bluuebunny/crossref_metadata_2025 huggingface dataset:
Can AI Help Pediatricians? Diagnosing Kawasaki Disease Using DRSA
Authors: Siewert Bartosz , Błaszczyński Jerzy , Gowin Ewelina , Słowiński Roman , Wysocki Jacek
Published: October 2021

The DRSA method (dominance-based rough set approach) was used to create decision-making rules based on the results of physical examination and additional laboratory tests in the differential diagnosis of Kawasaki disease (KD), infectious mononucleosis and S. pyogenes pharyngitis in children. The study was conducted retrospectively. The search was based on the ICD-10 (International Classification of Diseases) codes of final diagnosis. Demographic and laboratory data from one Polish hospital (Poznan) were collected. Traditional statistical methods and the DRSA method were applied in data analysis. The algorithm formed 45 decision rules recognizing KD. The rules with the highest sensitivity (number of false negatives equals zero) were based on the presence of conjunctivitis and CRP (C-reactive Protein) ≥ 40.1 mg/L, thrombocytosis and ESR (Erythrocyte Sedimentation Rate) ≥ 77 mm/h; fair general condition and fever ≥ 5 days and rash; fair general condition and fever ≥ 5 days and conjunctivitis; fever ≥ 5 days and rash and CRP ≥ 7.05 mg/L. The DRSA analysis may be helpful in diagnosing KD at an early stage of the disease. It can be used even with a small amount of clinical or laboratory data.
Melioration of Electrical and Optical Properties of Al and B Co-Doped ZnO Transparent Semiconductor Thin Films
Authors: Tsay Chien-Yie , Yu Shih-Hsun
Published: October 2021

Undoped, Al-doped and Al-B co-doped ZnO transparent semiconductor thin films were deposited on glass substrates by sol-gel method and spin coating technique. This study investigated the influence of Al (2 at.%) doping and Al (2 at.%)-B (1 or 2 at.%) co-doping on the microstructural, surface morphological, electrical and optical properties of the ZnO-based thin films. XRD analysis indicated that all as-prepared ZnO-based thin films were polycrystalline with a single-phase hexagonal wurtzite structure. The substitution of extrinsic dopants (Al or Al-B) into ZnO thin films can significantly degrade the crystallinity, refine the microstructures, improve surface flatness, enhance the optical transparency in the visible spectrum and lead to a shift in the absorption edge toward the short-wavelength direction. Experimental results showed that the Al-doped and Al-B co-doped ZnO thin films exhibited high average transmittance (>91.3%) and low average reflectance (<10%) in the visible region compared with the ZnO thin film. The optical parameters, including the optical bandgap, Urbach energy, extinction coefficient and refractive index, changed with the extrinsic doping level. Measured results of electrical properties revealed that the singly doped and co-doped samples exhibited higher electron concentrations and lower resistivities than those of the undoped sample and suggested that 2 at.% Al and 1 at.% B were the optimum dopant concentrations for achieving the best electrical properties in this study.
Understanding the Relations between Surface Stress State and Microstructure Feature for Enhancing the Fatigue Performance of TC6 Titanium Alloy
Authors: Shu Song , Huang Xin , Cheng Zonghui , Shen Yizhou , He Zhaoru , Liu Weilan
Published: October 2021

Fatigue performance has always been an important factor affecting the application of titanium alloy. The service life of TC6 titanium alloy is easily reduced under a continuously alternating load. Therefore, there is an urgent need for a new method to improve fatigue performance. Laser shock peening (LSP) is a widely proposed method to enhance the fatigue performance. Here, through experiments and finite element simulations, it was found that LSP can prolong the fatigue life of TC6 by improving the surface stress state. In strengthening processes, the generation of residual stress was mainly attributed to the change of microstructure, which could be reflected by the statistical results of grain sizes. The content of grains with a size under 0.8 μm reached 78%, and the microhardness value of treated TC6 was 18.7% higher than that of an untreated sample. In addition, the surface residual compressive stress was increased to −600 MPa at the depth of 1500 μm from the surface. On this basis, the fatigue life was prolonged to 135%, and the ultimate fracture macroscopic was also changed. With the treatment of LSP, the fatigue performance of TC6 is highly promoted. The strengthening mechanism of LSP was established with the aim of revealing the relationship between microstructure and stress state for enhancing the fatigue performance in whatever shapes.
Prediction of Dissolved Impurities and Movement of Oxide Particles in the Primary Circuit of LBE Fast Reactor
Authors: Wu Jiewei , Wu Rongjun , Wang Yuqing , He Jianbo , Hu Chen , Zeng Xian , Ni Muyi
Published: October 2021

To better understand the corrosion and corrosion products behavior in the primary circuit of lead-bismuth eutectic (LBE) coolant reactor, the concentration distribution of soluble impurities and the transport of solid particles are investigated through the finite-element method. An axisymmetric model of the primary circuit of an LBE reactor was constructed to accelerate the calculation of the thermal hydraulic filed of the circuit. The saturation concentration of solute Fe, Cr and Ni in LBE coolant are identified through the equilibrium of their oxides and PbO, and the very different saturation concentrations of Fe/Cr/Ni in LBE will lead to significant element-selective corrosion. The migration of solid oxide particles in the primary circuit is also investigated by the Euler–Lagrange tracing model. The simulation shows that driving force for the movement of particles >100 μm is buoyancy, which lets particles float on a free surface, while particles <10 μm tend to suspend in coolant. However, the behavior of particles also depends on the formation position, the particles formed above the core have a high possibility of re-entering in the core.
Microfabrication of VO2 Thin Films via a Photosensitive Sol-Gel Method
Authors: Wu Chuanbao , Wang Yunwei , Ma Guangqiang
Published: October 2021

VO2 films are widely used in photoelectric switches, smart glasses, storage media, and terahertz communications. In these applications, microfabrication technology is a very important process for producing microdevices or even improving film properties. In this paper, a novel photoetching microfabrication method is proposed for VO2 thin films. First, a VO2 precursor sol with ultraviolet photosensitivity was prepared using vanadyl acetylacetonate as the raw material and anhydrous methanol as the solvent. The dip-coated VO2 gel film can be directly subjected to photolithography processing without coating additional photoresist by using the photosensitive sol. A fine pattern on the VO2 film with good phase-transition performance can be obtained after annealing in a nitrogen atmosphere at 550 °C for 1 h. This method can be used to prepare grating, microarray, and various other fine patterns with the remarkable advantages of a low cost and simplified process, and the as-obtained material performances are unaffected using the method. It is a potential alternative method for optics, electronics, and magnetics devices based on VO2 thin films.
Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case
Authors: Palaiokrassas Georgios , Skoufis Petros , Voutyras Orfefs , Kawasaki Takafumi , Gallissot Mathieu , Azzabi Radhouene , Tsuge Akira , Litke Antonios , Okoshi Tadashi , Nakazawa Jin , Varvarigou Theodora
Published: October 2021

In this paper, we demonstrate the multiple points of innovation when combining blockchain technology with Internet of Things (IoT) and security frameworks. The deployment and use of IoT device networks in smart city environments has produced an enormous amount of data. The fact that those data are possessed by multiple sources that use independent systems for data collection, storage, and use impedes the exploitation of their value. Blockchains, as distributed ledgers, can be used for addressing the development of a universal system for data collection and distribution. Smart contracts can be used to automate all the processes of such a network, while at the same time, blockchain and the InterPlanetary File System (IPFS) protect sensitive data through anonymity and distributed storage. An innovative and open IoT blockchain market of applications, data, and services is proposed that: (i) provides the framework upon which objects and people can exchange value in form of virtual currencies, for assets (data and services) received; (ii) defines the motivation incentives according to social and business context for humans and smart objects to interact. The specific marketplace is piloted through a cross-border trial between Santander and Fujisawa, in the context of the M-Sec project, validating thus the interoperability, efficiency, and data protection principles.
Ab initio Investigation of Impurity Ferromagnetism in the Pd1−xFex Alloys: Concentration and Position Dependences
Authors: Piyanzina Irina , Gumarov Amir , Khaibullin Rustam , Tagirov Lenar
Published: October 2021

We present the results of ab initio studies of the structural and magnetic properties of the Pd host matrix doped by Fe atoms at various concentrations. By means of the density functional theory, we deduce that iron impurities are able to initialize significant magnetization of the Pd atoms, when the impurity concentration exceeds 3 at.%. We also demonstrate that the induced magnetization depends on impurity positions in the host matrix, in particular, there is a maximum of magnetization for a uniform distribution of the iron solute.
X-ray Spectrum Reconstruction by Diamond Detectors with Linear Response to Dose Rate
Authors: Trucchi Daniele , Ascarelli Paolo
Published: October 2021

The absorbers method is here applied by interposing filters of variable thickness between the X-ray source and a detector so to attenuate the radiation intensity by using the attenuation coefficient as a selective photon energy operator. The analysis of the signal provided by a polycrystalline diamond thin film detector exposed to the energy-selectively-attenuated X-ray beam was used for the reconstruction of the radiation spectrum. The 50 μm thick diamond detector achieves conditions of linear response to the dose rate of the incident radiation (linearity coefficient of 0.997 ± 0.003) for a bias voltage ≥90 V, corresponding to an electric field ≥1.8 × 104 V/cm. Once the absorbers method is applied, only the detector signal linearity to dose rate allows reconstructing the source X-ray bremsstrahlung spectrum with sufficiently high accuracy.
Kappa Carbide Precipitation in Duplex Fe-Al-Mn-Ni-C Low-Density Steel
Authors: Burja Jaka , Šetina Batič Barbara , Balaško Tilen
Published: October 2021

The microstructural evolution of a Fe-Mn-Al-Ni-C low-density steel was studied. The lightweight low-density steels are a promising material for the transportation industry, due to their good mechanical properties and low density. The base microstructure of the investigated steel consists of ferrite and austenite. Thermo-Calc calculations showed the formation of an ordered BCC (body-centred cubic) B2 phase below 1181 °C and kappa carbides below 864 °C. The steel was produced in a vacuum induction furnace, cast into ingots and hot forged into bars. The forged bars were solution annealed and then isothermally annealed at 350, 450, 550, 650, 750, and 850 °C. The microstructure of the as-cast state, the hot forged state, solution annealed, and isothermally annealed were investigated by optical microscopy and scanning electron microscopy. The results showed the formation of kappa carbides and the ordered B2 phase. The kappa carbides appeared in the as-cast sample and at the grain boundaries of the isothermally annealed samples. At 550 °C, the kappa carbides began to form in the austenite phase and coarsened with increasing temperature.
Structural and Biochemical Studies of Bacillus subtilis MobB
Authors: Kim Dajeong , Choi Sarah , Kim Hyunjin , Choe Jungwoo
Published: October 2021

The biosynthesis of molybdenum cofactor for redox enzymes is carried out by multiple enzymes in bacteria including MobA and MobB. MobA is known to catalyze the attachment of GMP to molybdopterin to form molybdopterin guanine dinucleotide. MobB is a GTP binding protein that enhances the activity of MobA by forming the MobA:MobB complex. However, the mechanism of activity enhancement by MobB is not well understood. The structure of Bacillus subtilis MobB was determined to 2.4 Å resolution and it showed an elongated homodimer with an extended β-sheet. Bound sulfate ions were observed in the Walker A motifs, indicating a possible phosphate-binding site for GTP molecules. The binding assay showed that the affinity between B. subtilis MobA and MobB increased in the presence of GTP, suggesting a possible role of MobB as an enhancer of MobA activity.
Single-Center Comparison of [64Cu]-DOTAGA-PSMA and [18F]-PSMA PET–CT for Imaging Prostate Cancer
Authors: Mirzaei Siroos , Lipp Rainer , Zandieh Shahin , Leisser Asha
Published: October 2021

Introduction: the diagnostic performance of [64Cu]-DOTAGA-PSMA PET–CT imaging was compared retrospectively to [18F]-PSMA PET–CT in prostate cancer patients with recurrent disease and in the primary staging of selected patients with advanced local and possible metastatic disease. Methods: We retrospectively selected a total of 100 patients, who were consecutively examined in our department, with biochemical recurrence after radical prostatectomy or who had progressive local and possible metastatic disease in the last 3 months prior to this investigation. All patients were examined with a dedicated PET–CT scanner (Biograph; Siemens Healthineers). A total of 250 MBq (3.5 MBq per kg bodyweight, range 230–290 MBq) of [64Cu]-DOTAGA-PSMA or [18-F]-PSMA was applied intravenously. PET images were performed 1 h post-injection (skull base to mid-thigh). The maximum standardized uptake values (SUVmax) of PSMA-positive lesions and the mean standardized uptake value (SUVmean) of the right liver lobe were measured. Results: All but 9/50 of the patients (18%; PSA range: 0.01–0.7 µg/L) studied with [64Cu]-DOTAGA-PSMA and 6/50 of the ones (12%; PSA range: 0.01–4.2) studied with [18F]-PSMA had at least one positive PSMA lesion shown by PET–CT. The total number of lesions was higher with [64Cu]-DOTAGA-PSMA (209 vs. 191); however, the median number of lesions was one for [64Cu]-DOTAGA-PSMA and two for [18F]-PSMA. Interestingly, the median SUVmean of the right liver lobe was slightly higher for [18F]-PSMA (11.8 vs. 8.9). Conclusions: [64Cu]-DOTAGA-PSMA and [18F]-PSMA have comparable detection rates for the assessment of residual disease in patients with recurrent or primary progressive prostate cancer. The uptake in the liver is moderately different, and therefore at least the SUVs of the lesions in both studies would not be comparable.
At the Heart of It All: Emotions of Consequence for the Conceptualization of Caregiver-Reported Outcomes in the Context of Colorectal Cancer
Authors: Howard A. Fuchsia , Lynch Kelsey , Beck Scott , Torrejón Maria-José , Avery Jonathan , Thorne Sally , Porcino Antony , De Vera Mary , Lambert Leah , Wolff Angela , McDonald Melanie , Lee Joyce , Hedges Penelope , McKenzie Michael
Published: October 2021

Colorectal cancer (CRC) can be demanding for primary caregivers; yet, there is insufficient evidence describing the caregiver-reported outcomes (CROs) that matter most to caregivers. CROs refer to caregivers’ assessments of their own health status as a result of supporting a patient. The study purpose was to describe the emotions that were most impactful to caregivers of patients with CRC, and how the importance caregivers attribute to these emotions changed from diagnosis throughout treatment. Guided by qualitative Interpretive Description, we analyzed 25 caregiver and 37 CRC patient interviews, either as individuals or as caregiver-patient dyads (six interviews), using inductive coding and constant comparative techniques. We found that the emotional aspect of caring for a patient with CRC was at the heart of caregiving. Caregiver experiences that engendered emotions of consequence included: (1) facing the patient’s life-changing diagnosis and an uncertain future, (2) needing to be with the patient throughout the never-ending nightmare of treatment, (3) bearing witness to patient suffering, (4) being worn down by unrelenting caregiver responsibilities, (5) navigating their relationship, and (6) enduring unwanted change. The broad range of emotions important to caregivers contributes to comprehensive foundational evidence for future conceptualization and the use of CROs.
Species Diversity and Community Assembly of Cladocera in the Sand Ponds of the Ulan Buh Desert, Inner Mongolia of China
Authors: Gu Yang-Liang , Huang Qi , Xu Lei , Rizo Eric Zeus , Alonso Miguel , Dumont Henri J. , Han Bo-Ping
Published: October 2021

In deserts, pond cladocerans suffer harsh conditions like low and erratic rainfall, high evaporation, and highly variable salinity, and they have limited species richness. The limited species can take advantage of ephippia or resting eggs for being dispersed with winds in such habitats. Thus, environmental selection is assumed to play a major role in community assembly, especially at a fine spatial scale. Located in Inner Mongolia, the Ulan Buh desert has plenty of temporary water bodies and a few permanent lakes filled by groundwater. To determine species diversity and the role of environmental selection in community assembly in such a harsh environment, we sampled 37 sand ponds in June 2012. Fourteen species of Cladocera were found in total, including six pelagic species, eight littoral species, and two benthic species. These cladocerans were mainly temperate and cosmopolitan fauna. Our classification and regression tree model showed that conductivity, dissolved oxygen, and pH were the main factors correlated with species richness in the sand ponds. Spatial analysis using a PCNM model demonstrated a broad-scale spatial structure in the cladoceran communities. Conductivity was the most significant environmental variable explaining cladoceran community variation. Two species, Moina cf. brachiata and Ceriodaphnia reticulata occurred commonly, with an overlap at intermediate conductivity. Our results, therefore, support that environmental selection plays a major role in structuring cladoceran communities in deserts.
The Hidden Wood-Decaying Fungal Diversity: Rhizochaete from East Asia
Authors: Gu Zi-Rui , Zhao Chang-Lin
Published: October 2021

Wood-decaying fungi play crucial roles as decomposers in forest ecosystems. In this study, two new corticioid fungi, Rhizochaete fissurata and R. grandinosa spp. nov., are proposed based on a combination of morphological features and molecular evidence. Rhizochaete fissurata is characterized by resupinate basidiomata with a cracking hymenial surface, a monomitic hyphal system with simple-septa generative hyphae, presence of subfusiform to conical cystidia encrusted at the apex or coarse on the upper half, and ellipsoid basidiospores. Rhizochaete grandinosa differs in its resupinate basidiomata with a smooth hymenial surface, presence of two types of cystidia, and ellipsoid basidiospores. Sequences of ITS and nLSU rRNA markers of the studied samples were employed, and phylogenetic analyses were performed with maximum likelihood, maximum parsimony, and Bayesian inference methods on two datasets (ITS+nLSU and ITS). Both dataset analyses showed that two new species clustered into the genus Rhizochaete, in which, based on the ITS+nLSU dataset, R. fissurata was sister to R. belizensis, and R. grandinosa grouped with R. radicata; the phylogram inferred from ITS sequences inside Rhizochaete indicated that R. fissurata formed a monophyletic lineage with a lower support; R. grandinosa grouped closely with R. radicata. In addition, an identification key to all Rhizochaete species worldwide is provided.
Machine Learning-Based Three-Month Outcome Prediction in Acute Ischemic Stroke: A Single Cerebrovascular-Specialty Hospital Study in South Korea
Authors: Park Dougho , Jeong Eunhwan , Kim Haejong , Pyun Hae Wook , Kim Haemin , Choi Yeon-Ju , Kim Youngsoo , Jin Suntak , Hong Daeyoung , Lee Dong Woo , Lee Su Yun , Kim Mun-Chul
Published: October 2021

Background: Functional outcomes after acute ischemic stroke are of great concern to patients and their families, as well as physicians and surgeons who make the clinical decisions. We developed machine learning (ML)-based functional outcome prediction models in acute ischemic stroke. Methods: This retrospective study used a prospective cohort database. A total of 1066 patients with acute ischemic stroke between January 2019 and March 2021 were included. Variables such as demographic factors, stroke-related factors, laboratory findings, and comorbidities were utilized at the time of admission. Five ML algorithms were applied to predict a favorable functional outcome (modified Rankin Scale 0 or 1) at 3 months after stroke onset. Results: Regularized logistic regression showed the best performance with an area under the receiver operating characteristic curve (AUC) of 0.86. Support vector machines represented the second-highest AUC of 0.85 with the highest F1-score of 0.86, and finally, all ML models applied achieved an AUC > 0.8. The National Institute of Health Stroke Scale at admission and age were consistently the top two important variables for generalized logistic regression, random forest, and extreme gradient boosting models. Conclusions: ML-based functional outcome prediction models for acute ischemic stroke were validated and proven to be readily applicable and useful.
Comprehensive Molecular Analysis of DMD Gene Increases the Diagnostic Value of Dystrophinopathies: A Pilot Study in a Southern Italy Cohort of Patients
Authors: De Palma Fatima Domenica Elisa , Nunziato Marcella , D’Argenio Valeria , Savarese Maria , Esposito Gabriella , Salvatore Francesco
Published: October 2021

Duchenne/Becker muscular dystrophy (DMD/BMD) is an X-linked neuromuscular disease due to pathogenic sequence variations in the dystrophin (DMD) gene, one of the largest human genes. More than 70% of DMD gene defects result from genomic rearrangements principally leading to large deletions, while the remaining are small nucleotide variants, including nonsense and missense variants, small insertions/deletions or splicing alterations. Considering the large size of the gene and the wide mutational spectrum, the comprehensive molecular diagnosis of DMD/BMD is complex and may require several laboratory methods, thus increasing the time and costs of the analysis. In an attempt to simplify DMD/BMD molecular diagnosis workflow, we tested an NGS method suitable for the detection of all the different types of genomic variations that may affect the DMD gene. Forty previously analyzed patients were enrolled in this study and re-analyzed using the next generation sequencing (NGS)-based single-step procedure. The NGS results were compared with those from multiplex ligation-dependent probe amplification (MLPA)/multiplex PCR and/or Sanger sequencing. Most of the previously identified deleted/duplicated exons and point mutations were confirmed by NGS and 1 more pathogenic point mutation (a nonsense variant) was identified. Our results show that this NGS-based strategy overcomes limitations of traditionally used methods and is easily transferable to routine diagnostic procedures, thereby increasing the diagnostic power of DMD molecular analysis.
Deep Semi-Supervised Algorithm for Learning Cluster-Oriented Representations of Medical Images Using Partially Observable DICOM Tags and Images
Authors: Manojlović Teo , Štajduhar Ivan
Published: October 2021

The task of automatically extracting large homogeneous datasets of medical images based on detailed criteria and/or semantic similarity can be challenging because the acquisition and storage of medical images in clinical practice is not fully standardised and can be prone to errors, which are often made unintentionally by medical professionals during manual input. In this paper, we propose an algorithm for learning cluster-oriented representations of medical images by fusing images with partially observable DICOM tags. Pairwise relations are modelled by thresholding the Gower distance measure which is calculated using eight DICOM tags. We trained the models using 30,000 images, and we tested them using a disjoint test set consisting of 8000 images, gathered retrospectively from the PACS repository of the Clinical Hospital Centre Rijeka in 2017. We compare our method against the standard and deep unsupervised clustering algorithms, as well as the popular semi-supervised algorithms combined with the most commonly used feature descriptors. Our model achieves an NMI score of 0.584 with respect to the anatomic region, and an NMI score of 0.793 with respect to the modality. The results suggest that DICOM data can be used to generate pairwise constraints that can help improve medical images clustering, even when using only a small number of constraints.
Coronary-Pulmonary Artery Fistula Recanalization on Coronary Computed Tomography Angiography Images
Authors: Gać Paweł , Martuszewski Adrian , Paluszkiewicz Patrycja , Poręba Rafał
Published: October 2021

Coronary computed tomography angiography (CCTA) is a non-invasive diagnostic method used (apart from the diagnosis of coronary artery disease) in the diagnosis of malformations of the coronary circulation and monitoring the effects of their treatment. In this paper, the authors present the case of recanalization of the coronary-pulmonary fistula, which was surgically closed in the past. This case highlights that follow-up CCTA after surgical treatment of coronary artery fistula should be performed in every patient. The recommendations regarding the frequency of such follow-up should be made.
A Promising and Challenging Approach: Radiologists’ Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19
Authors: Wang Tianming , Chen Zhu , Shang Quanliang , Ma Cong , Chen Xiangyu , Xiao Enhua
Published: October 2021

Chest X-rays (CXR) and computed tomography (CT) are the main medical imaging modalities used against the increased worldwide spread of the 2019 coronavirus disease (COVID-19) epidemic. Machine learning (ML) and artificial intelligence (AI) technology, based on medical imaging fully extracting and utilizing the hidden information in massive medical imaging data, have been used in COVID-19 research of disease diagnosis and classification, treatment decision-making, efficacy evaluation, and prognosis prediction. This review article describes the extensive research of medical image-based ML and AI methods in preventing and controlling COVID-19, and summarizes their characteristics, differences, and significance in terms of application direction, image collection, and algorithm improvement, from the perspective of radiologists. The limitations and challenges faced by these systems and technologies, such as generalization and robustness, are discussed to indicate future research directions.
Survey about the Quality of Life of Italian Patients with Fabry Disease
Authors: Polistena Barbara , Rigante Donato , Sicignano Ludovico Luca , Verrecchia Elena , Manna Raffaele , d’Angela Daniela , Spandonaro Federico
Published: October 2021

Fabry disease (FD) is a genetic disease included in the group of lysosomal storage disorders, caused by X-linked deficiency of the enzyme alpha-galactosidase A. The aim of this study was to evaluate different aspects related to the quality of life (QoL) of a multicentre cohort of Italian patients with FD. An observational survey was conducted to measure health-related quality of life (HR-QoL) in FD patients using the CAPI (Computer-Assisted Personal Interview) method: 106 patients (mostly women) responded to the questionnaire. Geographically, 53.7% of patients lived in northern Italy, 18.9% in central Italy and 27.4% in southern Italy or the Islands. All data were collected through a five-dimensional EuroQoL questionnaire referring to functional aspects (mobility, personal care, routine activities) and perception of physical/mental well-being (pain or discomfort, anxiety or depression). A descriptive analysis of responses was performed; FD patients were compared in terms of QoL with subjects suffering from other chronic diseases, such as Crohn’s disease, chronic hepatitis, cirrhosis and multiple sclerosis. Difficulty in normal daily activities was reported by 47.2% of FD patients. About one third of subjects also had mobility difficulties. Feelings of loneliness and isolation were reported by 33.3% of those being 60–69 years old. Anxiety was equally reported in both oldest and youngest patients (66.7%), while depression, relational problems, fear of other people’s judgement increased along with age, reaching 66.7% in the over-70-years group. Male patients were largely troubled about the risk of physical disability, particularly those aged 60 years or over. Furthermore, FD patients had a poorer QoL than people suffering from other chronic inflammatory disorders. Our study upholds that FD patients have a poor QoL, as already known, negatively impacting psychic well-being and social activities. Our survey has also found a worse QoL in FD patients compared with other severe chronic disorders.
Minimum Entropy Production Effect on a Quantum Scale
Authors: Márkus Ferenc , Gambár Katalin
Published: October 2021

The discovery of quantized electric conductance by the group of van Wees in 1988 was a major breakthrough in physics. A decade later, the group of Schwab has proven the existence of quantized thermal conductance. Advancing from these and many other aspects of the quantized conductances in other phenomena of nature, the concept of quantized entropy current can be established and it eases the description of a transferred quantized energy package. This might yield a universal transport behavior of the microscopic world. During the transfer of a single energy quantum, hν, between two neighboring domains, the minimum entropy increment is calculated. It is pointed out that the possible existence of the minimal entropy transfer can be formulated. Moreover, as a new result, it is proved that this minimal entropy transfer principle is equivalent to the Lagrangian description of thermodynamics.
A General Rate-Distortion Optimization Method for Block Compressed Sensing of Images
Authors: Chen Qunlin , Chen Derong , Gong Jiulu
Published: October 2021

Block compressed sensing (BCS) is a promising technology for image sampling and compression for resource-constrained applications, but it needs to balance the sampling rate and quantization bit-depth for a bit-rate constraint. In this paper, we summarize the commonly used CS quantization frameworks into a unified framework, and a new bit-rate model and a model of the optimal bit-depth are proposed for the unified CS framework. The proposed bit-rate model reveals the relationship between the bit-rate, sampling rate, and bit-depth based on the information entropy of generalized Gaussian distribution. The optimal bit-depth model can predict the optimal bit-depth of CS measurements at a given bit-rate. Then, we propose a general algorithm for choosing sampling rate and bit-depth based on the proposed models. Experimental results show that the proposed algorithm achieves near-optimal rate-distortion performance for the uniform quantization framework and predictive quantization framework in BCS.
The Effect of Distance Teaching Experiences on Educators’ Attitudes toward Distance Education for Preschoolers
Authors: Veraksa Alexander , Chursina Apollinaria , Gavrilova Margarita
Published: October 2021

The aim of the study was to explore and highlight the challenges and benefits of distance education that educators found in their practice of online teaching with preschool children during the first wave of the pandemic. An electronic questionnaire was used to collect teachers’ perceptions of (1) their own success in facilitating online sessions; (2) attitudes towards online sessions among teachers with and without experience; (3) factors that, according to teachers with and without experience, determine the effectiveness of online sessions; (4) effectiveness of online sessions for individual mental development goals among teachers with and without such experience. A total of 623 educators participated in the study. Online sessions were of particular benefit to educators who had experience of working remotely with preschool children during the first wave of the pandemic. The results of this study indicate that the capacity of the children and the effectiveness of the online sessions themselves exceeded teachers’ expectations in many ways.
Asset Administration Shell Design Methodology Using Embedded OPC Unified Architecture Server
Authors: Pribiš Rudolf , Beňo Lukáš , Drahoš Peter
Published: October 2021

This article captures the current trends in the development of communication interoperability and common data modelling for the integration of devices into Industry 4.0 networks. The use of open standards such as the Open Platform Communications Unified Architecture (OPC UA) or the Asset Administration Shell (AAS) concept is the only way to achieve global communication and semantic interoperability. This article presents an original methodology of AAS implementation into an embedded system, dramatically reducing system requirements. The proposed workflow of the I4.0 component creation includes a procedure for the implementation of the AAS in the OPC UA information model. This methodology was verified by creating an intelligent sensor as a specific I4.0 cyber-physical system based on the 32 bit Arm Cortex Microcontroller. The outcome is the AAS as an “Embedded Industry 4.0 Component” hosted by a minimalist hardware; this is the very first design and implementation of a device with such parameters. Compared to recent studies (which implement certain types of AAS devices), the system requirements of the proposed embedded AAS are in the order of hundreds lower. The presented novel methodology enables developers and industrial manufacturers to implement relatively simple devices (e.g., smart sensors or actuators) as I4.0 Components.
Multi-User Drone Flight Training in Mixed Reality
Authors: Go Yong-Guk , Kang Ho-San , Lee Jong-Won , Yu Mun-Su , Choi Soo-Mi
Published: October 2021

The development of services and applications involving drones is promoting the growth of the unmanned-aerial-vehicle industry. Moreover, the supply of low-cost compact drones has greatly contributed to the popularization of drone flying. However, flying first-person-view (FPV) drones requires considerable experience because the remote pilot views a video transmitted from a camera mounted on the drone. In this paper, we propose a remote training system for FPV drone flying in mixed reality. Thereby, beginners who are inexperienced in FPV drone flight control can practice under the guidance of remote experts.
A Pentaband Compound Reconfigurable Antenna for 5G and Multi-Standard Sub-6GHz Wireless Applications
Authors: Ahmad Ikhlas , Khan Wasi Ur Rehman , Dildar Haris , Ullah Sadiq , Ullah Shakir , Mufti Naveed , Kamal Babar , Ahmad Toufeeq , Ghaffar Adnan , Hussien Mousa I.
Published: October 2021

This work proposes a low-profile, printed antenna that offers pattern and frequency reconfiguration functionalities printed on FR-4 substrate with a size of 46 × 32 × 1.6 mm3. The proposed antenna can operate in five different frequency bands, each one identified as a Mode, wherein there are possibilities of pattern reconfiguration. The frequency and pattern reconfigurability are made possible through 12 p-i-n diode switches (S1 to S12). The former is enabled through the switches S1 to S4 within the radiating patch, hence effectively controlling the resonant bands of the antenna; the latter is made possible through main lobe beam steering, enabled by the rest of the eight switches (S5 to S12), loaded in split parasitic elements designed on both sides of the radiator. The proposed antenna operates in the 5 GHz (4.52–5.39 GHz) band when all switches are OFF. When S1 is ON, the operating band shifts to 3.5 GHz (2.96–4.17 GHz); it changes to a 2.6 GHz (2.36–2.95 GHz) band when S1 and S2 are ON. When S3 is also turned ON, the antenna shifts to the 2.1 GHz Band (1.95–2.30 GHz). When S1–S4 are ON, the operating band shifts to a 1.8GHz (1.67–1.90 GHz) band. In all these bands, the return loss remains less than −10 dB while maintaining good impedance matching. At each operating band, the ON/OFF states of the eight p-i-n diode switches (S5 through S12) enable beam steering. The proposed antenna can direct the main beam in five distinct directions at 3.5GHz, 2.6 GHz, and 2.1 GHz bands, and three different directions at 5 GHz and 1.8 GHz bands. Different 5G bands (2.1, 2.6, 3.5, and 5) GHz, which fall in the sub 6GHz range, are supported by the proposed antenna. In addition, GSM (1.8 GHz), UMTS (2.1 GHz), 4G-LTE (2.1 GHz and 2.6 GHz), WiMAX (2.6 GHz and 3.5 GHz) and WLAN (5 GHz) applications are also supported by the proposed antenna, which is a candidate for handheld 5G/4G/3G devices.
Improving Deep Object Detection Algorithms for Game Scenes
Authors: Jung Minji , Yang Heekyung , Min Kyungha
Published: October 2021

The advancement and popularity of computer games make game scene analysis one of the most interesting research topics in the computer vision society. Among the various computer vision techniques, we employ object detection algorithms for the analysis, since they can both recognize and localize objects in a scene. However, applying the existing object detection algorithms for analyzing game scenes does not guarantee a desired performance, since the algorithms are trained using datasets collected from the real world. In order to achieve a desired performance for analyzing game scenes, we built a dataset by collecting game scenes and retrained the object detection algorithms pre-trained with the datasets from the real world. We selected five object detection algorithms, namely YOLOv3, Faster R-CNN, SSD, FPN and EfficientDet, and eight games from various game genres including first-person shooting, role-playing, sports, and driving. PascalVOC and MS COCO were employed for the pre-training of the object detection algorithms. We proved the improvement in the performance that comes from our strategy in two aspects: recognition and localization. The improvement in recognition performance was measured using mean average precision (mAP) and the improvement in localization using intersection over union (IoU).
Wireless Power Transfer Using Double DD Coils
Authors: Prosen Nataša , Domajnko Jure , Milanovič Miro
Published: October 2021

This paper deals with a wireless power transfer system where a novel structure of transmitting/receiving double DD coils is applied. This system uses two identical double D (DD) transmitter coils stacked on each other to transfer power to two stacked receiver coils. The power is transmitted simultaneously and independently through both transmitter coils to the receiving coils. The magnetic field of the first coil does not interfere with the second coil. Both transmitter and receiver coils are placed on each other and occupy the same footprint, so there is no need for increased space. This can lead to an interesting wireless power transfer system—from single load to double the load and higher power transfer density.
Self-Assessment of Soft Skills of University Teachers from Countries with a Low Level of Digital Competence
Authors: Antón-Sancho Álvaro , Vergara Diego , Fernández-Arias Pablo
Published: October 2021

The lockdown of March and April 2020 as a consequence of the COVID-19 pandemic has forced relevant changes in the educational environment in a very short period of time, making it necessary to suspend in-person instruction and generating the need to implement virtual learning mechanisms. In a future post-COVID-19 hybrid educational model, it will be necessary for university teachers to acquire an optimal degree of digital competence, as a combination of different competencies, namely, (i) technical, (ii) digital, and (iii) soft. Soft skills have been shown to have a decisive influence on the development of digital competence. The aim of this study was to analyze the degree of acquisition of soft skills in Latin American university teachers whose countries are less digitally developed. For this purpose, the countries with the lowest Global Innovation Index (GII) were selected: (i) Panama; (ii) Peru; (iii) Argentina; (iv) El Salvador; (v) Ecuador; (vi) Paraguay; (vii) Honduras; and (viii) Bolivia. To achieve this objective, it was necessary to develop a questionnaire on the self-concept of soft skills, based on the soft skills included in the Bochum Inventory of Personality and Competences (BIP). Results obtained from statistical analysis of the data collected from a sample of 219 participants show that university teachers are sufficiently prepared, in terms of their soft skills, for the increase in digital competence required as a result of the COVID-19 crisis, despite the low level of digital development in their respective countries.
Designing the Calibration Process of Weigh-In-Motion Systems
Authors: Gajda Janusz , Sroka Ryszard , Burnos Piotr
Published: October 2021

Weigh-In-Motion (WIM) systems provide information on the state of road traffic and are used in activities undertaken as part of traffic supervision and management, enforcement of applicable regulations, and in the design of road infrastructure. The further development of such systems is aimed at increasing their measurement accuracy, operational reliability, and their resistance to disturbing environmental factors. Increasing the accuracy of measurement can be achieved both through actions taken in the hardware layer (technology of load sensors, the number of sensors and their arrangement, technology used in the construction of the pavement, selection of the system location), as well as by implementing better system calibration algorithms and algorithms for pre-processing measurement data. In this paper, we focus on the issue of WIM system calibration. We believe that through the correct selection of the calibration algorithm, it is possible to significantly increase the accuracy of vehicle weighing in WIM systems, from a practical point of view. The simulation and experimental studies we conducted confirmed this hypothesis.
Modeling and Analysis of PV System with Fuzzy Logic MPPT Technique for a DC Microgrid under Variable Atmospheric Conditions
Authors: Subramanian Vasantharaj , Indragandhi Vairavasundaram , Kuppusamy Ramya , Teekaraman Yuvaraja
Published: October 2021

Due to the easiness of setup and great energy efficiency, direct current (DC) microgrids (MGs) have become more common. Solar photovoltaic (PV) and fuel cell (FC) systems drive the DC MG. Under varying irradiance and temperature, this work proposes a fuzzy logic controller (FLC) based maximum power point tracking (MPPT) approach deployed to PV panel and FC generated boost converter. PV panels must be operated at their maximum power point (MPP) to enhance efficiency and shorten the system’s payback period. There are different kinds of MPPT approaches for using PV panels at that moment. Still, the FLC-based MPPT approach was chosen in this study because it responds instantaneously to environmental changes and is unaffected by circuit parameter changes. Similarly, this research proposes a better design strategy for FLC systems. It will improve the system reliability and stability of the response of the system. An FLC evaluates PV and FC via DC–DC boost converters to obtain this enhanced response time and accuracy.
Demand Side Management Based Power-to-Heat and Power-to-Gas Optimization Strategies for PV and Wind Self-Consumption in a Residential Building Cluster
Authors: Brennenstuhl Marcus , Lust Daniel , Pietruschka Dirk , Schneider Dietrich
Published: October 2021

The volatility of renewable energy sources (RES) poses a growing problem for operation of electricity grids. In contrary, the necessary decarbonisation of sectors such as heat supply and transport requires a rapid expansion of RES. Load management in the context of power-to-heat systems can help to simultaneously couple the electricity and heat sectors and stabilise the electricity grid, thus enabling a higher share of RES. In addition power-to-hydrogen offers the possibility of long-term energy storage options. Within this work, we present a novel optimization approach for heat pump operation with the aim to counteract the volatility and enable a higher usage of RES. For this purpose, a detailed simulation model of buildings and their energy supply systems is created, calibrated and validated based on a plus energy settlement. Subsequently, the potential of optimized operation is determined with regard to PV and small wind turbine self-consumption. In addition, the potential of seasonal hydrogen storage is examined. The results show, that on a daily basis a 33% reduction of electricity demand from grid is possible. However, the average optimization potential is reduced significantly by prediction inaccuracy. The addition of a hydrogen system for seasonal energy storage basically eliminates the carbon dioxide emissions of the cluster. However, this comes at high carbon dioxide prevention costs of 1.76€kg−1.
An Experimental and Kinetic Modelling Study on Laminar Premixed Flame Characteristics of Ethanol/Acetone Mixtures
Authors: Liu Yangxun , Liu Weinan , Liao Huihong , Zhou Wenhua , Xu Cangsu
Published: October 2021

Since both ethanol and acetone are the main components in many alternative fuels, research on the burning characteristics of ethanol-acetone blends is important to understand the combustion phenomena of these alternative fuels. In the present study, the burning characteristics of ethanol-acetone fuel blends are investigated at a temperature of 358 K and pressure of 0.1 MPa with equivalence ratios ranging from 0.7 to 1.4. Ethanol at 100% vol., 25% vol. ethanol/75% vol. acetone, 50% vol. ethanol/50% vol. acetone, 75% vol. ethanol/25% vol. acetone, and 100% vol. acetone are studied by the constant volume combustion chamber (CVCC) method. The results show that the laminar burning velocities of the fuel blends are between that of 100% vol. acetone and 100% vol. ethanol. As the ethanol content increases, the laminar burning velocities of the mixed fuels increase. Furthermore, a detailed chemical kinetic mechanism (AramcoMech 3.0) is used for simulating the burning characteristics of the mixtures. The directed relation graph (DRG), DRG with error propagation (DRGEP), sensitivity analysis (SA), and full species sensitivity analysis (FSSA) are used for mechanism reduction. The flame structure of the skeletal mechanism does not change significantly, and the concentration of each species remains basically the same value after the reaction. The numbers of reactions and species are reduced by 90% compared to the detailed mechanism. Sensitivity and reaction pathway analyses of the burning characteristics of the mixtures indicate that the reaction C2H2+H(+M)<=>C2H3(+M) is the key reaction.