workplace (hospital) while 31.4% of participants don’t. We found an association between the occupation and knowledge of the participants (P = 0.046). A significant association between occupation and practices of the participants was also found (P = 0.003). This study shows that nurses are more aware of hypoglycemia complications in pre-or post-surgery than AHPs. These results hint that AHPs need to expand their knowledge and awareness of hypoglycemia complications in pre-and post-surgery in order to avoid undesired treatment outcomes. Key words: Blood sugar level (BSL), Hypoglycemia, Non-diabetic, pre-and post-surgery, Nil-By-Mouth (NBM), Allied Healthcare Professionals (AHPs).
Analysis and Adequacy Methodology for Voltage Violations in Distribution Power Grid

This paper proposes a computational process development capable of filling the electric power sector shortage regarding voltage non-conformities identification in electric distribution power grid accounting for loads dynamic behavior at medium and low voltages. Actual distribution power grid data are used, with georeferencing to signal voltage transgressions locations, generate a report with voltage transgression indices and financial reimbursement values provided by legislation. The methodology compares regulatory requirements and makes available in software some possible actions in an attempt to adjust voltage levels, avoiding inconvenience and penalties for energy utilities providers. The method involves a data extractor construction for electricity provider company’s databases, computer simulations and comparison of obtained results with values established in electricity quality control standards. Thus, finding non-conformity locations and determining network adjustments to correct tension indexes in permanent regulation. The proposal features a reduction in electricity utilities operating costs, increasing efficiency in operation and energy quality available to consumers.
Breeding Performances of the European Blackbird (Turdus merula) in Morocco: Habitat Selection, Breeding Phenology, and Breeding Success

The European Blackbird (Turdus merula) is a widespread species. In Morocco, available knowledge on this species is limited to a few descriptive pieces of information with no detailed data provided. With climate change and the intensification of agricultural activities, the study of the breeding performances of this species is indispensable for management purposes. This study investigates breeding biology, nesting habitats, breeding chronology, and reproductive success of the European Blackbird in both apple orchards and surrounding woody vegetation at Ait Ayach (Morocco) between March and August 2016. We monitored weekly nest status, nesting sites, breeding dates, and failure factors. Results showed that the European Blackbird nests mainly in apple orchards, on Golden Delicious and Starkrimson Delicious trees. Nest height above the ground was 214.15 ± 0.09 cm. Blackbird nests were cup-shaped with medium size dimensions and built from twigs, including dry leaves, stems, and roots walled by the mud. Breeding activities started firstly by nest construction during the last week of April, secondly by egg laying during the first week of May, and thirdly by hatching during the second week of May. Among the 74 surveyed nests, 100% were active during the nesting phase and 88.38% of eggs have succeeded during the incubation phase. In total, 69.03% of chicks have been emancipated. In short, 15.9% of clutches were attacked by predators, 14.35% of clutches were failed due to nest desertion, and 8.75% of chicks were dead. Our study provides the first and only detailed data on reproductive parameters of the European Blackbird in Moroccan ecosystems. Data collected from this study provide valuable information for long-term monitoring of the Moroccan Blackbird population. Additionally, our data offer a possibility of large-scale comparative studies of the reproductive ecology of the Blackbird species.
Overview of Control Algorithm Verification Methods in Power Electronics Systems

The paper presents the existing verification methods for control algorithms in power electronics systems, including the application of model checking techniques. In the industry, the most frequently used verification methods are simulations and experiments; however, they have to be performed manually and do not give a 100% confidence that the system will operate correctly in all situations. Here we show the recent advancements in verification and performance assessment of power electronics systems with the usage of formal methods. Symbolic model checking can be used to achieve a guarantee that the system satisfies user-defined requirements, while statistical model checking combines simulation and statistical methods to gain statistically valid results that predict the behavior with high confidence. Both methods can be applied automatically before physical realization of the power electronics systems, so that any errors, incorrect assumptions or unforeseen situations are detected as early as possible. An additional functionality of verification with the use of formal methods is to check the converter operation in terms of reliability in various system operating conditions. It is possible to verify the distribution and uniformity of occurrence in time of the number of transistor switching, transistor conduction times for various current levels, etc. The information obtained in this way can be used to optimize control algorithms in terms of reliability in power electronics. The article provides an overview of various verification methods with an emphasis on statistical model checking. The basic functionalities of the methods, their construction, and their properties are indicated.
Realization of a Beam-Tilted Circularly Polarized Corporate-Fed Waveguide Slot Array in the 60 GHz Band

A beam-tilted circularly polarized (CP) corporate-fed waveguide slot array is accomplished in the 60 GHz band. The main beam tilting in the 45° cut-plane is achieved by introducing a corporate feeding circuit with a linearly tapered phase distribution. The T- and H-junctions with nonidentical output waveguide widths are newly proposed to realize progressive output phases. By cascading asymmetric T- and H-junctions into a <inline-formula> <tex-math notation="LaTeX">$16\times16$ </tex-math></inline-formula> way power divider, we design a <inline-formula> <tex-math notation="LaTeX">$32\times32$ </tex-math></inline-formula> element array consisting of <inline-formula> <tex-math notation="LaTeX">$256\,\,2\times 2$ </tex-math></inline-formula> element CP subarrays. The simulated tilt angle coincides with the theoretical one over the whole frequency band. The test antenna is fabricated by the diffusion bonding of thin copper plates. Stable beam directions and wideband operations are verified by the experimental evaluations. The overall reflection is sufficiently suppressed below −14 dB over the 56–67 GHz frequency band. The realized gain higher than 37 dBic is achieved over the frequency range of 59–64 GHz, while the AR is suppressed below 3.5 dB over the frequency range of 57.25–66.75 GHz.
Proliferation and osteoblast differentiation mice dental pulp stem cells between enzyme digestion and outgrowth method

The isolation method for dental pulp stem cells (DPSCs) is still unclear to obtain a conducive environment for DPSCs to proliferate. Enzymatic digestion and outgrowth method are two commonly used methods for DPSCs isolation but are not well characterized in mice DPSCs. This study aimed to compare these isolation methods and differentiation potential of mice DPSCs into bone cells. Dental pulp was extracted from mice’s incisors and subjected to isolation either by collagenase 1A or culture of pulp tissue in complete alpha-Modified Eagle Medium (αMEM). Both cells isolated were cultured until passage 4 and subjected to in vitro proliferation and differentiation analysis. Both cells exhibited fibroblastliked morphology, but cells isolated by enzyme digestion proliferate faster compare to outgrowth method. After 21 days of osteoblast differentiation, DPSCs isolated from enzyme digestion method showed alkaline phosphatase (ALP) activity slightly different as compared to outgrowth method. In conclusion, there is a significant difference between the cells isolated from enzyme digestion compare to outgrowth method with regard to proliferation and osteoblast differentiation. Thus, it is preferable to isolate by enzyme digestion as it is faster and consistent compared to outgrowth method.
The Role of Canary Island Date Palms in Physical Amenity Provisioning for Urban Landscape Settings

Canary Island date palms (Phoenix canariensis) have been planted as a landscaping feature plant throughout warm, temperate, and subtropical climates. The physical amenity provisioning of this species (shade effects, microclimate amelioration, water usage, etc.) has so far not been systematically assessed. This paper reports on temperature and humidity measurements in both a suburban and a rural location in SE Australia. The study demonstrates the effects of the palm canopy as regulator of humidity and provider of shade and, thus, amenity values in urban landscape settings. Drawing on published energy savings and growth requirements of the plant, the paper argues that Canary Island date palms are landscaping plants suitable to ameliorate the microclimate in urban neighborhoods with varied socio-economic conditions.
Comparison of Stock Price Prediction Models using Pre-trained Neural Networks

Several intelligent data mining approaches, including neural networks, have been widely employed by academics during the last decade. In today's rapidly evolving economy, stock market data prediction and analysis play a significant role. Several non-linear models like neural network, generalized autoregressive conditional heteroskedasticity (GARCH) and autoregressive conditional heteroscedasticity (ARCH) as well as linear models like Auto-Regressive Integrated Moving Average (ARIMA), Moving Average (MA) and Auto Regressive (AR) may be used for stock forecasting. The deep learning architectures inclusive of Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNN), Multilayer Perceptron (MLP) and Support Vector Machine (SVM) are used in this paper for stock price prediction of an organization by using the previously available stock prices. The National Stock Exchange (NSE) of India dataset is used for training the model with day-wise closing price. Data prediction is performed for a few sample companies selected on a random basis. Based on the comparison results, it is evident that the existing models are outperformed by CNN. The network can also perform stock predictions for other stock markets despite being trained with single market data as a common inner dynamics that has been shared between certain stock markets. When compared to the existing linear models, the neural network model outperforms them in a significant manner, which can be observed from the comparison results.
Different Morphologies of SnS2 Supported on 2D g-C3N4 for Excellent and Stable Visible Light Photocatalytic Hydrogen Generation

Highly efficient different morphologies of SnS2 (nanoparticles, nanosheets, and 3D flower-like)/g-C3N4 composites were, respectively, prepared via an elementary hydrothermal method that was integrated with the calcination means. The XRD results showed that the relative intensities of several diffraction peaks, especially (001), (100), (101), and (102), indicated that the as-prepared samples (SnS2 nanoparticle, SnS2 nanosheet, and 3D flower-like SnS2) should be dominated by different specific preferred growth of facets. In comparison with SnS2 and pure g-C3N4, the SnS2/g-C3N4 composites exhibited much higher H2 development performance under visible light irradiation in the presence of Na2SO3 and Na2S as the sacrificial agent. The SnS2 nanoparticles/g-C3N4 composites exhibit the highest visible-light-driven H2-generation rate of 6305.18 μmol h–1 g–1 without any noble metal as cocatalyst, which is approximately 16.98 times higher than that of SnS2 nanoparticles. In all, the SnS2 nanoparticles (SnS2 nanoparti.