Miracle-dz/UniFAR-FTUs huggingface dataset:
Roll Control of Morphing Aircraft with Synthetic Jet Actuators at a High Angle of Attack

Flow separation and dynamic stall occurring at a high angle of attack will lead to difficulty in control and maneuverability for morphing aircraft. This study proposes a novel active flow control technology using a synthetic jet actuator for the roll motion of morphing aircraft. With the help of the computational fluid dynamics method and vortex lattice method, the roll control model of morphing aircraft undergoing large shape change at a high angle of attack is established. In this model, both the array of the actuator with an optimized cavity shape and morphing span, which are subject to the input saturation constraint, are used to mimic the conventional control surface. Integrated flight control based on the sliding mode control method is designed to ensure the desired closed-loop asymptotic stability, wherein the radial basis function neural network is employed to provide the compensation induced by the input saturation constraint. To demonstrate the effectiveness of the control scheme, various control strategies for different combinations of input are proposed to maintain the roll motion. The numerical results show that the designed control law could track the target signal well, which suggests that the virtual control surface is an effective tool for maintaining the high flight performance of morphing aircraft.
3-D FEM–BEM Coupling for the Magnetic Field Computation in Thin Shells: Application to the Evaluation of Ship Magnetic Signature

In this article, a model based on finite element–boundary element methods (FEM–BEM) coupling is developed for the magnetic field computation in thin magnetic shells submitted to external magnetic fields. The model is formulated in terms of the reduced magnetic vector potential. Surface fictitious currents are used for the FEM–BEM coupling. Only the active arts are discretized by using edge elements. The model is validated by comparing with analytical results for a magnetic hollow sphere in a homogeneous magnetic field. An application to the evaluation of ship magnetization is then considered.
Influence of Non-Thermal Atmospheric Pressure Plasma Jet on Extracellular Activity of α-Amylase in Aspergillus oryzae

In a previous study, we found that plasma can enhance spore germination and α-amylase secretion in A. oryzae, a beneficial fungus used in fermentation. To confirm this, in the current study, we investigated the effects of plasma on development and α-amylase secretion using an enlarged sample size and a different plasma source: a plasma jet. There was a ~10% (p < 0.01) increase in spore germination upon non-thermal atmospheric pressure plasma jet (NTAPPJ) treatment for 5 min and 10 min, as compared with the control (no plasma treatment). The activity of α-amylase detected in potato dextrose broth (PDB) media during incubation was significantly elevated in plasma-treated samples, with a more obvious increase upon 10 min and 15 min treatments and 24–96 h incubation periods. The levels of the oxidation reduction potential (ORP) and NOX (nitrogen oxide species) were higher in the plasma-treated samples than in the control samples, suggesting that these two variables could serve as standard indicators for enhancing α-amylase activity after plasma treatment. Genome sequencing analysis showed approximately 0.0016–0.0017% variations (changes in 596–655 base pairs out of a total of 37,912,014 base pairs) in the genomic DNA sequence of A. oryzae after plasma treatment. Our results suggest that NATPPJ can enhance the spore germination and extracellular activity of α-amylase, probably by increasing the levels of ORP and NOX to an optimum level.
PRICING VARIANCE SWAPS UNDER DOUBLE HESTON STOCHASTIC VOLATILITY MODEL WITH STOCHASTIC INTEREST RATE

In this paper, we discuss the problem of pricing discretely sampled variance swaps under a hybrid stochastic model. Our modeling framework is a combination with a double Heston stochastic volatility model and a Cox–Ingersoll–Ross stochastic interest rate process. Due to the application of the T-forward measure with the stochastic interest process, we can only obtain an efficient semi-closed form of pricing formula for variance swaps instead of a closed-form solution based on the derivation of characteristic functions. The practicality of this hybrid model is demonstrated by numerical simulations.
A Hybrid Task Crash Recovery Solution for Edge Computing in IoT-Based Manufacturing

Smart factory is the deep integration of technology, business, products, and industry. The R&D of products, the construction of factory information, customer orders, and supply chain data are combined to act on the production. This paper proposes a Hybrid Internet of Things (H-IoT) platform framework, which consists of five layers: intelligent device layer, communication protocol layer, edge computing layer, IoT control layer, and application layer. Object Linking and Embedding (OLE) for Process Control (OPC) transmits the received device data to the database of the edge server through the TCP/IP protocol. After the edge server performs preprocessing such as data cleaning, the device data are uniformly collected and distributed through the IoT layer. The various subsystems of the smart factory obtain the required resource data through IoT. To run tasks uninterruptedly and efficiently, we propose a Container-Managed Task Crash Recovery Mechanism for the Edge Computing (EC) layer. We design a reasonable EC hierarchy, then propose a task migration scheduling strategy. Our method ensures the reliability and stability of manufacturing with mass data transmission even in the case of a random crash of partial edge servers.
The Use of Digital Healthcare Platforms During the COVID-19 Pandemic: the Consumer Perspective

Background: The spending on digital healthcare solutions is estimated to reach EUR 232 billion by 2025. Digital healthcare platforms are making transformative changes to conventional healthcare processes which can provide many beneficial improvements for both citizen and government provision to society. These benefits are obvious during pandemics such as Covid-19, when most healthcare services are offered through digital means. Objective: The objective of this study is to measure the role of trust and information quality when using digital healthcare platforms. These constructs are integrated with the Unified Theory of Acceptance and Use of Technology (UTAUT) to provide a better understanding of the consumer perspective regarding the use of digital healthcare platforms. Methods: Online structured self-administered questionnaire was utilized to collect the data. A sample consisting of 249 respondents participated in the questionnaire. Descriptive analysis was used to characterize the attributes of participants, and other statistical tests were conducted to ensure the reliability and validity of the survey. The model of the study was evaluated using Structural Equation Modelling (SEM) to explain the extent of the relationship among latent variables. Results: The study determined that facilitating conditions (t=0.233, p=0.023) and trust (t=0.324, p=0.005) had a significant impact on consumers’ behavioral intention of using such platforms during Covid-19 pandemic. Conclusion: This study highlighted the importance of facilitating conditions and trust factors for healthcare consumers of digital healthcare platforms especially during the pandemic time.
A novel IoT architecture for measuring and
visualizing influence of common factors on house dust concentration

The house dust mites are considered to be an allergen source and a main cause of allergic rhinitis and allergic asthma. House dust mites, their feces and other allergens which they produce are usually major constituents of house dust. Any stir in the air causes settled dust, and therefore allergen source found in it, to become airborne and thus easier to be inhaled by people, possibly causing different kinds of allergic reactions (sneezing, for example). In this paper, the correlation between common home activities (walking around, bed making, vacuuming etc.) and airborne dust concentration is examined. In order to do so, a novel Internet of things architecture is proposed that is capable of establishing that correlation. This proposed system not only collects dust concentration but it also visualizes it in an easy to understand and interpret way.
An Overview of the Miniaturization and Endurance for Wearable Devices

: The miniaturization and endurance of wearable devices have been the research direction for a long time. With the development of nanotechnology and the emergence of microelectronics products, people have explored many new strategies that may be applied to wearable devices. In this overview, we will summarize the recent research of wearable devices in these two directions, and summarize some available related technologies.
Chinese cultural theme parks: text mining and sentiment analysis

ABSTRACT This paper aims to explore cultural aspects and factors of Chinese theme parks and identify the sentiment of tourists’ online reviews, thus bridging the academic gap of a lack of knowledge on the theme park industry's cultural aspects. This research adopted social media analytics and explored 18,753 original reviews in 160 Chinese cultural theme parks. The results identified nine cultural aspects, and tourists’ attitudes among them are sorted in descending order as follows: historical figures and Chinese history/dynasties, folk art and traditional crafts, myths and legends, traditional architecture, literature and painting, drama and dance, folk customs and beliefs, traditional flowers and plants, and traditional food. Moreover, this paper identified the effects of cultural aspects of theme parks on tourists’ sentiment, which provided further insight for industry practitioners in setting marketing and operation strategies.
Interference-Aware Online Multicomponent Service Placement in Edge Cloud Networks and its AI Application

Edge computing that utilizes ubiquitous edge devices locating in close proximity to users is powerful for providing Quality of Service guaranteed computation offloading services. Toward the limited resources of edge servers and wireless links, large services can be split into multiple interconnected components to be served by multiple edge servers cooperatively. The current works on service placement either assume unsplittable services or ignore the geographically isolated property of edge servers. They also ignore the interference among online services that share the same physical nodes/links in terms of executing delay. Namely, every service adds load to the placed nodes/links and every increment on load of nodes/links risks delay violation of existing services. To overcome above challenges, this article emphasizes on the interference-aware (IA) online multicomponent service placement in edge cloud networks. First, the delay of tree-like services is analyzed considering the dependency among components, based on which the IA residual capacities of physical nodes, links, and paths are defined and formulated theoretically. Furthermore, we reduce the problem of multicomponent service placement to be NP-hard and transform it into an ant colony optimization (ACO) problem to obtain the near-optimal solution. More importantly, a level traversal component ranking method and an IA dynamic pruning method are proposed for ACO to achieve faster convergence, interference awareness, and higher acceptance ratio of services. Simulation results are presented to validate the effectiveness of proposed methods. In addition, the classic artificial intelligence application of image classification is experimented to further strength the motivation of IA investigation in practical.
A new approach for retinal vessel differentiation using binary particle swarm optimization

ABSTRACT Hypertensive Retinopathy is an ocular disease that occurs due to the presence of hypertension in the body. Hypertensive Retinopathy is quantified using a parameter known as Arteriovenous Ratio. To calculate Arteriovenous Ratio, retinal blood vessels in fundus images are segmented, classified, and measured. The complex structure of retinal vessels and uneven illumination in fundus images make retinal vessel classification a difficult task. In this paper, we propose a method for an improved differentiation of retinal vessels, that employs Binary Particle Swarm Optimization to select the optimal retinal vessel features. We design an objective function that considers the size and relevancy of the feature subset in classifying the retinal vessels. The designed objective function ensures the selected feature subset contains the minimum number of features and it corresponds to maximum vessel classification accuracy. Once, the optimization process has reached the stopping criteria, the selected feature subset is evaluated using Support Vector Machines. We compare the retinal vessel classification accuracy obtained using the proposed framework with the existing state-of-the-art approaches and found our method more accurate and robust on healthy as well as diseased images. The effectiveness of the proposed method is validated using the public as well as a private dataset.
How is the impact of Assessment for Learning (AfL) on mathematics learning in elementary schools?

This study aims to describe the effectiveness of the Assessment for Learning (AfL) in improving the quality of learning and mathematics learning outcomes in elementary schools. This study used a quasi-experimental method with a non-equivalent control group design. The instrument used was a test instrument with good validity, reliability, difficulty level, and different power. The non-test instrument was valid and good. Data analysis was performed using descriptive statistics, mean difference test, and variance difference test on AfL learning outcomes. The results showed that the effectiveness of learning in implementing AfL could be influenced by assessment preparation, student involvement, and follow-up assessment. The quantitative analysis results show that AfL can improve student learning outcomes; there is no mean-variance in AfL learning outcomes; There are differences in learning outcomes, and there are no variants in learning with AfL and conventional assessments. Suggestions, it is necessary to plan the assessment process, diagnose student needs and abilities. Moreover, there is a need for follow-up and feedback to see achievements
A Simulation Model for Sprinklers Irrigation System

Center pivot irrigation (CPI) system is one of the most efficient methods of applying irrigation water. It is a form of overhead sprinklers irrigation supported by trusses. The sprinkler flow rate out of each sprinkler orifice is based on the water pressure supplied to the sprinkler inlet. The objective of this paper is to build a simulation model for CPI to optimize performance of system estimating the expected number of a sprinklers and diameter of nozzle according to the required water quantities.
Conducting Polymers in Biological Systems

Conducting polymers (CPs) were first fabricated in the 70s of XX century as a novel generation of organic materials that have both electrical and optical properties similar to those of metals and inorganic semiconductors. The fact that several tissues are responsive to electrical fields and stimuli has made CPs attractive for a number of biological and medical applications. This review provides information on desirable CP properties specific to biomedical applications and how CPs have been optimized to generate these properties. The manuscript first introduces different types of CPs, their unique properties and their synthesis. Then specific information is provided on their modification for use in applications such as biosensors, medical engineering, and also neural probes.
MLNet: Multi-level Classification Network

The point cloud classification network only uses point cloud structure features or edge features to construct the feature vector, so that the classification accuracy is low. To solve this problem, this paper proposes a multi-level classification network. First, the original point cloud is divided into small samples using the preprocessing algorithm to obtain batch input and improve training efficiency; then construct structural features and edge features for point cloud feature extraction, and obtain local fine-grained descriptions through multi-level expressions within and between points; then design a convolutional neural network for feature learning. With the deepening of the network level, the degree of feature abstraction level is higher and higher, and the degree of distinction increases, so as to effectively improve the accuracy. Using the Vaihingen dataset to test the MLMS-Net network, the accuracy rate reached 85.4%.
Are Emotions Important for College Teachers’ Intentions to Use the Online Learning System? An Integrated Model of TAM and PAD

Project based learning(PBL) is an innovative instructional strategy focusing on practice and participation, which emphasizes problem solving and integrates a variety of authentic learning approaches. As such, PBL is an appropriate instructional strategy to realize "learner-centered" and "ability-centered" education. As the core of teaching, whether teachers are willing to use the online system for PBL has become a key factor. Based on this, to investigate the influence of teachers' emotions on their intention to use the PBL online system is helpful to improve teachers' teaching. Using 196 Taiwan college teachers attending the workshops of PBL online system as the participants, this study combined TAM (Technology Acceptance Model) with PAD (pleasure, arousal, dominance) to propose a new, integrated model to clarify the impact of teachers’ emotions on the intentions to use the PBL online system. The results showed that: Among the original TAM, the variables of perceived usefulness and perceived ease of use were positive to the attitude and the attitude was positive to the intention of using the PBL online system; For the variables of PAD, the variables of pleasure and arousal were positive to the attitude and the variable of dominance was positive to the variable of perceived ease of use.
Students’ Transition from Secondary School French Programs into University Level French Immersion

A great deal of time and resources are invested throughout Canada to encourage students to learn French as a second official language through a variety of programs (core French, intensive French, and French immersion programs). Little is known, however, about the impact of these efforts once French language learners complete their high school studies. This paper reports on longitudinal qualitative case studies of two students registered within a Canadian university-level immersion stream. Drawing on an academic discourse socialization approach, the paper examines students’ perspectives of their literacy development as they transition from high school French language programs to a universitylevel immersion program designed to promote advanced levels of bilingualism. Findings stress how the experience of transitioning from French high school programs to university immersion challenges students’ perception of themselves as French learners and their notion of the legitimacy of their high school French experiences.
Bagley polygon power divider realized by ridge gap waveguide technology

The novel ridge‐gap waveguide (RGW) technology which uses a full metal structure has many advantages in micro/mm‐wave frequencies such as low loss, broad bandwidth, low sensitivity to manufacturing errors, and easy integration with active components, and so forth. In this paper, a Ku‐band 3‐way Bagley polygon power divider (BPD) is proposed and experimentally demonstrated based on the RGW technology for the first time, to the best of our knowledge. An RGW‐toWR62 transition is also designed and fabricated. The proposed three‐way RGW‐based BPD with WR62 transitions shows low‐loss equal‐power division in phase with good impedance matching and isolation between output ports in the Ku band. The proposed RGW‐based BPD can be extended to an N‐way power divider.
A fistful of followers: the resilience of the second-order campaign model?

ABSTRACT EP elections are widely regarded as the archetypal second-order national election. Although parties’ strategic moves are frequently mediated by traditional media, parties are increasingly using alternative communication strategies, as social media, to communicate directly to their electorate. Social media can be particularly relevant in ‘bridging the gap’ with voters in second-order elections. After 2014, EP elections took place in a context where policy had been, to a non-negligible extent, perceived to have been shaped at the European level. The extent to which Eurozone crisis ‘disrupted’ the second-order model requires further examination. Through the analysis of the activities of political parties in social media, this study seeks to assess the extent to which the Eurozone crisis triggered more intense campaigns while assessing the partisan variables that explain variation in parties’ levels of activities. Overall, social media activity tends to suggest the resilience of the second-order model. This article highlights that the economic downturn has very much forced European issues into the political agendas, unveiling important signs of a disruption of the second-order model. Also, the politicisation of Europe in the first elections after the Eurozone crises (2019) was characterised by higher levels of activities of parties that openly contested the EU.
Sustainable Process and Product Innovation in the Eyewear Sector: The Role of Industry 4.0 Enabling Technologies

This paper aims to provide the reader with an organic view of the eyewear sector considering both market and quality aspects and evaluating the role of Industry 4.0 in process and product innovation for managing consumer health, analyzing a case study of a leading multinational company in the eyewear and ophthalmic lenses sector. The research has been developed with a qualitative approach. The study is a conceptual development and it uses an exploratory interview to create a single case study. The case study was developed with the realization by the researcher of a semi-structured interview. The selected interlocutor was the Innovation Manager of Alpha Optics. It has been decided to focus the attention on this figure, as it was responsible for the realization and introduction into the company of Industry 4.0 enabling technologies for developing health innovations. From this case study it was possible to observe how the connection with the trends that influence the demand for eyeglasses is a driving factor for product innovation. Products increasingly adapted to the needs of young people and the use of digital devices seem to be the ones on which the greatest number of innovations are concentrated.