bluuebunny/crossref_metadata_2025 huggingface dataset:
Causes of Intensive Care Unit Admissions in Children with SARS-CoV-2: A Single-Centre Observational Study
Authors: Homola Lukáš , Klučka Jozef , Fabián Dominik , Štourač Petr , Šikula Josef , Vávrová Eva , Jeřábková Barbora , Sihlovec Martin , Musil Václav , Španělová Klára , Mužlayová Patricia , Danhofer Pavlína
Published: January 2023

Background: The proportion of intensive care unit (ICU) admissions in children that have and have not been directly caused by SARS-CoV-2 remains unclear. The aim of the study is to analyse a cohort of children admitted to the ICU with SARS-CoV-2 and determine whether the infection was the primary cause of their hospitalisation, a significant contributor, a suspected accomplice, or an incidental finding. Methods: This was a retrospective observational study of all the children admitted to the ICU with SARS-CoV-2 from March 2020 to February 2022 from the South Moravia region. The aim of the study was to assess whether the hospitalisation was likely to be directly caused by the virus (i.e., patients with acute COVID-19; the COVID group), whether the virus was a significant contributor to the hospitalisation (i.e., patients with multisystem inflammatory syndrome in children due to COVID-19; the MIS-C group), whether it may have contributed to the worsening of their underlying disease (the WORSENING group), or whether it was an incidental finding very likely unrelated to hospitalisation where SARS-CoV-2 positivity merely placed patients in the COVID-19 unit (the ISOLATION group). The groups were compared using a series of secondary outcomes. Results: The study population represented 150 paediatric ICU cases (age 8.6; IQR 3.5–13.3 years), with 66.7% being male. The COVID group represented 32.7% of cases (49/150); MIS-C, 30% (45/150); WORSENING, 14.7% (22/150); and ISOLATION, 22.7% (34/150). The median length of hospitalisation was found for the MIS-C group (11 days; 9 days in the ICU), the COVID group (6 days; five days in the ICU), WORSENING group (4.5 days; 4.5 days in the ICU) and the ISOLATION group (5.5 days; 3.5 days in the ICU), where the difference was significant (p < 0.001). Asymptomatic and mild cases were most common in the WORSENING (36.4% and 63.6%) and ISOLATION (52.9% and 44.1%) groups. Severe and critical cases were only present in the COVID (6.1% and 12.2%) and MIS-C (4.4% and 11.1%) groups; the severity difference was significant (p < 0.001). The groups did not differ significantly in the proportion of complete recovery and short- and long-term sequelae (p = 0.09). Conclusions: Patients with acute COVID-19 accounted for one-third of all ICU admissions, patients with MIS-C accounted for approximately another third, patients with worsening underlying disease accounted for 15%, and patients with incidental findings of SARS-CoV-2 positivity accounted for one-fifth of ICU admissions. A more significant disease was seen with acute COVID-19 and MIS-C.
Food Difficulties in Infancy and ASD: A Literature Review
Authors: Vasilakis Marios , Polychronis Konstantinos , Panagouli Eleni , Tzila Efthalia , Papageorgiou Alexia , Thomaidou Loretta , Psaltopoulou Theodora , Tsolia Maria , Sergentanis Theodoros N. , Tsitsika Artemis K.
Published: January 2023

Purpose: The aim of this literature review is to investigate the potential association between specific food difficulties and autism spectrum disorder (ASD) during the first two years of life. Materials: The search was conducted in PubMed, Google Scholar, Embase and PsycInfo databases. Results: Twenty-one studies were synthesized (3763 infants and children). Difficulties during breastfeeding, breast milk refusal and avoidance of taking solids have been linked to ASD. Infants with ASD have been referred to as picky eaters. Problematic mealtime behaviour during infancy has also been associated with ASD. Conclusions: The present review highlights the association between food difficulties, including problematic mealtime behaviours, food selectivity, breastfeeding difficulties and food refusal during infancy and ASD early during life, including the first months.
Mothers’ Emotion Regulation and Negative Affect in Infants: The Role of Self-Efficacy and Knowledge of Parenting Practices
Authors: Hamzallari Oriola , Rosinski Leanna , Petrenko Anton , Bridgett David J.
Published: January 2023

Early in development, children rely heavily on caregivers for assistance with the regulation of negative emotion. As such, it is important to understand parent characteristics that influence caregiver ability to attenuate infant negative affect and mediating factors by which this process may unfold. This study examined the relationship between parental emotional regulation strategies (ERs) and infants’ negative affect and tested the mediating effects of parenting self-efficacy and knowledge of this association. Results indicated that higher maternal reappraisal was related to higher maternal self-efficacy whereas higher maternal suppression was related to lower knowledge of parenting practices. Maternal suppression was negatively related to infant frustration; maternal self-efficacy was positively related to infant falling reactivity and negatively related to sadness. There was a significant indirect effect between maternal reappraisal and infant falling reactivity through maternal self-efficacy. The mediation result suggests that mothers with higher use of reappraisal show higher self-efficacy and have infants with higher falling reactivity. Maternal knowledge about parenting practices was related to lower infant fear. Maternal knowledge of parenting practices did not mediate any associations between maternal emotion regulation strategies and infant negative affect. These findings contribute to the understanding early protective parenting mechanisms for supporting the external regulation of negative affect in infants and also in designing and implementing preventive parenting programs focused on the emotional needs of parents and children.
Skin Barrier Function and Infant Tidal Flow-Volume Loops—A Population-Based Observational Study
Authors: Färdig Martin , Gudmundsdóttir Hrefna Katrín , Hoyer Angela , Bains Karen Eline Stensby , Almqvist Catarina , Monceyron Jonassen Christine , Rehbinder Eva Maria , Skjerven Håvard O. , Staff Anne Cathrine , Vettukattil Riyas , Söderhäll Cilla , Carlsen Karin C. Lødrup , Nordlund Björn
Published: January 2023

Background: The relationship between the skin barrier- and lung function in infancy is largely unexplored. We aimed to explore if reduced skin barrier function by high transepidermal water loss (TEWL), or manifestations of eczema or Filaggrin (FLG) mutations, were associated with lower lung function in three-month-old infants. Methods: From the population-based PreventADALL cohort, 899 infants with lung function measurements and information on either TEWL, eczema at three months of age and/or FLG mutations were included. Lower lung function by tidal flow-volume loops was defined as a ratio of time to peak tidal expiratory flow to expiratory time (tPTEF/tE) <0.25 and a tPTEF <0.17 s (<25th percentile). A high TEWL >8.83 g/m2/h (>75th percentile) denoted reduced skin barrier function, and DNA was genotyped for FLG mutations (R501X, 2282del4 and R2447X). Results: Neither a high TEWL, nor eczema or FLG mutations, were associated with a lower tPTEF/tE. While a high TEWL was associated with a lower tPTEF; adjusted OR (95% CI) 1.61 (1.08, 2.42), the presence of eczema or FLG mutations were not. Conclusions: Overall, a high TEWL, eczema or FLG mutations were not associated with lower lung function in healthy three-month-old infants. However, an inverse association between high TEWL and tPTEF was observed, indicating a possible link between the skin barrier- and lung function in early infancy.
Management of Choanal Atresia: National Recommendations with a Comprehensive Literature Review
Authors: Urbančič Jure , Vozel Domen , Battelino Saba , Boršoš Imre , Bregant Lev , Glavan Matic , Iglič Črtomir , Jenko Klemen , Lanišnik Boštjan , Soklič Košak Tanja
Published: January 2023

Choanal atresia is the most common congenital anatomical abnormality of the nasal cavities, manifested with a clinical picture of neonatal respiratory distress. The treatment requires interdisciplinary management based mainly on tertiary referral centre experiences. However, there is a lack of high-quality evidence in the available literature. Recommendations were prepared based on a systematic review of the supporting literature: on a website survey addressed to the participating authors consisting of 28 questions and on five live meetings. The initial response to the recommendations was determined at their presentation at the sectional meeting of the section for otorhinolaryngology of the Slovenian Medical Association. Then, reactions from the professional public were accepted until the recommendations were presented at the Expert Council for Otorhinolaryngology of the Slovenian Medical Association. A systematic literature review identified eight systematic reviews or meta-analyses and four randomized controlled clinical trials. Thirty-four recommendations for diagnosis, treatment and postoperative management were consolidated. The paper presents the proposal and first Slovenian recommendations for treating patients with choanal atresia. They are based on foreign medical institutions’ published literature and our clinical experience. They represent the basic requirements of diagnostics and may represent an essential guide in treatment.
Fatigue Prediction Model and Stiffness Modulus for Semi-Flexible Pavement Surfacing Using Irradiated Waste Polyethylene Terephthalate-Based Cement Grouts
Authors: Khan Muhammad Imran , Sutanto Muslich Hartadi , Khahro Shabir Hussain , Zoorob Salah E. , Md. Yusoff Nur Izzi , Al-Sabaeei Abdulnaser M. , Javed Yasir
Published: January 2023

Semi-flexible pavement surfacing, or grouted macadam, is an alternative to conventional flexible and rigid pavement. It is constructed by injecting cementitious grout into the voids of an open-graded asphalt surfacing. The cement used in cementitious grouts has adverse environmental effects because of the carbon dioxide emission in cement production. The objective of this study was to investigate the potential of using irradiated waste polyethylene terephthalate (PET) and fly ash (FA) as a (partial) cement replacement in cementitious grouts for semi-flexible pavement surfacing. This study sought to assess the stiffness modulus and fatigue properties of the semi-flexible specimens prepared with control grout, regular PET (2.57% PET + 10% FA) and irradiated PET (4.75% PET + 10% FA)-based grouts and compares the stiffness modulus and fatigue properties of semi-flexible specimens with the conventional hot mix asphalt (HMA) concrete. The semi-flexible surfacing specimens showed superior performance, higher stiffness modulus, and better fatigue life than the hot mix asphalt. The difference in fatigue cycles was apparent at lower stress ratios of 25 and 30%. The semi-flexible pavement mixtures exceeded 100,000 cycles at the lowest stress ratio of 25%, while the HMA fatigue cycles were less than 100,000 cycles. Furthermore, the semi-flexible specimen with irradiated PET (which contain a higher amount of waste PET than the regular PET) showed similar stiffness modulus and fatigue life as the specimens with regular PET and control grout. The irradiation technique offers a sustainable solution for recycling higher amounts of waste PET in highway materials for semi-flexible pavement surfacing.
Modeling of Quantum Dots with the Finite Element Method
Authors: Mantashian G.A. , Mantashyan P.A. , Hayrapetyan D.B.
Published: January 2023

Considering the increasing number of experimental results in the manufacturing process of quantum dots (QDs) with different geometries, and the fact that most numerical methods that can be used to investigate quantum dots with nontrivial geometries require large computational capacities, the finite element method (FEM) becomes an incredibly attractive tool for modeling semiconductor QDs. In the current article, we used FEM to obtain the first twenty-six probability densities and energy values for the following GaAs structures: rectangular, spherical, cylindrical, ellipsoidal, spheroidal, and conical QDs, as well as quantum rings, nanotadpoles, and nanostars. The results of the numerical calculations were compared with the exact analytical solutions and a good deviation was obtained. The ground-state energy dependence on the element size was obtained to find the optimal parameter for the investigated structures. The abovementioned calculation results were used to obtain valuable insight into the effects of the size quantization’s dependence on the shape of the QDs. Additionally, the wavefunctions and energies of spherical CdSe/CdS quantum dots were obtained while taking into account the diffusion effects on the potential depth with the use of a piecewise Woods–Saxon potential. The diffusion of the effective mass and the dielectric permittivity was obtained with the use of a normal Woods–Saxon potential. A structure with a quasi-type-II band alignment was obtained at the core size of ≈2.2 nm This result is consistent with the experimental data.
Cyclic Voltammetry and Impedance Measurements of Graphene Oxide Thin Films Dip-Coated on n-Type and p-Type Silicon
Authors: Politano Grazia Giuseppina , Burza Stefano , Versace Carlo
Published: January 2023

Despite the increasing interest in graphene, a less studied aspect is the enhancement of silicon (Si) performances due to the interaction with graphene-based materials. In this study, cyclic voltammetry and electric impedance measurements are performed on graphene oxide (GO) dip-coated on n-type and p-type Si samples. The electrical properties of GO on n-type Si samples are dramatically enhanced: The conductivity and the photocurrent meaningfully increase in comparison to bare n-type Si. Such findings could be used in a wide variety of optoelectronic applications, improving GO future applicability in the Si semiconductor industry.
Case Study on the Reproducibility of Characterizing the Electrocatalytic Activity of La1−xSrxMnO3 in ORR
Authors: Gong Minhui
Published: January 2023

The electrocatalytic activity characterization of the oxygen reduction reaction (ORR) is commonly characterized using a rotating disk electrode (RDE) with linear sweep voltammetry (LSV) or cyclic voltammetry (CV) measurements. Despite the wide application of this method in the literature, its reproducibility and comparability are rarely mentioned in articles. LSV and CV are sensitive to experimental conditions, thus the reproducibility is a significant concern. In this article, the perovskite oxides La1−xSrxMnO3 (LSMOx, x = 0, 0.1, 0.2, 0.3, 0.4, 0.5) are chosen for the case study to measure their electroactivity using the RDE method. The main elements that influence the reproducibility of the experiment are presented and the corresponding explanations as well as the means for ensuring the reproducibility are given. Through the case study of LSMOx with variations in x and calcination temperatures, the values for the kinetic current of ORR on different catalysts are compared. It is found that doping ratios above 0.1 are associated with higher ORR electroactivity, with around a 50 mV difference in ORR onset potential between x > 0.1 and x = 0.1, which is in accordance with the results of reported works, whereas there is no significant difference when x = 0.2–0.5. Calcination temperature has little influence on the electroactivity of LSMOx, resulting in only a slight advantage at lower calcination temperatures, with an ORR onset potential that is around 10 mV more positive.
Investigation into the Characteristics of Double-Layer Transparent Conductive Oxide ITO/TNO Anti-Reflection Coating for Silicon Solar Cells
Authors: Lee Yih-Shing , Chuang Li-Yang , Tang Cheng-Jia , Yan Zi-Zhu , Le Bing-Shin , Jaing Cheng-Chung
Published: January 2023

In this study, indium–tin oxide (ITO)/Nb-doping TiO2 (TNO) double-layer transparent conductive oxide (TCO) films deposited using DC magnetron sputtering were used as a surface anti-reflection layer with an overall thickness of 100 nm for double-layer films. The simulated results showed that ITO and TNO thickness combinations of 90 nm/10 nm, 80 nm/20 nm, and 70 nm/30 nm had a higher transmittance and lower reflectance than others in the visible wavelength range. Compared to the single-layer ITO films, for ITO/TNO films deposited on the glass and silicon substrates with an optimum thickness of 80/20 nm, the reflectance was reduced by 5.06% and 4.63%, respectively, at the central wavelength of 550 nm and crystalline silicon photo response wavelength of 900 nm. Moreover, the near-infrared reflectance of the double-layer ITO/TNO with thickness combinations of 90 nm/10 nm, 80 nm/20 nm, and 70 nm/30 nm, when deposited on silicon substrates, was obviously improved by the graded refractive index lamination effect of air (1)/ITO (1.98)/TNO (2.41)/Si (3.9).
UTMInDualSymFi: A Dual-Band Wi-Fi Dataset for Fingerprinting Positioning in Symmetric Indoor Environments
Authors: Abdullah Asim , Haris Muhammad , Aziz Omar Abdul , Rashid Rozeha A. , Abdullah Ahmad Shahidan
Published: January 2023

Recent studies on indoor positioning using Wi-Fi fingerprinting are motivated by the ubiquity of Wi-Fi networks and their promising positioning accuracy. Machine learning algorithms are commonly leveraged in indoor positioning works. The performance of machine learning based solutions are dependent on the availability, volume, quality, and diversity of related data. Several public datasets have been published in order to foster advancements in Wi-Fi based fingerprinting indoor positioning solutions. These datasets, however, lack dual-band Wi-Fi data within symmetric indoor environments. To fill this gap, this research work presents the UTMInDualSymFi dataset, as a source of dual-band Wi-Fi data, acquired within multiple residential buildings with symmetric deployment of access points. UTMInDualSymFi comprises the recorded dual-band raw data, training and test datasets, radio maps and supporting metadata. Additionally, a statistical radio map construction algorithm is presented. Benchmark performance was evaluated by implementing a machine-learning-based positioning algorithm on the dataset. In general, higher accuracy was observed, on the 5 GHz data scenarios. This systematically collected dataset enables the development and validation of future comprehensive solutions, inclusive of novel preprocessing, radio map construction, and positioning algorithms.
The Need for Artificial Intelligence Based Risk Factor Analysis for Age-Related Macular Degeneration: A Review
Authors: Vyas Abhishek , Raman Sundaresan , Surya Janani , Sen Sagnik , Raman Rajiv
Published: January 2023

In epidemiology, a risk factor is a variable associated with increased disease risk. Understanding the role of risk factors is significant for developing a strategy to improve global health. There is strong evidence that risk factors like smoking, alcohol consumption, previous cataract surgery, age, high-density lipoprotein (HDL) cholesterol, BMI, female gender, and focal hyper-pigmentation are independently associated with age-related macular degeneration (AMD). Currently, in the literature, statistical techniques like logistic regression, multivariable logistic regression, etc., are being used to identify AMD risk factors by employing numerical/categorical data. However, artificial intelligence (AI) techniques have not been used so far in the literature for identifying risk factors for AMD. On the other hand, artificial intelligence (AI) based tools can anticipate when a person is at risk of developing chronic diseases like cancer, dementia, asthma, etc., in providing personalized care. AI-based techniques can employ numerical/categorical and/or image data thus resulting in multimodal data analysis, which provides the need for AI-based tools to be used for risk factor analysis in ophthalmology. This review summarizes the statistical techniques used to identify various risk factors and the higher benefits that AI techniques provide for AMD-related disease prediction. Additional studies are required to review different techniques for risk factor identification for other ophthalmic diseases like glaucoma, diabetic macular edema, retinopathy of prematurity, cataract, and diabetic retinopathy.
A Comparative Study of Choroidal Vascular and Structural Characteristics of Typical Polypoidal Choroidal Vasculopathy and Polypoidal Choroidal Neovascularization: OCTA-Based Evaluation of Intervortex Venous Anastomosis
Authors: Batıoğlu Figen , Yanık Özge , Özer Ferhad , Demirel Sibel , Özmert Emin
Published: January 2023

Background: The aim of this study was to compare the choroidal characteristics of typical polypoidal choroidal vasculopathy (T-PCV) and polypoidal choroidal neovascularization (P-CNV) cases, and to investigate the presence of intervortex venous anastomoses in these PCV subtypes by using en face optical coherence tomography angiography (OCTA). Methods: A total of 35 eyes of 33 PCV cases were included. The PCV cases were divided into T-PCV and P-CNV groups. The choroidal vascularity index (CVI) was calculated. En face OCTA images were evaluated for the presence of intervortex venous anastomoses. The diameter of the largest anastomotic Haller vessel was measured. Results: T-PCV cases had significantly higher mean CVI values (73.9 ± 3.7 vs. 70.8 ± 4.5%) than P-CNV cases (p = 0.039). Intervortex venous anastomoses were observed in 85.7% of T-PCV eyes and in 91.7% of P-CNV eyes on en face OCTA (p = 1.000). In the cases with intervortex venous anastomosis, the mean diameter of the largest anastomotic vessel on en face OCTA was 341.2 ± 109.1 µm in the T-PCV and 280.4 ± 68.4 µm in the P-CNV group (p = 0.048). Conclusions: The higher CVI value in T-PCV may be an important feature concerning the pathogenesis and classification of PCV. Although there was no difference between the two subtypes in terms of intervortex anastomosis, more dilated anastomotic vessels were observed in the T-PCV.
PPO-Exp: Keeping Fixed-Wing UAV Formation with Deep Reinforcement Learning
Authors: Xu Dan , Guo Yunxiao , Yu Zhongyi , Wang Zhenfeng , Lan Rongze , Zhao Runhao , Xie Xinjia , Long Han
Published: January 2023

Flocking for fixed-Wing Unmanned Aerial Vehicles (UAVs) is an extremely complex challenge due to fixed-wing UAV’s control problem and the system’s coordinate difficulty. Recently, flocking approaches based on reinforcement learning have attracted attention. However, current methods also require that each UAV makes the decision decentralized, which increases the cost and computation of the whole UAV system. This paper researches a low-cost UAV formation system consisting of one leader (equipped with the intelligence chip) with five followers (without the intelligence chip), and proposes a centralized collision-free formation-keeping method. The communication in the whole process is considered and the protocol is designed by minimizing the communication cost. In addition, an analysis of the Proximal Policy Optimization (PPO) algorithm is provided; the paper derives the estimation error bound, and reveals the relationship between the bound and exploration. To encourage the agent to balance their exploration and estimation error bound, a version of PPO named PPO-Exploration (PPO-Exp) is proposed. It can adjust the clip constraint parameter and make the exploration mechanism more flexible. The results of the experiments show that PPO-Exp performs better than the current algorithms in these tasks.
A Lightweight and Drift-Free Fusion Strategy for Drone Autonomous and Safe Navigation
Authors: Zhang Chi , Yang Zhong , Zhuo Haoze , Liao Luwei , Yang Xin , Zhu Tang , Li Guotao
Published: January 2023

Self-localization and state estimation are crucial capabilities for agile drone autonomous navigation. This article presents a lightweight and drift-free vision-IMU-GNSS tightly coupled multisensor fusion (LDMF) strategy for drones’ autonomous and safe navigation. The drone is carried out with a front-facing camera to create visual geometric constraints and generate a 3D environmental map. Ulteriorly, a GNSS receiver with multiple constellations support is used to continuously provide pseudo-range, Doppler frequency shift and UTC time pulse signals to the drone navigation system. The proposed multisensor fusion strategy leverages the Kanade–Lucas algorithm to track multiple visual features in each input image. The local graph solution is bounded in a restricted sliding window, which can immensely predigest the computational complexity in factor graph optimization procedures. The drone navigation system can achieve camera-rate performance on a small companion computer. We thoroughly experimented with the LDMF system in both simulated and real-world environments, and the results demonstrate dramatic advantages over the state-of-the-art sensor fusion strategies.
CEGH: A Hybrid Model Using CEEMD, Entropy, GRU, and History Attention for Intraday Stock Market Forecasting
Authors: Liu Yijiao , Liu Xinghua , Zhang Yuxin , Li Shuping
Published: January 2023

Intraday stock time series are noisier and more complex than other financial time series with longer time horizons, which makes it challenging to predict. We propose a hybrid CEGH model for intraday stock market forecasting. The CEGH model contains four stages. First, we use complete ensemble empirical mode decomposition (CEEMD) to decompose the original intraday stock market data into different intrinsic mode functions (IMFs). Then, we calculate the approximate entropy (ApEn) values and sample entropy (SampEn) values of each IMF to eliminate noise. After that, we group the retained IMFs into four groups and predict the comprehensive signals of those groups using a feedforward neural network (FNN) or gate recurrent unit with history attention (GRU-HA). Finally, we obtain the final prediction results by integrating the prediction results of each group. The experiments were conducted on the U.S. and China stock markets to evaluate the proposed model. The results demonstrate that the CEGH model improved forecasting performance considerably. The creation of a collaboration between CEEMD, entropy-based denoising, and GRU-HA is our major contribution. This hybrid model could improve the signal-to-noise ratio of stock data and extract global dependence more comprehensively in intraday stock market forecasting.
Thermal Behavior of the Time-Dependent Radiative Flow of Water-Based CNTs/Au Nanoparticles Past a Riga Plate with Entropy Optimization and Multiple Slip Conditions
Authors: Rajupillai K. , Alessa Nazek , Eswaramoorthi S. , Loganathan Karuppusamy
Published: January 2023

This communication deliberates the time-reliant and Darcy–Forchheimer flow of water-based CNTs/gold nanoparticles past a Riga plate. In addition, nonlinear radiation, heat consumption and multiple slip conditions are considered. Entropy generation is computed through various flow parameters. A suitable transformation with symmetry variables is invoked to remodel the governing mathematical flow models into the ODE equations. The homotopy analysis scheme and MATLAB bvp4c method are imposed to solve the reduced ODE equations analytically and numerically. The impact of sundry flow variables on nanofluid velocity, nanofluid temperature, skin friction coefficient, local Nusselt number, entropy profile and Bejan number are computed and analyzed through graphs and tables. It is found that the nanofluid velocity is reduced by greater porosity and slip factors. The thickness of the thermal boundary layer increases with increasing radiation, temperature ratio, and heat consumption/generation parameters. The surface drag force is reduced when there is a higher Forchheimer number, unsteadiness parameter and porosity parameter. The amount of entropy created is proportional to the radiation parameter, porosity parameter and Reynolds number. The Bejan number profile increases with radiation parameter, heat consumption/generation parameter and the Forchheimer number.
HT-Fed-GAN: Federated Generative Model for Decentralized Tabular Data Synthesis
Authors: Duan Shaoming , Liu Chuanyi , Han Peiyi , Jin Xiaopeng , Zhang Xinyi , He Tianyu , Pan Hezhong , Xiang Xiayu
Published: January 2023

In this paper, we study the problem of privacy-preserving data synthesis (PPDS) for tabular data in a distributed multi-party environment. In a decentralized setting, for PPDS, federated generative models with differential privacy are used by the existing methods. Unfortunately, the existing models apply only to images or text data and not to tabular data. Unlike images, tabular data usually consist of mixed data types (discrete and continuous attributes) and real-world datasets with highly imbalanced data distributions. Existing methods hardly model such scenarios due to the multimodal distributions in the decentralized continuous columns and highly imbalanced categorical attributes of the clients. To solve these problems, we propose a federated generative model for decentralized tabular data synthesis (HT-Fed-GAN). There are three important parts of HT-Fed-GAN: the federated variational Bayesian Gaussian mixture model (Fed-VB-GMM), which is designed to solve the problem of multimodal distributions; federated conditional one-hot encoding with conditional sampling for global categorical attribute representation and rebalancing; and a privacy consumption-based federated conditional GAN for privacy-preserving decentralized data modeling. The experimental results on five real-world datasets show that HT-Fed-GAN obtains the best trade-off between the data utility and privacy level. For the data utility, the tables generated by HT-Fed-GAN are the most statistically similar to the original tables and the evaluation scores show that HT-Fed-GAN outperforms the state-of-the-art model in terms of machine learning tasks.
Instructional Design of an Integrative Online Business English Course for Master’s Students of a Technical University
Authors: Varlakova Ekaterina , Bugreeva Elena , Maevskaya Anna , Borisova Yulia
Published: January 2023

The article deals with the instructional design of an integrative Business English course for master’s students of a technical university (a case study of the Saint Petersburg Mining University) for blended and/or flexible learning. The main goal is to design a course that can be used as a full-fledged online course in asynchronous learning and is at the same time adjustable to the existing offline Business English course. The research uses methods such as observation, focus groups, surveying, empirical research and analytical and descriptive methods. The authors see a solution in a special instructional design based on the integration of traditional teaching approaches in offline learning, information technology and elements of infotainment and edutainment. The article presents the results of the target audience analysis and the needs analysis, outlines the structure of the course, specifies approaches to enhance motivation in master’s students and presents an integrative system of assessment and evaluation of the learners’ knowledge and skills. The key features of the instructional design of the Business English course suggested include exposure to professional scenarios, learners’ reflection, multiple instruments encouraging learners’ cognitive activity and performance and an opportunity to apply their knowledge to actual performance rather than summative assessment.
Enhancing Online Instructional Approaches for Sustainable Business Education in the Current and Post-Pandemic Era: An Action Research Study of Student Engagement
Authors: Ng Lui-Kwan , Lo Chung-Kwan
Published: January 2023

The outbreak of the COVID-19 pandemic has pushed traditional classroom instruction to fully online teaching and learning modes. Higher education institutions in China were among the first to shift to these new modalities. The innovative integration of techno-pedagogies with the advancement of information communication technologies and multimedia applications made these rapid changes feasible in practice. However, the shift from traditional to fully online instruction was challenging. Student disengagement and learning performance losses due to these pedagogical changes have impacted the sustainability of educational programmes. We used mixed methods with dual-cycle action research to explore better pedagogical solutions. Seventy-six adult students, three teachers and three teaching assistants were involved in our study. Informed by the results of the first action research cycle, gamification was introduced in the second cycle. The gamified flipped classroom approach in the second action research cycle significantly improved student engagement, and their learning performance was sustained throughout the study. Suggestions for flexibility, all-in-inclusive, coopetitive learning, technical support and sustainable learning (F.A.C.T.S.) are proposed as a practical framework for new techno-pedagogical approaches in the current and post-COVID-19 era.
ENCODE4OpenU and the Preparation and Delivery of an International Collaborative MOOC: A Preliminary Analysis of its Pedagogical and Technical Implementation
Authors: Salvaterra Carla , Bencivenni Alice , Fogagnolo Marta , Gheldof Tom , Vagionakis Irene
Published: January 2023

Among the potential intellectual outputs of the ENCODE project is the production of a MOOC that introduces teaching staff and scientific experts to the digital transition in the field of ancient writing cultures. The basis for this MOOC is the need to foster awareness of the importance of digital competences and to use a structured framework to introduce people to the available innovative teaching and learning materials and opportunities for organizing (self-)training in this field of research. For specialists in the humanities, there is often an unexpected reluctance to go beyond simply using digital tools and to deepen their understanding of the implications of the digital transitions of research fields, as well as considering the readiness of young graduates to acquire digital competences. This MOOC, which is easily accessible, affordable, sustainable, and flexible, may achieve the initial aim of the project, namely, bridging the gap between the highly specialized competences in the humanities and the innovative digital skills needed in open science practices. The main methodological issue concerns the design and adaptation of cooperative tools in order to implement a common pedagogical approach and to produce MOOC content that integrates the different competences and insights of the project participants. This report on the experiment provides useful insights into the differing expectations of academic staff as content producers, issues surrounding MOOC-cooperative design between universities in different countries, the usability of the tested platform and of the different features provided, and sustainability, as guaranteed through the connection with digital infrastructures. In the concluding section, the originality of the MOOC at a more general scale is emphasized. The ways in which the MOOC can facilitate and support the digital transition are assessed according to the FAIR principles in Higher Education Institutions. Moreover, the MOOC offers models for hands-on experiences of digital training and the evaluation of learning outcomes according to shared European frameworks; it demonstrates the importance of being connected with larger projects and digital infrastructures.
Factor Analysis of Students’ Knowledge Assessment Based on the Results of Online Entrance Testing in Mathematics to the University under the Conditions of COVID-19
Authors: Safonova Anastasiia , Guner Mikhail
Published: January 2023

After the COVID-19 pandemic emerged, many educational institutions switched to distance learning, which led to the problem of organizing entrance examinations for universities. When conducting entrance examinations online, applicants have many more opportunities for fraudulent activities (cheating on the exam and using outside help). This article is devoted to the factor analysis of the assessment of students’ knowledge in mathematics enrolled in 2020 at the Altai State Technical University (Barnaul, Russia) based on the results of online entrance testing during the COVID-19 pandemic using an Internet browser and the webcams of applicants. The study used statistical methods, including groupings and comparisons. The analysis revealed that the spread of students’ entrance ratings and their grades at the end of examination sessions in the first year increased by 2.7 times compared to previous years when entrance testing was held offline at the university. Such a large spread can be justified by 37% of the personal problems of applicants (difficulty adapting to the educational process at the university, lack of time, change of interests, etc.) and by 17% of a partial transition to distance learning in the current COVID-19 pandemic. There is a 46% imperfection rate of online testing as a mechanism for competitive selection of applicants. Despite the moderator’s constant control over the progress of testing by monitoring the video from the cameras of applicants, some students probably used outside help in the exam. A correlation analysis showed that the propensity to such behavior is influenced by such characteristics as the age of the applicant, the level of previous education, knowledge of Russian for foreigners, degree of adaptation to life, and education in another country. In addition, the analysis of the correctness of answers to the tasks of the online test made it possible to identify several tasks that can additionally serve as a detector of independence when passing the test, called “traps”.
Mobile Robot Gas Source Localization Using SLAM-GDM with a Graphene-Based Gas Sensor
Authors: Norzam Wan Abdul Syaqur , Hawari Huzein Fahmi , Kamarudin Kamarulzaman , Juffry Zaffry Hadi Mohd , Hussein Nurul Athirah Abu , Gupta Monika , Abdullah Abdulnasser Nabil
Published: January 2023

Mobile olfaction is one of the applications of mobile robots. Metal oxide sensors (MOX) are mobile robots’ most popular gas sensors. However, the sensor has drawbacks, such as high-power consumption, high operating temperature, and long recovery time. This research compares a reduced graphene oxide (RGO) sensor with the traditionally used MOX in a mobile robot. The method uses a map created from simultaneous localization and mapping (SLAM) combined with gas distribution mapping (GDM) to draw the gas distribution in the map and locate the gas source. RGO and MOX are tested in the lab for their response to 100 and 300 ppm ethanol. Both sensors’ response and recovery times show that RGO resulted in 56% and 54% faster response times, with 33% and 57% shorter recovery times than MOX. In the experiment, one gas source, 95% ethanol solution, is placed in the lab, and the mobile robot runs through the map in 7 min and 12 min after the source is set, with five repetitions. The results show the average distance error of the predicted source from the actual location was 19.52 cm and 30.28 cm using MOX and 25.24 cm and 30.60 cm using the RGO gas sensor for the 7th and 12th min trials, respectively. The errors show that the predicted gas source location based on MOX is 1.0% (12th min), much closer to the actual site than that predicted with RGO. However, RGO also shows a larger gas sensing area than MOX by 0.35–8.33% based on the binary image of the SLAM-GDM map, which indicates that RGO is much more sensitive than MOX in the trial run. Regarding power consumption, RGO consumes an average of 294.605 mW, 56.33% less than MOX, with an average consumption of 674.565 mW. The experiment shows that RGO can perform as well as MOX in mobile olfaction applications but with lower power consumption and operating temperature.
Dual Circular Polarization Fabry–Pérot Resonant Antennas Based on Meta-Surface
Authors: Li Jianfeng , Huang Xiaoyan
Published: January 2023

A dual circular polarization Fabry–Pérot resonant antenna is proposed in this paper. The proposed antenna consists of a microstrip antenna radiator and meta-surface. Meta-surface is applied into the design of a Fabry–Pérot (FP) resonant cavity for generating two circularly polarized (CP) beams. When the meta-surface functions as a partially reflecting surface with a top C-gaps array, dielectric substrate with holes periodically arranged around the atoms and bottom metal plate with strip gaps, the proposed design would split an LP wave from the feed into the left-hand CP and right-hand CP waves by rotating the top C-gaps to form prescribed phase gradients. Simulation and measurement results show that the proposed antenna is capable of generating left-hand CP and right-hand CP radiation beams pointing at 18° and −18° at 14.9 GHz with a stable gain of over 22.7 dBic and an aperture efficiency of 25.7%. The proposed technique offers an efficient way to fulfill FP resonant antennas with specific characteristics using meta-surface for more advanced functionalities.
Load Restoration Flexible Optimization in Wind Power Integrated System Based on Conditional Value at Risk
Authors: Chen Rusi , Liu Haiguang , Liu Yan , Han Sicong , Yu Xiaodong
Published: January 2023

In order to better accommodate the uncertainty induced from a high penetration of wind power during load recovery, a method of load restoration flexible optimization is developed in this paper. First, the idea of adopting flexible operational constraints when optimizing schemes is presented so as not to be too conservative in the application of wind power output during restoration. Further, conditional value at risk (CVaR) is employed to define an operational constraint slacking factor (OCSF) through analyzing the extent of constraint exceeding the prescribed limits when wind speed is taking the value outside its confidence interval. Adopting OCSF, a mixed integer linear programming (MILP) model of flexible load restoration, is constructed based on the primary model by substituting adjustable constraints for rigid constraints, which can be solved with CPLEX. Finally, the New England 10-unit 39-bus power system is used to demonstrate the proposed method, and the results explicitly indicate that the amount of load picked up can be effectively increased and an operational security can be guaranteed as well.
Hybrid PDA/FIR Filtering for Indoor Localization Using Wireless Sensor Networks
Authors: Pak Jung Min
Published: January 2023

Indoor localization systems using wireless sensor networks (WSNs) are widely used to track the positions of workers, robots, and equipment. In indoor spaces, the occasional obstruction of radio propagation by physical objects such as furniture, appliances, and humans is referred to as the non-line-of-sight (NLOS) problem and has been a challenge for indoor localization. In this study, a new indoor localization algorithm to overcome the NLOS problem is proposed. We propose a new method to use redundant fixed nodes and nearest neighbor (NN) measurements, which increases the probability of avoiding NLOS-contaminated measurements. In addition, we propose a novel localization algorithm that can handle the contaminated measurements as clutters. The proposed algorithm is based on the hybrid filtering structure in which probabilistic data association (PDA) filter and a finite impulse response (FIR) filter are used as main and assisting filters, respectively. We adopt the extended minimum variance FIR (EMVF) filter as an assisting FIR filter, which recovers the main PDA filter from failures. Thus, the resulting filter is referred to as hybrid PDA/FIR filter (HPFF). Extensive simulations using an indoor localization scenario in a long corridor were performed for evaluation of the proposed localization algorithm. The EKF using NN measurements improves localization accuracy under temporary NLOS conditions, and the PDA filter further enhances the localization accuracy of EKF. However, EKF and PDA filter cannot completely overcome NLOS problem and exhibit significant increase in errors under certain conditions. The HPFF produced localization accuracy with the root time-averaged mean square (RTAMS) position error under 0.4 m and did not fail under NLOS conditions. The accurate and reliable localization performance of HPFF was demonstrated in comparison with the EKF and PDA filter through extensive WSN-based indoor localization simulations.
FPGA-Based High-Throughput Key-Value Store Using Hashing and B-Tree for Securities Trading System
Authors: Puranik Sunil , Barve Mahesh , Rodi Swapnil , Patrikar Rajendra
Published: January 2023

Field-Programmable Array (FPGA) technology is extensively used in Finance. This paper describes a high-throughput key-value store (KVS) for securities trading system applications using an FPGA. The design uses a combination of hashing and B-Tree techniques and supports a large number of keys (40 million) as required by the Trading System. We have used a novel technique of using buckets of different capacities to reduce the amount of Block-RAM (BRAM) and perform a high-speed lookup. The design uses high-bandwidth-memory (HBM), an On-chip memory available in Virtex Ultrascale+ FPGAs to support a large number of keys. Another feature of this design is the replication of the database and lookup logic to increase the overall throughput. By implementing multiple lookup engines in parallel and replicating the database, we could achieve high throughput (up to 6.32 million search operations/second) as specified by our client, which is a major stock exchange. The design has been implemented with a combination of Verilog and high-level-synthesis (HLS) flow to reduce the implementation time.
A Clutter Loss Model for Satellite Communication Systems
Authors: Riva Carlo G. , Luini Lorenzo , Panzeri Alberto , Morandi Filippo , Resteghini Laura , De Donno Danilo , Mazzucco Christian , Lombardi Renato
Published: January 2023

Buildings and vegetation in the proximity of a terrestrial base station induce a significant additional loss, typically referred to as “clutter loss”, which sums up to free space loss and atmospheric attenuation. Clutter loss is essentially due to the radiowave reflection and diffraction caused by buildings and vegetation, and tends to reduce the interference between terrestrial systems, such as upper 6 GHz (U6G), and satellite systems operating in the same frequency bands. In fact, for example, at low elevation angles, the clutter loss could reach some tens of dB in the U6G band. A novel clutter loss model in urban and suburban environments for frequencies up to 10 GHz is proposed. The model relies on the Monte Carlo simulation approach presented in Report ITU-R P.2402-0, but some limitations have been removed to extend its applicability to more complex scenarios and possibly increase its accuracy for U6G systems. An analytical approach is also proposed to model the clutter loss statistics obtained by properly fitting the obtained statistics for the cities of London and Melbourne. Finally, the proposed model is validated by comparing its results to those obtained by a commercial ray tracer.
CRLB Analysis for Passive Sensor Network Localization Using Intelligent Reconfigurable Surface and Phase Modulation
Authors: Liu Dunge , Chen Song , Lu Ziyang , Jin Shichao , Zhao Yubin
Published: January 2023

Passive wireless sensor network (PWSN) requires high positioning for network management. The harvested energy of the passive sensor is modulated as the ranging data and the position is derived accordingly. Thus, the wireless power transfer (WPT) is a dominant factor for such localization. With the help of intelligent reconfigurable surface (IRS), the WPT efficiency can be significantly improved. In this paper, we propose the Fisher information matrix (FIM) and the Cramér–Rao lower bound (CRLB) analyzing model of the PWSN localization. We prove the impacts of phase modulation of IRS on the localization performance. Based on our analysis, we develop an approximation algorithm and a genetic algorithm to control the IRS phases. Then, the localization accuracy of PWSN can be further improved. The simulation results demonstrate that the phase modulation based on GA can achieve high accurate localization for PWSN using IRS.