bluuebunny/crossref_metadata_2025 huggingface dataset:
Prenatal Diagnosis of Uniparental Disomy in Cases of Rare Autosomal Trisomies Detected Using Noninvasive Prenatal Test: A Case of Prader–Willi Syndrome
Authors: Hong Da Kyung , Park Ji Eun , Kang Kyung Min , Shim Sung Han , Shim So Hyun , Han You Jung , Cho Hee Young , Cha Dong Hyun
Published: February 2023

Rare autosomal trisomies (RATs) other than common aneuploidies can be detected using noninvasive prenatal testing (NIPT). However, conventional karyotyping is insufficient for evaluating diploid fetuses with uniparental disomy (UPD) due to trisomy rescue. Using the diagnostic process for Prader–Willi syndrome (PWS), we aim to describe the need for additional prenatal diagnostic testing for confirming UPD in fetuses diagnosed with RATs via NIPT and its clinical implications. NIPT was performed using the massively parallel sequencing (MPS) method, and all pregnant women with RATs underwent amniocentesis. After confirming the normal karyotype, short tandem repeat (STR) analysis, methylation-specific PCR (MS-PCR), and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) were performed to detect UPD. Overall, six cases were diagnosed with RATs. There was a suspicion of trisomies of chromosomes 7, 8, and 15 in two cases each. However, these cases were confirmed to have a normal karyotype using amniocentesis. In one of six cases, PWS caused by maternal UPD 15 was diagnosed using MS-PCR and MS-MLPA. We propose that in cases where RAT is detected by NIPT, UPD should be considered following trisomy rescue. Even if amniocentesis confirms a normal karyotype, UPD testing (such as MS-PCR and MS-MLPA) should be recommended for accurate assessment, as an accurate diagnosis can lead to appropriate genetic counseling and improved overall pregnancy management.
Prognostic Significance of Ultrasound Characteristics and Body Mass Index in Patients with Apparent Early-Stage Cervical Cancer: A Single-Center, Retrospective, Cohort Study
Authors: Bizzarri Nicolò , Biscione Antonella , Moro Francesca , Pedone Anchora Luigi , Catinella Valeria , Certelli Camilla , Teodorico Elena , Fagotti Anna , Fanfani Francesco , Kucukmetin Ali , Querleu Denis , Ferrandina Gabriella , Scambia Giovanni , Testa Antonia
Published: February 2023

The primary aim of the present study was to investigate the prognostic impact (defined as disease-free—DFS and overall survival—OS) of the ultrasound scan tumor parameters, patients’ anthropometric parameters, and their combination in early-stage cervical cancer. The secondary aim was to assess the relation between ultrasound characteristics and pathological parametrial infiltration. This is a retrospective, single-center, observational cohort study. Consecutive patients with clinical FIGO 2018 stage IA1–IB2 and IIA1 cervical cancer who underwent preoperative ultrasound examination and radical surgery between 02/2012 and 06/2019 were included. Patients who underwent neo-adjuvant treatment, fertility sparing surgery, and pre-operative conization were excluded. Data from 164 patients were analyzed. Body mass index (BMI) ≤20 Kg/m2 (p < 0.001) and ultrasound tumor volume (p = 0.038) were related to a higher risk of recurrence. The ratios between ultrasound tumor volume and BMI, ultrasound tumor volume and height, and ultrasound largest tumor diameter and BMI were significantly related to a higher risk of recurrence (p = 0.011, p = 0.031, and p = 0.017, respectively). The only anthropometric characteristic related to a higher risk of death was BMI ≤20 Kg/m2 (p = 0.021). In the multivariate analysis, the ratio between ultrasound-measured largest tumor diameter and cervix-fundus uterine diameter (with 37 as the cut-off) was significantly associated with pathological microscopic parametrial infiltration (p = 0.018). In conclusion, a low BMI was the most significant anthropometric biomarker impairing DFS and OS in patients with apparent early-stage cervical cancer. The ratios between ultrasound tumor volume and BMI, ultrasound tumor volume and height, and ultrasound largest tumor diameter and BMI significantly affected DFS but not OS. The ratio between ultrasound-measured largest tumor diameter and cervix-fundus uterine diameter was related to parametrial infiltration. These novel prognostic parameters may be useful in pre-operative workup for a patient-tailored treatment in early-stage cervical cancer.
Artificial Intelligence-Assisted Chest X-ray for the Diagnosis of COVID-19: A Systematic Review and Meta-Analysis
Authors: Tzeng I-Shiang , Hsieh Po-Chun , Su Wen-Lin , Hsieh Tsung-Han , Chang Sheng-Chang
Published: February 2023

Because it is an accessible and routine image test, medical personnel commonly use a chest X-ray for COVID-19 infections. Artificial intelligence (AI) is now widely applied to improve the precision of routine image tests. Hence, we investigated the clinical merit of the chest X-ray to detect COVID-19 when assisted by AI. We used PubMed, Cochrane Library, MedRxiv, ArXiv, and Embase to search for relevant research published between 1 January 2020 and 30 May 2022. We collected essays that dissected AI-based measures used for patients diagnosed with COVID-19 and excluded research lacking measurements using relevant parameters (i.e., sensitivity, specificity, and area under curve). Two independent researchers summarized the information, and discords were eliminated by consensus. A random effects model was used to calculate the pooled sensitivities and specificities. The sensitivity of the included research studies was enhanced by eliminating research with possible heterogeneity. A summary receiver operating characteristic curve (SROC) was generated to investigate the diagnostic value for detecting COVID-19 patients. Nine studies were recruited in this analysis, including 39,603 subjects. The pooled sensitivity and specificity were estimated as 0.9472 (p = 0.0338, 95% CI 0.9009–0.9959) and 0.9610 (p < 0.0001, 95% CI 0.9428–0.9795), respectively. The area under the SROC was 0.98 (95% CI 0.94–1.00). The heterogeneity of diagnostic odds ratio was presented in the recruited studies (I2 = 36.212, p = 0.129). The AI-assisted chest X-ray scan for COVID-19 detection offered excellent diagnostic potential and broader application.
The Role of Magnetic Resonance Imaging (MRI) in the Diagnosis of Pancreatic Cystic Lesions (PCLs)
Authors: Quingalahua Elit , Al-Hawary Mahmoud M. , Machicado Jorge D.
Published: February 2023

Pancreatic cystic lesions (PCLs) are a common incidental finding on cross-sectional imaging. Given the high signal to noise and contrast resolution, multi-parametric capability and lack of ionizing radiation, magnetic resonance imaging (MRI) has become the non-invasive method of choice to predict cyst type, risk stratify the presence of neoplasia, and monitor changes during surveillance. In many patients with PCLs, the combination of MRI and the patient’s history and demographics will suffice to stratify lesions and guide treatment decisions. In other patients, especially those with worrisome or high-risk features, a multimodal diagnostic approach that includes endoscopic ultrasound (EUS) with fluid analysis, digital pathomics, and/or molecular analysis is often necessary to decide on management options. The application of radiomics and artificial intelligence in MRI may improve the ability to non-invasively stratify PCLs and better guide treatment decisions. This review will summarize the evidence on the evolution of MRI for PCLs, the prevalence of PCLs using MRI, and the MRI features to diagnose specific PCL types and early malignancy. We will also describe topics such as the utility of gadolinium and secretin in MRIs of PCLs, the limitations of MRI for PCLs, and future directions.
Striatal Patchwork of D1-like and D2-like Receptors Binding Densities in Rats with Genetic Audiogenic and Absence Epilepsies
Authors: Tsyba Evgeniya T. , Midzyanovskaya Inna S. , Birioukova Lidia M. , Tuomisto Leena M. , van Luijtelaar Gilles , Abbasova Kenul R.
Published: February 2023

Binding densities to dopamine D1-like and D2-like receptors (D1DR and D2DR) were studied in brain regions of animals with genetic generalized audiogenic (AGS) and/or absence (AbS) epilepsy (KM, WAG/Rij-AGS, and WAG/Rij rats, respectively) as compared to non-epileptic Wistar (WS) rats. Convulsive epilepsy (AGS) exerted a major effect on the striatal subregional binding densities for D1DR and D2DR. An increased binding density to D1DR was found in the dorsal striatal subregions of AGS-prone rats. Similar changes were seen for D2DR in the central and dorsal striatal territories. Subregions of the nucleus accumbens demonstrated consistent subregional decreases in the binding densities of D1DR and D2DR in epileptic animals, irrespective of epilepsy types. This was seen for D1DR in the dorsal core, dorsal, and ventrolateral shell; and for D2DR in the dorsal, dorsolateral, and ventrolateral shell. An increased density of D2DR was found in the motor cortex of AGS-prone rats. An AGS-related increase in binding densities to D1DR and D2DR in the dorsal striatum and motor cortex, areas responsible for motor activity, possibly reflects the activation of brain anticonvulsive loops. General epilepsy-related decreases in binding densities to D1DR and D2DR in the accumbal subregions might contribute to behavioral comorbidities of epilepsy.
Cranial Autonomic Symptoms and Neck Pain in Differential Diagnosis of Migraine
Authors: Vicente Beatriz Nunes , Oliveira Renato , Martins Isabel Pavão , Gil-Gouveia Raquel
Published: February 2023

Cranial autonomic symptoms and neck pain have been reported to be highly prevalent in migraine, although they are rarely considered in clinical evaluation. The aim of this review is to focus on the prevalence, pathophysiology, and clinical characteristics of these two symptoms, and their importance in the differential diagnosis between migraines and other headaches. The most common cranial autonomic symptoms are aural fullness, lacrimation, facial/forehead sweating, and conjunctival injection. Migraineurs experiencing cranial autonomic symptoms are more likely to have more severe, frequent, and longer attacks, as well as higher rates of photophobia, phonophobia, osmophobia, and allodynia. Cranial autonomic symptoms occur due to the activation of the trigeminal autonomic reflex, and the differential diagnosis with cluster headaches can be challenging. Neck pain can be part of the migraine prodromal symptoms or act as a trigger for a migraine attack. The prevalence of neck pain correlates with headache frequency and is associated with treatment resistance and greater disability. The convergence between upper cervical and trigeminal nociception via the trigeminal nucleus caudalis is the likely mechanism for neck pain in migraine. The recognition of cranial autonomic symptoms and neck pain as potential migraine features is important because they often contribute to the misdiagnosis of cervicogenic problems, tension-type headache, cluster headache, and rhinosinusitis in migraine patients, delaying appropriate attack and disease management.
Understanding the Quality of Life and Its Related Factors in Orthodontics Postgraduate Students: A Mixed Methods Approach
Authors: López-Trujillo Laura V. , López-Valencia Sara C. , Agudelo-Suárez Andrés A.
Published: February 2023

This study analyzed the academic, sociodemographic, and labor conditions related to the quality of life (QOL) of orthodontics postgraduate students in Colombia. A mixed study (explanatory sequential design) was conducted. An online cross-sectional survey (n = 84; 64.3% females) was carried out with sociodemographic, academic, social support, health, labor, and QOL (WHOQOL-BREF) variables. Descriptive, bivariate analyses, and multivariate linear regression were performed. Focus groups (FGs) delved into aspects of relevance regarding QOL and determinants, through qualitative content analysis and triangulation of information. The median score in the four WHOQOL-BREF dimensions surpasses 50 points, with the highest score being in the psychological dimension (62.5 ± 16.7). According to the multivariate linear regression models, the variables significantly associated with QOL scores were playing sports, being married/living together, normal BMI, low social support, and medium/low socioeconomic status. The qualitative results explained the determinants of QOL in the personal, academic, and social dimensions of the participants. The discourses showed that the postgraduate course represents a resignification of their life, where their QOL is affected by the difficulties of their academic development, by the difficulty of reconciling the personal academic load with their affective, work, and social life, and by the stress they experience in their staff process. In conclusion, the participants’ QOL was moderate and affected by different factors. The findings highlighted the importance of mental health promotion and well-being strategies in students of orthodontic postgraduate training programs in Colombia for improving QOL.
A Computational Investigation of the Hover Mechanism of an Innovated Disc-Shaped VTOL UAV
Authors: Ahmed Snikdha Samia Shahrin , Chen Shih-Hsiung
Published: February 2023

Inventive approaches are constantly being revealed in the field of vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) configuration concepts and designs. To date, a body-associated configuration of UAVs for augmented lift remains unclear among other approached designs. The current paper investigates the mechanism of a high-lift ducted fan mounted in the central body for VTOL UAV designs. We report an unresolved design of a disc-shaped UAV with a single rotor that aims to enhance the cost-effectiveness of fuel consumption with a substantial contribution of body lift to hover thrust. The convex upper surface curvature was applied to generate a significant lift contribution from the body during hover. The computational fluid dynamics (CFD) approach based on unstructured discretization followed by three-dimensional steady Reynolds-averaged Navier–Stokes (RANS) flow was applied in ANSYS CFX to mechanistically investigate the underlying design considerations. The disc-shaped UAV uses the lip curvature on the duct inlet to generate a vertical force that demonstrates a significant contribution of 95% of the rotor thrust during hovering. The UAV’s upper surface generates prolonged flow entrainment free from momentum losses in swirling flows. This phenomenon is followed by reduced power consumption in hovering and vertical flight, making the UAV aerodynamically stable and environmentally safe.
Fault Tolerant Control of Drone Interceptors Using Command Filtered Backstepping and Fault Weighting Dynamic Control Allocation
Authors: Xu Biao , Ma Qingfeng , Feng Jianxin , Zhang Jinpeng
Published: February 2023

This paper proposes a fault tolerant control strategy for drone interceptors with fixed wings and reaction jets subject to actuator faults. The drone interceptors have both continuous and discrete actuators, which pose a challenge to the control system design. The proposed fault tolerant control system consists of two parts, a nonlinear virtual control law and a dynamic control allocator. To deal with system uncertainty and quantization error, a virtual control law with a parameter update law is designed by command filtered backstepping. Then, a fault weighting dynamic control allocation algorithm is developed to distribute the virtual control signal to the actuators on the drone interceptor. When an actuator fault occurs, the proposed fault weighting dynamic control allocation scheme can redistribute the control signals to the remaining actuators. The effectiveness of the proposed algorithm is confirmed by numerical simulation.
Adaptive Fault-Tolerant Tracking Control of Quadrotor UAVs against Uncertainties of Inertial Matrices and State Constraints
Authors: Yang Shuai , Zou Zhihui , Li Yingchao , Shi Haodong , Fu Qiang
Published: February 2023

This paper presents a study on a quadrotor unmanned aerial vehicle (UAV) fault-tolerant control scheme. According to the attitude model and safety control of the aircraft under the uncertainty of inertial matrix, the attitude state constraint by reinforcement learning is designed to ensure safety. Even if the boundary is crossed, it can be pulled back to the boundary by means of a designed penalty function with reinforcement learning. Meanwhile, in order to inhibit the oscillation caused by immediate reward as usual, an adaptive update law is proposed. Furthermore, considering the coupled actuator fault and system input saturation due to uncertainty of inertial matrix, the Nussbaum-type function is utilized in this work to handle this challenge, which likely causes the singularity of inertia matrix. As a consequence, combined with the Lyapunov stability theory, it is confirmed that the proposed FTC scheme ensures that all the closed-loop signals are bounded. Simulation results are carried out to illustrate the effectiveness and advantage of the proposed control scheme.
Can the Sci-Tech Innovation Increase the China’s Green Brands Value?—Evidence from Threshold Effect and Spatial Dubin Model
Authors: Zhang Xiaofei , Xiao Yang , Wang Linyu
Published: February 2023

Based on the perspective of the innovation value chain, sci-tech innovation is divided into two stages: R&D and achievement transformation. This paper uses panel data from 25 provinces in China as the sample. We utilize a two-way fixed effect model, spatial Dubin model, and panel threshold model to discuss the impact of two-stage innovation efficiency on the value of the green brand, the spatial effect of this impact, and the threshold role of intellectual property protection in the process. The results indicate that: (1) the two stages of innovation efficiency have a positive impact on the value of green brands, and the effect of the eastern region is significantly better than that of the central and western regions. (2) The spatial spillover effect of the two stages of regional innovation efficiency on the value of green brands is evident, especially in the eastern region. (3) The innovation value chain has a pronounced spillover effect. (4) The single threshold effect of intellectual property protection is significant. When the threshold is crossed, the positive impact of the two stages of innovation efficiency on the value of green brands is significantly enhanced. (5) The influence of economic development level, openness, market size, and marketization degree on the value of green brands shows remarkable regional differences. In conclusion, this study contributes to understanding green brands’ growth and provides important implications for developing independent brands in various regions of China.
Optimal Tracking Control of a Nonlinear Multiagent System Using Q-Learning via Event-Triggered Reinforcement Learning
Authors: Wang Ziwei , Wang Xin , Tang Yijie , Liu Ying , Hu Jun
Published: February 2023

This article offers an optimal control tracking method using an event-triggered technique and the internal reinforcement Q-learning (IrQL) algorithm to address the tracking control issue of unknown nonlinear systems with multiple agents (MASs). Relying on the internal reinforcement reward (IRR) formula, a Q-learning function is calculated, and then the iteration IRQL method is developed. In contrast to mechanisms triggered by time, an event-triggered algorithm reduces the rate of transmission and computational load, since the controller may only be upgraded when the predetermined triggering circumstances are met. In addition, in order to implement the suggested system, a neutral reinforce-critic-actor (RCA) network structure is created that may assess the indices of performance and online learning of the event-triggering mechanism. This strategy is intended to be data-driven without having in-depth knowledge of system dynamics. We must develop the event-triggered weight tuning rule, which only modifies the parameters of the actor neutral network (ANN) in response to triggering cases. In addition, a Lyapunov-based convergence study of the reinforce-critic-actor neutral network (NN) is presented. Lastly, an example demonstrates the accessibility and efficiency of the suggested approach.
Complexity and Entropy in Physiological Signals (CEPS): Resonance Breathing Rate Assessed Using Measures of Fractal Dimension, Heart Rate Asymmetry and Permutation Entropy
Authors: Mayor David , Steffert Tony , Datseris George , Firth Andrea , Panday Deepak , Kandel Harikala , Banks Duncan
Published: February 2023

Background: As technology becomes more sophisticated, more accessible methods of interpretating Big Data become essential. We have continued to develop Complexity and Entropy in Physiological Signals (CEPS) as an open access MATLAB® GUI (graphical user interface) providing multiple methods for the modification and analysis of physiological data. Methods: To demonstrate the functionality of the software, data were collected from 44 healthy adults for a study investigating the effects on vagal tone of breathing paced at five different rates, as well as self-paced and un-paced. Five-minute 15-s recordings were used. Results were also compared with those from shorter segments of the data. Electrocardiogram (ECG), electrodermal activity (EDA) and Respiration (RSP) data were recorded. Particular attention was paid to COVID risk mitigation, and to parameter tuning for the CEPS measures. For comparison, data were processed using Kubios HRV, RR-APET and DynamicalSystems.jl software. We also compared findings for ECG RR interval (RRi) data resampled at 4 Hz (4R) or 10 Hz (10R), and non-resampled (noR). In total, we used around 190–220 measures from CEPS at various scales, depending on the analysis undertaken, with our investigation focused on three families of measures: 22 fractal dimension (FD) measures, 40 heart rate asymmetries or measures derived from Poincaré plots (HRA), and 8 measures based on permutation entropy (PE). Results: FDs for the RRi data differentiated strongly between breathing rates, whether data were resampled or not, increasing between 5 and 7 breaths per minute (BrPM). Largest effect sizes for RRi (4R and noR) differentiation between breathing rates were found for the PE-based measures. Measures that both differentiated well between breathing rates and were consistent across different RRi data lengths (1–5 min) included five PE-based (noR) and three FDs (4R). Of the top 12 measures with short-data values consistently within ± 5% of their values for the 5-min data, five were FDs, one was PE-based, and none were HRAs. Effect sizes were usually greater for CEPS measures than for those implemented in DynamicalSystems.jl. Conclusion: The updated CEPS software enables visualisation and analysis of multichannel physiological data using a variety of established and recently introduced complexity entropy measures. Although equal resampling is theoretically important for FD estimation, it appears that FD measures may also be usefully applied to non-resampled data.
The Entropy of Digital Texts—The Mathematical Background of Correctness
Authors: Csernoch Mária , Nagy Keve , Nagy Tímea
Published: February 2023

Based on Shannon’s communication theory, in the present paper, we provide the theoretical background to finding an objective measurement—the text-entropy—that can describe the quality of digital natural language documents handled with word processors. The text-entropy can be calculated from the formatting, correction, and modification entropy, and based on these values, we are able to tell how correct or how erroneous digital text-based documents are. To present how the theory can be applied to real-world texts, for the present study, three erroneous MS Word documents were selected. With these examples, we can demonstrate how to build their correcting, formatting, and modification algorithms, to calculate the time spent on modification and the entropy of the completed tasks, in both the original erroneous and the corrected documents. In general, it was found that using and modifying properly edited and formatted digital texts requires less or an equal number of knowledge-items. In information theory, it means that less data must be put on the communication channel than in the case of erroneous documents. The analysis also revealed that in the corrected documents not only the quantity of the data is less, but the quality of the data (knowledge pieces) is higher. As the consequence of these two findings, it is proven that the modification time of erroneous documents is severalfold of the correct ones, even in the case of minimal first level actions. It is also proven that to avoid the repetition of the time- and resource-consuming actions, we must correct the documents before their modification.
Competition Prospects in Regulated Market of a Baltic Country
Authors: Burinskienė Aurelija
Published: February 2023

The author examines competition prospects in the regulated market of a selected EU country to investigate specific policy choices. Under full market regulation, the actors have the exclusive right to deliver economic transactions. (1) Literature review: The theoretical part starts with the presentation of actors’ heterogeneity and their market competition. (2) Methods: During empirical research, the author revised the cost structure and tested assumptions of the new trade theory of heterogenous firms and the impact of this heterogeneity on actors’ competition. The author formed a three-step methodology where at the beginning, the actors are described, then a regression model is formulated, and volumes of delivered services are analyzed. In the end of this study, the author investigated if the costs of regulated market participants are characterized by the distribution of Pareto and analyzed the gaps between regulated prices and the level of costs. The author applied Pareto distribution and LS regression methods in the study. (3) Results: Although the author found that the market participants in the market concerned are very different, their distribution according to the Pareto distribution function could not be confirmed. (4) Conclusions: The study shows that competition prospects in a regulated market differ. This is proven by analyzing the impact of this heterogeneity on actors’ competition. These results are essential in formulating the suggestion of economic policy.
Motion Capture Systems and Their Use in Educational Research: Insights from a Systematic Literature Review
Authors: Reuter Anna Sophia , Schindler Maike
Published: February 2023

Motion capture is gaining significance in educational research. Different motion capture systems (MCSs) are used in educational research for different purposes and in different ways, which creates a diversity that is difficult to monitor. The aim of this article is to provide an overview of MCSs and their uses in educational research addressing primary and secondary school education. We conducted a systematic review focusing on the types of MCSs and the concrete systems being used, looking at how they are used, the purposes of their use, the aims and the research questions under investigation, the subjects/topics addressed in the studies, the locations/places of use, the potential benefits of using MCSs perceived by the researchers, and the underlying theories of movement. Based on n = 20 studies focusing on primary and secondary school education identified in our database search, we found that these studies mainly used optical MCSs. Furthermore, we identified three main purposes of their use: to directly support the learning process of students, as analysis tools, or for developing tutoring systems that support students in their learning. This paper gives insights into the use of MCSs in educational research and provides a springboard for further research using MCSs in educational research.
An Inclusive Approach to Teaching Quantum Mechanics in Secondary School
Authors: Colletti Leonardo
Published: February 2023

Quantum physics is not only a fundamental part of physics education per se but could offer an opportunity to develop cultural tools also relevant outside the boundaries of physics, for instance helping raise awareness about basic cognitive patterns or providing a model for how science works and grows. Given this kind of significance, when it comes to teaching quantum mechanics in secondary school, instructors should be as inclusive as possible; rather than working out its mathematical or technical aspects, which ultimately may turn out inadequate at this level, they should try to make sense of the subject, so that students not oriented toward a STEM-related career are also given the possibility of appreciating the cultural depths reached by physics. Therefore, based on my experience with numerous classes and by making broad reference to the philosophical discipline of hermeneutics, I argue that quantum mechanics represents an invaluable opportunity for each and every learner to broaden and enrich his or her set of cognitive tools with which to make sense of both the outer and inner world. An essential but decade-long qualitative survey clearly shows that by approaching quantum physics with this purpose, all physics and science itself acquire a new relevance in students’ and society’s eyes.
A Novel Methodology to Develop STEAM Projects According to National Curricula
Authors: Montés Nicolás , Zapatera Alberto , Ruiz Francisco , Zuccato Laura , Rainero Sandra , Zanetti Amerigo , Gallon Ketty , Pacheco Gabriel , Mancuso Anna , Kofteros Alesandros , Marathefti Matina
Published: February 2023

The objective of this work is the elaboration of a methodology to develop STEAM projects (Science (S), Technology (T), Engineering (E), Art (A) and Mathematics (M)). The methodology proposed in this article is part of the results of the project ERASMUS+DART4City (2020-1-ES01-KA227-SCH-095545) “Empowering Arts and creativity for the cities of tomorrow”, whose objective is to design a methodology in order to develop STEAM projects from European curricula. The proposed methodology emerges after analysing, among others, the curricula from Spain, Italy, Cyprus, France, Finland and Germany, taking into account the international perspective of STEAM education, their priorities and problems. The proposal has two variants: “forward” and “backward”. Both variants begin with the analysis of the curriculum in which the contents are grouped by similarity, classified according to STEAM disciplines so that the thematic areas can be obtained. Subsequently, in the “forward” variant, the thematic areas with most connections are selected as areas of opportunity; for the development of the STEAM project, so from the “forward” methodology, the teacher will be able to select an area of opportunity and develop the project around it, so, the concept or project idea comes from an area of oportunity. The “backward” variant starts from a concept considered interesting for society or just for the teacher and which will become the main theme of the STEAM project and, from that concept, we will select the thematic areas of the curriculum that can be included in the project. The main difference bewteen both methodologies is that in the “forward” variant, the STEAM project concept comes from an area of oportunity detected in the curriculum meanwhile in the “backward” variant the concept of the STEAM project comes from the teacher, without taking into acount, initially, the curriculum. This article shows an example of application of each variant. From the “forward” variant, the STEAM project “Sustainable City” is shown for years 4, 5 and 6 of Primary Education, which has been carried out from the opportunity area “Sustainability”. From the “backward” variant, we develop the STEAM project, whose main theme is cooking, in which, based on this theme, 10 tests are developed, each of them related to different thematic areas of the Spanish curriculum.
Mobile Eye Tracking during Experimenting with Digital Scaffolding—Gaze Shifts between Augmented Reality and Experiment during Zinc Iodide Electrolysis Set-Up
Authors: Fleischer Timo , Deibl Ines , Moser Stephanie , Strahl Alexander , Maier Simone , Zumbach Joerg
Published: February 2023

In this exploratory eye tracking study, gaze behavior during an experiment on electrolysis of a zinc iodide solution has been examined. The experiment is designed according to inquiry-based learning and therefore well suited to students’ self-directed experimenting in science classrooms. Scaffolding by means of stepwise presented digital hints (sequential scaffolds), here by means of augmented reality (AR), supported learners during the experiment. Two succeeding AR-hints were offered. This research focuses on the set-up of the experiment by learners and the change of gaze between the AR-hints and the real experiment. This was investigated by means of mobile eye tracking. For the analysis of the gaze changes, scanpath analyses are used. Areas of Interest-based visualizations such as radial transition graphs and scarf plots are used to compare and detect similar or different gaze behaviors of participants. Results reveal that students first look at the AR-hints, try to memorize the construction and then switch to setting up the experiment. Recurrent changes of gaze between the AR-hints and the experiment hardly, or do not, occur. Furthermore, students who had already set up the experiment correctly with the first hint only use the second hint for evaluating correctness of their own set-up.
Design and Multi-Objective Optimization of a Composite Cage Rotor Bearingless Induction Motor
Authors: Lu Chengling , Yang Zebin , Sun Xiaodong , Ding Qifeng
Published: February 2023

To improve the quality of starting torque and suspension force, a composite cage rotor bearingless induction motor (CCR-BIM) is designed, which adopts a composite cage rotor structure that combines an inner rotor and an outer rotor. First, the overall structure of the CCR-BIM is designed, the composite cage rotor of the CCR-BIM is specially designed and analyzed for the induction principle, and the mathematical model of suspension force and torque is deduced. Second, the initial structural parameters are determined, and motor qualities, such as starting torque quality and suspension force quality, are compared and analyzed between the proposed motor and BIM using a finite element model (FEM). Third, based on the response surface model (RSM), a multi-objective improved NSGA-II is constructed, and the three optimization objectives of starting torque, suspension force, and suspension force pulsation are optimized. Finally, the results of the experimental setup prove that the starting torque increases by 6.98%, the suspension force increases by 5.45%, and the suspension force pulsation decreases by 18.54%. The effectiveness of the proposed motor and the correctness of the multi-objective optimization strategy are verified.
An Interoperable Blockchain Security Frameworks Based on Microservices and Smart Contract in IoT Environment
Authors: Alshudukhi Khulud Salem , Khemakhem Maher Ali , Eassa Fathy Elbouraey , Jambi Kamal Mansur
Published: February 2023

In the Internet of Things (IoT), technological developments have increased the significance of federated cloud systems with integrated cloud providers for exchange transactions. Monolithic IoT systems implement service-oriented architecture (SOA), which is complex for supporting scalability and communicating transactions in a federated cloud system. One weakness of conventional security methods is that they depend on a centralized party, which means there is a single point of failure for the system. In contrast, blockchain (BC) and microservice (MS) technologies allow services to split for independent tasks. In this research paper, we introduce BC security managers based on MS technology for federated cloud systems in an IoT environment. In addition, we present the design of the Federation Security System Manager (FSSM) MS with interoperability features. This enables the exchange of transactions between permissioned BC managers at different cloud providers, with some constraints. Furthermore, a security framework based on MSs and BCs is implemented to ensure security and protect access control. The security functions are deployed based on a smart contract between the permissioned BC managers to achieve interoperability. Finally, we introduce the development process of the proposed framework, which allows for interoperability and ensures the security and privacy of the participating data for a distributed IoT based on the federated cloud system.
Solution pH Effect on Drain-Gate Characteristics of SOI FET Biosensor
Authors: Bulgakova Anastasia , Berdyugin Anton , Naumova Olga , Fomin Boris , Pyshnyi Dmitrii , Chubarov Alexey , Dmitrienko Elena , Lomzov Alexander
Published: February 2023

Nanowire or nanobelt sensors based on silicon-on-insulator field-effect transistors (SOI-FETs) are one of the leading directions of label-free biosensors. An essential issue in this device construction type is obtaining reproducible results from electrochemical measurements. It is affected by many factors, including the measuring solution and the design parameters of the sensor. The biosensor surface should be charged minimally for the highest sensitivity and maximum effect from interaction with other charged molecules. Therefore, the pH value should be chosen so that the surface has a minimum charge. Here, we studied the SOI-FET sensor containing 12 nanobelt elements concatenated on a single substrate. Two types of sensing elements of similar design and different widths (0.2 or 3 μm) were located in the chips. The drain-gate measurements of wires with a width of 3 µm are sufficiently reproducible for the entire chip to obtain measurement statistics in air and deionized water. For the pH values from 3 to 12, we found significant changes in source-drain characteristics of nanobelts, which reach the plateau at pH values of 7 and higher. High pH sensitivity (ca. 1500 and 970 mV/pH) was observed in sensors of 3 μm and 0.2 μm in width in the range of pH values from 3 to 7. We found a higher “on” current to “off” current ratio for wide wires. At all studied pH values, Ion/Ioff was up to 4600 and 30,800 for 0.2 and 3 μm wires, respectively. In the scheme on the source-drain current measurements at fixed gate voltages, the highest sensitivity to the pH changes reaches a gate voltage of 13 and 19 V for 0.2 μm and 3 μm sensors, respectively. In summary, the most suitable is 3 μm nanobelt sensing elements for the reliable analysis of biomolecules and measurements at pH over 7.
Localization of Wireless Capsule Endoscopes Using the Receiver Selection Algorithm and a Modified Capsule Antenna
Authors: Oleksy Paweł , Januszkiewicz Łukasz
Published: February 2023

Wireless capsule endoscopes capture and transmit images of the human gastrointestinal tract for use in medical diagnosis. The localization of the capsule makes it possible to precisely identify areas with lesions detected during the examination. The antenna is an important element of the endoscopic capsule that is used for the transmission of the signal containing the recorded image of the inside of the digestive system. Antenna parameters influence also the performance of algorithms that are locating capsule endoscopes based on the analysis of the received signal. The zig-zag conformal antenna for the endoscope capsule is presented in this paper. It was examined both in simulation and tissue simulant liquid. It is then applied to an improved localization system that is based on phase difference analysis of received signals. In this new approach, the algorithm selects five external receivers from the predefined set and uses an adaptive estimation of human body model permittivity. The localization algorithm was verified with computer simulations. Remcom XFdtd software and both simplified and heterogeneous human body models were applied in simulations. The technique which uses automatic selection of the external receiver together with proposed antenna enhanced localization accuracy by about 15% compared with the previous version of this algorithm.
Recognition and Detection of Persimmon in a Natural Environment Based on an Improved YOLOv5 Model
Authors: Cao Ziang , Mei Fangfang , Zhang Dashan , Liu Bingyou , Wang Yuwei , Hou Wenhui
Published: February 2023

Accurate and rapid recognition of fruit is the guarantee of intelligent persimmon picking. Given the changes in the light and occlusion conditions in a natural environment, this study developed a detection method based on the improved YOLOv5 model. This approach has several critical steps, including optimizing the loss function based on the traditional YOLOv5, combining the centralized feature pyramid (CFP), integrating the convolutional block attention module (CBAM), and adding a small target detection layer. Images of ripe and unripe persimmons were collected from fruit trees. These images were preprocessed to enhance the contrast, and they were then extended by means of image enhancement to increase the robustness of the network. To test the proposed method, several experiments, including detection and comparative experiments, were conducted. From the detection experiments, persimmons in a natural environment could be detected successfully using the proposed model, with the accuracy rate reaching 92.69%, the recall rate reaching 94.05%, and the average accuracy rate reaching 95.53%. Furthermore, from the comparison experiments, the proposed model performed better than the traditional YOLOv5 and single-shot multibox detector (SSD) models, improving the detection accuracy while reducing the leak detection and false detection rate. These findings provide some references for the automatic picking of persimmons.
NT-GNN: Network Traffic Graph for 5G Mobile IoT Android Malware Detection
Authors: Liu Tianyue , Li Zhenwan , Long Haixia , Bilal Anas
Published: February 2023

IoT Android application is the most common implementation system in the mobile ecosystem. As assaults have increased over time, malware attacks will likely happen on 5G mobile IoT Android applications. The huge threat posed by malware to communication systems security has made it one of the main focuses of information security research. Therefore, this paper proposes a new graph neural network model based on a network traffic graph for Android malware detection (NT-GNN). While some current malware detection systems use network traffic data for detection, they ignore the complex structural relationships of network traffic, focusing exclusively on network traffic between pairs of endpoints. Additionally, our suggested network traffic graph neural network model (NT-GNN) considers the graph node and edge aspects, capturing the connection between various traffic flows and individual traffic attributes. We first extract the network traffic graph and then detect it using a novel graph neural network architecture. Finally, we experimented with the proposed NT-GNN model on the well-known Android malware CICAndMal2017 and AAGM datasets and achieved 97% accuracy. The results reflect the sophisticated nature of our methodology. Furthermore, we want to provide a new method for malicious code detection.
Frequency Reconfigurable Quad-Element MIMO Antenna with Improved Isolation for 5G Systems
Authors: Singh Ghanshyam , Kumar Sachin , Abrol Ajay , Kanaujia Binod Kumar , Pandey Vijay Kumar , Marey Mohamed , Mostafa Hala
Published: February 2023

In this paper, a frequency reconfigurable multiband multiple-input-multiple-output (MIMO) antenna is developed for 5G communication systems. The presented MIMO antenna element consists of a 50 Ω microstrip line, a rectangular monopole divided into two patches, and a partial ground plane. A split-ring resonator (SRR) is introduced into the upper patch to cover multiple 5G application bands, and an RF PIN diode is embedded between the upper and lower patches to enable the frequency diversity feature. In order to design a MIMO antenna with improved inter-element isolation, four antenna elements are orthogonally located with ground planes connected to each other. The antenna design covers the n41/n46/n48/n79 5G application bands. The prototype MIMO antenna is developed on the FR-4 substrate, and the measured results match with the simulated outcomes. The overall footprint of the prototype antenna is 70 × 70 × 1.6 mm3.
XTM: A Novel Transformer and LSTM-Based Model for Detection and Localization of Formally Verified FDI Attack in Smart Grid
Authors: Baul Anik , Sarker Gobinda Chandra , Sadhu Pintu Kumar , Yanambaka Venkata P. , Abdelgawad Ahmed
Published: February 2023

The modern smart grid (SG) is mainly a cyber-physical system (CPS), combining the traditional power system infrastructure with information technologies. SG is frequently threatened by cyber attacks such as False Data Injection (FDI), which manipulates the states of power systems by adding malicious data. To maintain a reliable and secure operation of the smart grid, it is crucial to detect FDI attacks in the system along with their exact location. The conventional Bad Data Detection (BDD) algorithm cannot detect such stealthy attacks. So, motivated by the most recent deep learning (DL) developments and data-driven solutions, a new transformer-based model named XTM is proposed to detect and identify the exact locations of data intrusions in real-time scenarios. XTM, which combines the transformer and long short-term memory (LSTM), is the first hybrid DL model that explores the performance of transformers in this particular research field. First, a new threshold selection scheme is introduced to detect the presence of FDI, replacing the need for conventional BDD. Then, the exact intrusion point of the attack is located using a multilabel classification approach. A formally verified constraints satisfaction-based attack vector model was used to manipulate the data set. In this work, considering the temporal nature of power system, both hourly and minutely sensor data are used to train and evaluate the proposed model in the IEEE-14 bus system, achieving a detection accuracy of almost 100%. The row accuracy (RACC) metric was also evaluated for the location detection module, with values of 92.99% and 99.99% for the hourly and minutely datasets, respectively. Moreover, the proposed technique was compared with other deep learning models as well, showing that the proposed model outperforms the state-of-the-art methods mentioned in the literature.
Towards Nuts and Bolts of Conducting Literature Review: A Typology of Literature Review
Authors: Taherdoost Hamed
Published: February 2023

Literature reviews demonstrate the progress of knowledge and a comprehensive understanding of related phenomena, contexts, and variables in any subject. Learning how to efficiently conduct a literature review is crucial to succeeding in an academic and even up-to-speed career. Summing up and synthesizing previous research in a particular field of interest indicates enjoying a thorough grasp of the available knowledge. It also lends a hand in learning and moving forward towards being professional in a particular milieu. However, an unorganized growth in literature may hinder amelioration by broaching the probability of complicated, competing, and implausible arguments in the scholarly inquiry. This study is a just-out attempt to develop a typology of review types and present an explanatory insight into the most typical and applicable literature reviews by relying on the aim, significance, applicability, and pros and cons. The goals of conducted typology are to study and analysis different types of literature review to assist researchers to commence their evaluations and place their contribution.