bluuebunny/crossref_metadata_2025 huggingface dataset:
Early Basal Cuspal Tear of a Porcine Bioprosthetic Mitral Valve Causing Massive Mitral Regurgitation
Authors: Tamim Muhammed , Alexiou Christos , AlKadi Yaser , Mahmoud Mohsen S. , Qaddoura Fatema
Published: November 2020

Although porcine mitral bioprostheses provide predictably good long-term outcomes, unexpected leaflet tears leading to abrupt haemodynamic changes may occur. Here, we report on a patient who was presented with acute dyspnea due to a cuspal tear of a porcine bioprosthetic mitral valve causing severe mitral regurgitation. Her condition was subsequently complicated by a systemic infection, probably pneumonia, and was successfully managed with an urgent redo-mitral valve replacement.
Five-Year Trends in Potential Drug Interactions with Direct-Acting Oral Anticoagulants in Patients with Atrial Fibrillation: An Australian-Wide Study
Authors: Bezabhe Woldesellassie M. , Bereznicki Luke R. , Radford Jan , Wimmer Barbara C. , Salahudeen Mohammed S. , Bindoff Ivan , Garrahy Edward , Peterson Gregory M.
Published: November 2020

Background: Co-prescribing medications that can interact with direct-acting oral anticoagulants (DOACs) may decrease their safety and efficacy. The aim of this study was to examine the co-prescribing of such medications with DOACs using the Australian national general practice dataset, MedicineInsight, over a five-year period. Methods: We performed five sequential cross-sectional analyses in patients with atrial fibrillation (AF) and a recorded DOAC prescription. Patients were defined as having a drug interaction if they had a recorded prescription of an interacting medication while they had had a recorded prescription of DOAC in the previous six months. The sample size for the cross-sectional analyses ranged from 5333 in 2014 to 19,196 in 2018. Results: The proportion of patients who had potential drug interactions with a DOAC decreased from 45.9% (95% confidence interval (CI) 44.6%–47.4%) in 2014 to 39.9% (95% CI 39.2%–40.6%) in 2018, p for trend < 0.001. During this period, the most frequent interacting class of medication recorded as having been prescribed with DOACs was selective serotonin/serotonin and norepinephrine reuptake inhibitor (SSRI/SNRI) antidepressants, followed by non-steroidal anti-inflammatory drugs (NSAIDs), calcium channel blockers (CCBs) and amiodarone. Conclusions: Overall, potential drug interactions with DOACs have decreased slightly over the last five years; however, the rate of possible interaction with SSRIs/SNRIs has remained relatively unchanged and warrants awareness-raising amongst prescribers.
Neutron Radiography and Tomography of the Drying Process of Screed Samples
Authors: Kapral Lorenz , Zawisky Michael , Abele Hartmut
Published: November 2020

The moisture content of screed samples is an essential parameter in the construction industry, since the screed must dry to a certain level of moisture content to be ready for covering. This paper introduces neutron radiography (NR) and neutron tomography (NT) as new, non-destructive techniques for analysing the drying characteristics of screed. Our NR analyses evaluate the results of the established methods while offering much higher spatial resolution of 200 μm, thereby facilitating a two- and three-dimensional understanding of screed’s drying behaviour. Because of NR’s exceptionally high sensitivity regarding the total cross section of hydrogen the precise moisture content of screed samples is obtainable, resulting in new observations. The current methods to measure moisture content comprise the ‘calcium carbide method’, the ‘Darr method’, and electrical sensor systems.
Automated Breast Cancer Detection in Digital Mammograms of Various Densities via Deep Learning
Authors: Suh Yong Joon , Jung Jaewon , Cho Bum-Joo
Published: November 2020

Mammography plays an important role in screening breast cancer among females, and artificial intelligence has enabled the automated detection of diseases on medical images. This study aimed to develop a deep learning model detecting breast cancer in digital mammograms of various densities and to evaluate the model performance compared to previous studies. From 1501 subjects who underwent digital mammography between February 2007 and May 2015, craniocaudal and mediolateral view mammograms were included and concatenated for each breast, ultimately producing 3002 merged images. Two convolutional neural networks were trained to detect any malignant lesion on the merged images. The performances were tested using 301 merged images from 284 subjects and compared to a meta-analysis including 12 previous deep learning studies. The mean area under the receiver-operating characteristic curve (AUC) for detecting breast cancer in each merged mammogram was 0.952 ± 0.005 by DenseNet-169 and 0.954 ± 0.020 by EfficientNet-B5, respectively. The performance for malignancy detection decreased as breast density increased (density A, mean AUC = 0.984 vs. density D, mean AUC = 0.902 by DenseNet-169). When patients’ age was used as a covariate for malignancy detection, the performance showed little change (mean AUC, 0.953 ± 0.005). The mean sensitivity and specificity of the DenseNet-169 (87 and 88%, respectively) surpassed the mean values (81 and 82%, respectively) obtained in a meta-analysis. Deep learning would work efficiently in screening breast cancer in digital mammograms of various densities, which could be maximized in breasts with lower parenchyma density.
(Divergent) Participation in the California Vowel Shift by Korean Americans in Southern California
Authors: Kim Ji Young , Wong Nicole
Published: November 2020

This study investigates the participation in the California Vowel Shift by Korean Americans in Los Angeles. Five groups of subjects participated in a picture narrative task: first-, 1.5-, and second-generation Korean Americans, Anglo-Californians, and (non-immigrant) Korean late learners of English. Results showed a clear distinction between early vs. late bilinguals; while the first-generation Korean Americans and the late learners showed apparent signs of Korean influence, the 1.5- and the second-generation Korean Americans participated in most patterns of the California Vowel Shift. However, divergence from the Anglo-Californians was observed in early bilinguals’ speech. Similar to the late bilinguals, the 1.5-generation speakers did not systematically distinguish prenasal and non-prenasal /æ/. The second-generation speakers demonstrated a split-/æ/ system, but it was less pronounced than for the Anglo-Californians. These findings suggest that age of arrival has a strong effect on immigrant minority speakers’ participation in local sound change. In the case of the second-generation Korean Americans, certain patterns of the California Vowel Shift were even more pronounced than for the Anglo-Californians (i.e., /ɪ/-lowering, /ɑ/-/ɔ/ merger, /ʊ/- and /ʌ/-fronting). Moreover, the entire vowel space of the second-generation Korean Americans, especially female speakers, was more fronted than that of the Anglo-Californians. These findings suggest that second-generation Korean Americans may be in a more advanced stage of the California Vowel Shift than Anglo-Californians or the California Vowel Shift is on a different trajectory for these speakers. Possible explanations in relation to second-generation Korean Americans’ intersecting gender, ethnic, and racial identities, and suggestions for future research are discussed.
Expression Kinetics of Regulatory Genes Involved in the Vesicle Trafficking Processes Operating in Tomato Flower Abscission Zone Cells during Pedicel Abscission
Authors: Sundaresan Srivignesh , Philosoph-Hadas Sonia , Riov Joseph , Salim Shoshana , Meir Shimon
Published: November 2020

The abscission process occurs in a specific abscission zone (AZ) as a consequence of the middle lamella dissolution, cell wall degradation, and formation of a defense layer. The proteins and metabolites related to these processes are secreted by vesicle trafficking through the plasma membrane to the cell wall and middle lamella of the separating cells in the AZ. We investigated this process, since the regulation of vesicle trafficking in abscission systems is poorly understood. The data obtained describe, for the first time, the kinetics of the upregulated expression of genes encoding the components involved in vesicle trafficking, occurring specifically in the tomato (Solanum lycopersicum) flower AZ (FAZ) during pedicel abscission induced by flower removal. The genes encoding vesicle trafficking components included soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs), SNARE regulators, and small GTPases. Our results clearly show how the processes of protein secretion by vesicle trafficking are regulated, programmed, and orchestrated at the level of gene expression in the FAZ. The data provide evidence for target proteins, which can be further used for affinity purification of plant vesicles in their natural state. Such analyses and dissection of the complex vesicle trafficking networks are essential for further elucidating the mechanism of organ abscission.
Characterizing the Local Material Properties of Different Fe–C–Cr-Steels by Using Deep Rolled Single Tracks
Authors: Wielki Nicole , Heinz Noémie , Meyer Daniel
Published: November 2020

As part of a novel method for material development, deep rolling was used in this work to characterize the mechanical properties of macroscopic specimens of C45 (AISI 1045), S235 (AISI 1015), and 100Cr6 (AISI 52100) in various heat treatment states. Deep rolling is conventionally used to enhance surface and subsurface properties by reducing the surface roughness, introducing compressive residual stresses, and strain hardening. In the context of this work, it was utilized to determine material-specific variables via a mechanically applied load. For that purpose, the geometries of individual deep rolled tracks were measured. In dependence of the process parameters such as deep rolling pressure and tool size, the track geometry, i.e., the specific track depth, was for the first time compared for different materials. A functional relationship identified between the specific track depth and the material state dependent hardness forms the basis for a future characterization of the properties of alloy compositions belonging to the Fe–C–Cr system. Since deep rolling is performed in the same clamping as machining operations, hardness alterations could easily be determined at different points in the process chain using an optical in-process measurement of track geometries in the future.
Effect of Elevated Temperature on the Bond Strength of Prestressing Reinforcement in UHPC
Authors: Pokorný Petr , Kolísko Jiří , Čítek David , Kostelecká Michaela
Published: November 2020

The study explores the effect of elevated temperatures on the bond strength between prestressing reinforcement and ultra-high performance concrete (UHPC). Laboratory investigations reveal that the changes in bond strength correspond well with the changes in compressive strength of UHPC and their correlation can be mathematically described. Exposition of specimens to temperatures up to 200 °C does not reduce bond strength as a negative effect of increasing temperature is outweighed by the positive effect of thermal increase on the reactivity of silica fume in UHPC mixture. Above 200 °C, bond strength significantly reduces; for instance, a decrease by about 70% is observed at 800 °C. The decreases in compressive and bond strengths for temperatures above 400 °C are related to the changes of phase composition of UHPC matrix (as revealed by X-ray powder diffraction) and the changes in microstructure including the increase of porosity (verified by mercury intrusion porosimetry and observation of confocal microscopy) and development cracks detected by scanning electron microscopy. Future research should investigate the effect of relaxation of prestressing reinforcement with increasing temperature on bond strength reduction by numerical modelling.
Experimental and Theoretical Insights into the Synergistic Effect of Iodide Ions and 1-Acetyl-3-Thiosemicarbazide on the Corrosion Protection of C1018 Carbon Steel in 1 M HCl
Authors: Alamri Aeshah Hassan
Published: November 2020

Experimental insights into the synergistic effect of 1-acetyl-3-thiosemicarbazide (AST) and iodide ions on the corrosion of C1018 carbon steel in 1 M HCl solution were investigated using open-circuit potential (OCP), linear polarization resistance (LPR), electrochemical frequency modulation (EFM), potentiodynamic polarization (PDP) measurements and electrochemical impedance spectroscopy (EIS). Theoretical studies were further undertaken using ACD/LABS Percepta software, density functional theory (DFT) calculations and Monte Carlo simulation to understand the mechanism of the corrosion inhibition process and interpret the experimental results at the atomic and molecular levels. The electrochemical results obtained showed that AST alone inhibited the acid-induced corrosion of C1018 carbon steel. The inhibition efficiency increases with a concentration reaching up to 72.27% at 750 ppm of AST. The addition of 5 mM KI to 250 ppm of AST improved the inhibition efficiency to 81.64%. The solubility and protonated state results predicted using the ACD/LABS Percepta software showed that AST was highly soluble in the aqueous acidic medium and approximately 95% of AST exists in the neutral form in 1 M HCl (pH = 0). DFT calculations and a Monte Carlo simulation were utilized to predict the active reactivity sites of AST and calculate the lowest adsorption energy and configuration of AST alone and AST + iodide on/Fe (110)/water interface.
Isolation, Characterization and Bioactive Properties of Alkali-Extracted Polysaccharides from Enteromorpha prolifera
Authors: Zhao Shifeng , He Yuan , Wang Chungu , Assani Israa , Hou Peilei , Feng Yan , Yang Juanjuan , Wang Yehua , Liao Zhixin , Shen Songdong
Published: November 2020

Four new purified polysaccharides (PAP) were isolated and purified from the Enteromorpha prolifera by alkali extraction, and further characterization was investigated. Their average molecular weights of PAP-1, PAP-2, PAP-3, and PAP-4 were estimated as 3.44 × 104, 6.42 × 104, 1.20 × 105, and 4.82 × 104 Da, respectively. The results from monosaccharide analysis indicated that PAP-1, PAP-2, PAP-3 were acidic polysaccharides and PAP-4 was a neutral polysaccharide. PAP-1 and PAP-2 mainly consist of galacturonic acid, while PAP-3 and PAP-4 mainly contained rhamnose. Congo red test showed that no triple helical structure was detected in the four polysaccharides. The antioxidant activities were investigated using 1,1-diphenyl-2-picrylhydrazyl (DPPH), Superoxide, and 2, 2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical assay. In vitro antitumor activities were evaluated by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. PAP-1 exhibited relatively stronger antioxidant activities among the four polysaccharides in a dose-dependent manner. At a concentration of 1.00 mg/mL, the antioxidant activities of PAP-1 on the DPPH radical scavenging rate, superoxide anion radical scavenging rate, and ABTS radical rate at 1.00 mg/mL were 56.40%, 54.27%, and 42.07%, respectively. They also showed no significant inhibitory activity against MGC-803, HepG2, T24, and Bel-7402 cells. These investigations of polysaccharides provide a scientific basis for the use of E. prolifera as an ingredient in functional foods and medicines.
The Potential Mechanisms of the Neuroprotective Actions of Oil Palm Phenolics: Implications for Neurodegenerative Diseases
Authors: Ibrahim Nurul ‘Izzah , Muhammad Ismail Tadj Nur Balqis , Rahman Sarker Md. Moklesur , Naina Mohamed Isa
Published: November 2020

Neurodegenerative diseases (ND) can be characterized by degradation and subsequent loss of neurons. ND has been identified as the leading cause of disability-adjusted life years (DALYs) worldwide and is associated with various risk factors such as ageing, certain genetic polymorphisms, inflammation, immune and metabolic conditions that may induce elevated reactive oxygen species (ROS) release and subsequent oxidative stress. Presently, no specific cure or prevention is available for ND patients; the symptoms can be only alleviated via drug treatment or surgery. The existing pharmacological treatments are only available for partial treatment of the symptoms. A natural product known as oil palm phenolics (OPP), which is high in antioxidant, could become a potential supplementary antioxidant for neurodegenerative health. OPP is a water-soluble extract from palm fruit that demonstrated medicinal properties including anti-tumor, anti-diabetic and neuroprotective effects. In this review, OPP was proposed for its neuroprotective effects via several mechanisms including antioxidant and anti-inflammatory properties. Besides, OPP has been found to modulate the genes involved in neurotrophic activity. The evidence and proposed mechanism of OPP on the neuroprotective health may provide a comprehensive natural medicine approach to alleviate the symptoms of neurodegenerative diseases.
Osmotic Stress Leads to Significant Changes in Rice Root Metabolic Profiles between Tolerant and Sensitive Genotypes
Authors: Matsunami Maya , Toyofuku Kyoko , Kimura Natsumi , Ogawa Atsushi
Published: November 2020

To breed osmotic stress-tolerant rice, the mechanisms involved in maintaining root growth under osmotic stress is important to elucidate. In this study, two rice (Oryza sativa L.) cultivars, IR 58 (stress-tolerant cultivar) and Basilanon (stress-sensitive cultivar), were used. After 1, 3, and 7 days of −0.42 MPa osmotic stress treatment induced by polyethylene glycol (PEG) 6000, root metabolomes were analyzed, yielding 276 detected compounds. Among 276 metabolites, 102 metabolites increased with the duration of the stress treatment in IR 58 roots, and only nine metabolites decreased. In contrast, 51 metabolites increased, and 45 metabolites decreased in Basilanon roots. Principal component analysis (PCA) scores clearly indicated differences between the cultivars and the treatments. Pathway analysis showed that the metabolites exhibiting stress-induced increases in IR 58 were those involved in sugar metabolism (such as sucrose 6’-phosphate, glucose 1-phosphate), polyamine and phenylpropanoid metabolisms (such as spermine, spermidine, gamma-aminobutyric acid (GABA)), and glutathione metabolism (such as glutathione, cysteine, cadaverine). IR 58 roots showed an increase in the most proteinogenic amino acids such as proline, serine, glutamine and asparagine. It was also maintained or increased the tricarboxylic acid (TCA) cycle intermediates (citric acid, cis-Aconitic acid, isocitric acid, fumaric acid, malic acid) under osmotic stress compared with that under control. Therefore, IR 58 actively synthesized various metabolites, and the increase in these metabolites contributed to the maintenance of important biological functions such as energy production and antioxidant defense to promote root development under osmotic stress.
Digital Literacy and Higher Education during COVID-19 Lockdown: Spain, Italy, and Ecuador
Authors: Tejedor Santiago , Cervi Laura , Pérez-Escoda Ana , Jumbo Fernanda Tusa
Published: November 2020

Digital literacy constitutes the basis for citizenship in order to be effective and efficient in the 21st Century in professional and personal lives. The set of skills and competences integrating digital literacy are expected to be guaranteed in higher education. During the lockdown globally imposed for the COVID-19 pandemic, educational systems worldwide had to face many disruptive changes. The aim of this research is to present a comparative study of three countries’ higher education institutions (Spain, Italy, and Ecuador), analyzing how they have faced the global lockdown situation, focusing on the development of digital literacy. The methodological approach followed in this study was quantitative with an exploratory-correlational scope using a questionnaire designed ad hoc and applied in a sample of 376 students. Results point the necessity of enhancing the main aspects such as the teacher’s digital skills, sources for learning that may be adapted, communication between universities and students, and teaching methodologies that should be appropriate to the current context. Conclusions may suggest rethinking higher education learning and reinforcing main issues for this transformation, mainly: communication, teaching, and digital competences. Otherwise, digital literacy is not being guaranteed, which means higher education is not accomplishing one of its main objectives.
Multi-Instance Inertial Navigation System for Radar Terrain Imaging
Authors: Labowski Michal , Kaniewski Piotr
Published: November 2020

Navigation systems used for the motion correction (MOCO) of radar terrain images have several limitations, including the maximum duration of the measurement session, the time duration of the synthetic aperture, and only focusing on minimizing long-term positioning errors of the radar host. To overcome these limitations, a novel, multi-instance inertial navigation system (MINS) has been proposed by the authors. In this approach, the classic inertial navigation system (INS), which works from the beginning to the end of the measurement session, was replaced by short INS instances. The initialization of each INS instance is performed using an INS/GPS system and is triggered by exceeding the positioning error of the currently operating instance. According to this procedure, both INS instances operate simultaneously. The parallel work of the instances is performed until the image line can be calculated using navigation data originating only from the new instance. The described mechanism aims to perform instance switching in a manner that does not disturb the initial phases of echo signals processed in a single aperture. The obtained results indicate that the proposed method improves the imaging quality compared to the methods using the classic INS or the INS/GPS system.
Interdigital Capacitor-Based Passive LC Resonant Sensor for Improved Moisture Sensing
Authors: Dimitrov Kristian Chavdarov , Song Sanghun , Chang Hyungjun , Lim Taejun , Lee Yongshik , Kwak Byung-Jae
Published: November 2020

Herein, a passive low-profile moisture sensor design based on radio frequency identification (RFID) technology is proposed. The sensor consists of an LC resonant loop, and the sensing mechanism is based on the fringing electric field generated by the capacitor in the circuit. A standard planar inductor and a two-layer interdigital capacitor (IDC) with a significantly higher fringing capacitance compared to that of a conventional parallel plate capacitor (PPC) are used, resulting in improved frequency offset and sensitivity of the sensor. Furthermore, a sensor tag was designed to operate at an 8.2 MHz electronic article surveillance (EAS) frequency range and the corresponding simulation results were experimentally verified. The IDC- and PPC-based capacitor designs were comprehensively compared. The proposed IDC sensor exhibits enhanced sensitivity of 10% in terms of frequency offset that is maintained over time, increased detection distance of 5%, and more than 20% increase in the quality factor compared to sensors based on PPC. The sensor’s performance as a urine detector was experimentally qualified. Additionally, it was shown experimentally that the proposed sensor shows a faster response to moisture. Both simulation and experimental data are presented and elucidated herein.
Application of Transfer Learning in EEG Decoding Based on Brain-Computer Interfaces: A Review
Authors: Zhang Kai , Xu Guanghua , Zheng Xiaowei , Li Huanzhong , Zhang Sicong , Yu Yunhui , Liang Renghao
Published: November 2020

The algorithms of electroencephalography (EEG) decoding are mainly based on machine learning in current research. One of the main assumptions of machine learning is that training and test data belong to the same feature space and are subject to the same probability distribution. However, this may be violated in EEG processing. Variations across sessions/subjects result in a deviation of the feature distribution of EEG signals in the same task, which reduces the accuracy of the decoding model for mental tasks. Recently, transfer learning (TL) has shown great potential in processing EEG signals across sessions/subjects. In this work, we reviewed 80 related published studies from 2010 to 2020 about TL application for EEG decoding. Herein, we report what kind of TL methods have been used (e.g., instance knowledge, feature representation knowledge, and model parameter knowledge), describe which types of EEG paradigms have been analyzed, and summarize the datasets that have been used to evaluate performance. Moreover, we discuss the state-of-the-art and future development of TL for EEG decoding. The results show that TL can significantly improve the performance of decoding models across subjects/sessions and can reduce the calibration time of brain–computer interface (BCI) systems. This review summarizes the current practical suggestions and performance outcomes in the hope that it will provide guidance and help for EEG research in the future.
Evaluation of Clustering Algorithms on GPU-Based Edge Computing Platforms
Authors: Cecilia José M. , Cano Juan-Carlos , Morales-García Juan , Llanes Antonio , Imbernón Baldomero
Published: November 2020

Internet of Things (IoT) is becoming a new socioeconomic revolution in which data and immediacy are the main ingredients. IoT generates large datasets on a daily basis but it is currently considered as “dark data”, i.e., data generated but never analyzed. The efficient analysis of this data is mandatory to create intelligent applications for the next generation of IoT applications that benefits society. Artificial Intelligence (AI) techniques are very well suited to identifying hidden patterns and correlations in this data deluge. In particular, clustering algorithms are of the utmost importance for performing exploratory data analysis to identify a set (a.k.a., cluster) of similar objects. Clustering algorithms are computationally heavy workloads and require to be executed on high-performance computing clusters, especially to deal with large datasets. This execution on HPC infrastructures is an energy hungry procedure with additional issues, such as high-latency communications or privacy. Edge computing is a paradigm to enable light-weight computations at the edge of the network that has been proposed recently to solve these issues. In this paper, we provide an in-depth analysis of emergent edge computing architectures that include low-power Graphics Processing Units (GPUs) to speed-up these workloads. Our analysis includes performance and power consumption figures of the latest Nvidia’s AGX Xavier to compare the energy-performance ratio of these low-cost platforms with a high-performance cloud-based counterpart version. Three different clustering algorithms (i.e., k-means, Fuzzy Minimals (FM), and Fuzzy C-Means (FCM)) are designed to be optimally executed on edge and cloud platforms, showing a speed-up factor of up to 11× for the GPU code compared to sequential counterpart versions in the edge platforms and energy savings of up to 150% between the edge computing and HPC platforms.
A Multimodal Real-Time Feedback Platform Based on Spoken Interactions for Remote Active Learning Support
Authors: Cornide-Reyes Hector , Riquelme Fabián , Monsalves Diego , Noel Rene , Cechinel Cristian , Villarroel Rodolfo , Ponce Francisco , Munoz Roberto
Published: November 2020

While technology has helped improve process efficiency in several domains, it still has an outstanding debt to education. In this article, we introduce NAIRA, a Multimodal Learning Analytics platform that provides Real-Time Feedback to foster collaborative learning activities’ efficiency. NAIRA provides real-time visualizations for students’ verbal interactions when working in groups, allowing teachers to perform precise interventions to ensure learning activities’ correct execution. We present a case study with 24 undergraduate subjects performing a remote collaborative learning activity based on the Jigsaw learning technique within the COVID-19 pandemic context. The main goals of the study are (1) to qualitatively describe how the teacher used NAIRA’s visualizations to perform interventions and (2) to identify quantitative differences in the number and time between students’ spoken interactions among two different stages of the activity, one of them supported by NAIRA’s visualizations. The case study showed that NAIRA allowed the teacher to monitor and facilitate the learning activity’s supervised stage execution, even in a remote learning context, with students working in separate virtual classrooms with their video cameras off. The quantitative comparison of spoken interactions suggests the existence of differences in the distribution between the monitored and unmonitored stages of the activity, with a more homogeneous speaking time distribution in the NAIRA supported stage.
Hybrid System of Emotion Evaluation in Physiotherapeutic Procedures
Authors: Romaniszyn-Kania Patrycja , Pollak Anita , Danch-Wierzchowska Marta , Kania Damian , Myśliwiec Andrzej P. , Piętka Ewa , Mitas Andrzej W.
Published: November 2020

Nowadays, the dynamic development of technology allows for the design of systems based on various information sources and their integration into hybrid expert systems. One of the areas of research where such systems are especially helpful is emotion analysis. The sympathetic nervous system controls emotions, while its function is directly reflected by the electrodermal activity (EDA) signal. The presented study aimed to develop a tool and propose a physiological data set to complement the psychological data. The study group consisted of 41 students aged from 19 to 26 years. The presented research protocol was based on the acquisition of the electrodermal activity signal using the Empatica E4 device during three exercises performed in a prototype Disc4Spine system and using the psychological research methods. Different methods (hierarchical and non-hierarchical) of subsequent data clustering and optimisation in the context of emotions experienced were analysed. The best results were obtained for the k-means classifier during Exercise 3 (80.49%) and for the combination of the EDA signal with negative emotions (80.48%). A comparison of accuracy of the k-means classification with the independent division made by a psychologist revealed again the best results for negative emotions (78.05%).
Importance of Gender, Location of Secondary School, and Professional Experience for GPA—A Survey of Students in a Free Tertiary Education Setting
Authors: Kurek Bartosz , Górowski Ireneusz
Published: November 2020

A publicly financed tertiary education system is a manifestation of a sustainable approach to education. Society as a whole decides to spend money on the education of young generations, who in turn are expected to do the same for future generations. The benefactor expects that students conscientiously gain knowledge, skills, and competences during their studies. These features are incorporated into and measured with the grade point average (GPA). This research contributes to the scientific debate through the identification and measurement of determinants of students’ GPA in a unique country setting, where top tertiary education is financed by a government. We investigate the relationship between GPA and differentiating factors: gender, population size of a town where students’ secondary school was located, and professional experience. Research methods used include literature analysis, parametric and nonparametric statistical tests, and econometric modeling. The surveyed sample comprised 341 accounting and controlling students from Cracow University of Economics. We find that gender, location of a secondary school, and professional experience are statistically significantly associated with GPA. Female students tend to earn higher GPAs. Similarly, students who completed secondary education in smaller towns earn higher GPAs. On the contrary students who have professional experience tend to earn lower GPAs.
Sustainability Assessment in Manufacturing under a Strong Sustainability Perspective—An Ecological Neutrality Initiative
Authors: Pinto Luiz Fernando Rodrigues , Venturini Glória de Fátima Pereira , Digiesi Salvatore , Facchini Francesco , Oliveira Neto Geraldo Cardoso de
Published: November 2020

The concept of strong sustainability establishes ecosystem conservation as the basis for socioeconomic development. Despite the increase in the number of studies on this subject, the qualitative approach used in studies on strong sustainability makes the introduction of this theme difficult in the industrial context. The absence of a model of sustainability evaluation in manufacturing based on the concept of strong sustainability was the gap identified by this research. The objective of this study was to develop a model that embeds strong sustainability within the sustainability assessment of manufacturing companies. The research used survey methodology to obtain the opinion of experts on the relevance of sustainability metrics. Information collected from experts was used to calculate the weights of indicators and of the participation of each dimension in strong sustainability. The results indicated that strong sustainability consists of 48% of environmental, 29% of social, and 23% of economic factors. The model has been applied in a study of multiple cases in factories in the automotive sector, two in Brazil and two in Italy. The results revealed that the four companies were rated regular in the strong sustainability scale. However, the sustainability performances of the companies showed different patterns over five years. Furthermore, analysis of the individual performance of the dimensions showed that the economic growth of the two Brazilian factories was superior to the socio-environmental development. The result of the Italian units emphasized different priorities. A firm reached the best result in environmental performance and the other one on the social dimension.
Peer Assessment in Physical Education: A Systematic Review of the Last Five Years
Authors: Bores-García Daniel , Hortigüela-Alcalá David , González-Calvo Gustavo , Barba-Martín Raúl
Published: November 2020

Purpose: A systematic review of the use of peer assessment in Physical Education in the last five years (2016–2020). Method: Four databases were used to select those articles that included information on peer assessment in Physical Education in the different educational stages. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, including the PICO (participants, intervention, comparators, and outcomes) strategy, after the exclusion criteria, 13 articles were fully assessed based on seven criteria: (1) year and author; (2) country; (3) educational stage; (4) type of paper; (5) purpose; (6) content; and (7) outcomes. Results: the results show that the research was geographically dispersed, although Spain and the USA had half of the articles reviewed. The research was carried out at all educational stages, although a greater focus was observed in higher education than in primary and secondary education. Quantitative, qualitative, and mixed research was almost equally represented, and dealt mainly with sports and games. Regarding the goals of the studies, a diversity of research so great that it produced a lack of continuity and coherence in the literature on the subject was found. The research results on the use of peer assessment showed an increase in the level of motivation, perceived teaching confidence and competence, and teaching self-efficacy. More research is needed on the benefits of the use of peer assessment on the self-regulation of learning and the critical thinking of students.
Dynamics of Regional Development in Regional and Municipal Economy
Authors: Beran Vaclav , Teichmann Marek , Kuda Frantisek , Zdarilova Renata
Published: November 2020

This article deals with the dynamics of territory development in the regional and municipal economy. The development of the territory is and has always been limited or restricted by the available sources of capital, the dynamics of its use, and the localization of its distribution in the chosen territory. Today’s limits are, under Czech conditions, laid down by the Building Act; namely, the land-use plan, the strategic plans for development, and the political mechanisms of the elected leaders. The verbalization of the democratization of the economy is swayed by the concepts of meritocratic holding and the attempts to create values, but also by already existing values. We interpret the term values as infrastructure developed in the past, but also as resources given by the natural, geographic, and other environments.
Digitalization in Developing Maritime Business Environments towards Ensuring Sustainability
Authors: Kapidani Nexhat , Bauk Sanja , Davidson Innocent E.
Published: November 2020

The paper focuses on assessing the level of digitalization in several developing maritime business environments in Albania, Bosnia and Herzegovina, Montenegro, and Serbia. The assessment has been done in reference to Holtham’s and Courtney’s Intelligent Information and Communication Technologies (ICT) Exploiter Model. The dimensions as maritime business system effectiveness, roles, and skills of information technology personnel, ladders of knowledge, ICT strategy, organizational culture, and manager’s mindset are analyzed. In addition, benchmarking with findings from developed maritime business environments in Croatia, Greece, Italy, and Slovenia, which belong to the European Union (EU), by using the same model, has been conducted. This is done with the aim to outline directions for improving the quality and speed of digitalization in non-EU countries, which have been functioning for decades in transitional conditions. The maritime ecosystem naturally has a tendency to be unique and to function smoothly as such. Alleviating the differences in the level and effectiveness of digitalization in developed and developing European countries is a path towards achieving this goal. By sharing their own expertise in the rational and intelligent use of ICT, developed EU countries can support developing non-EU countries towards ensuring sustainability in the entire European and worldwide maritime business ecosystem.
Sustainable Public Procurement in Central European Countries. Can It Also Bring Savings?
Authors: Džupka Peter , Kubák Matúš , Nemec Peter
Published: November 2020

The efficiency of public resource use and its strategic framework with respect to sustainable public procurement policies, such as the most economically advantageous tender (hereafter MEAT), has become an important topic nowadays. Therefore, the study examines the determinants of savings creation within MEAT in Central European countries. It uses a dataset published in the Tenders Electronic Daily database in 2017–2018 about contract award notices and carries out a generalized linear model to study the determinants of savings creation within MEAT. The findings suggest that when services are procured within MEAT, the savings are considerably higher than compared to works. If the framework agreement takes place in a procurement process, the savings are significantly smaller. In cases where the subject of procurement is not co-financed by EU funds, the savings are higher than in the case that they are. If an open type of procurement is used, the savings are seemingly smaller than in cases where a non-open type of procurement takes place. When the contract is awarded to a single supplier, the savings are higher than otherwise. A higher number of total offers, as well as a higher number of offers from small and medium-sized enterprises, induce higher savings. It can be concluded that the use of sustainable public procurement subtly reduces the creation of savings.
Therapeutic Qualities and Sustainable Approach to Heritage of the City. The Coastal Strip in Gdańsk, Poland
Authors: Trojanowska Monika
Published: November 2020

In this paper, the case of the Coastal Strip in Gdańsk is presented. Gdańsk has natural and cultural heritage of great value and is included on Tentative list of UNESCO World Heritage List as “Gdansk—Town of Memory and Freedom”. The Coastal Strip is a rare example of landscape with natural dunes located within walking distance from densely populated residential districts. Therefore, the economic pressure for urban development is extremely strong. At the same time, the rise of social awareness about potential consequences of urbanization brought numerous efforts by local activists and researchers to prevent further development of the Coastal Strip. This study consisted of assessment of therapeutic qualities of The Coastal Strip using a conceptual framework—a universal standard for health promoting places. The results demonstrated that The Coastal Strip is a health-promoting place, thus adding new research-based evidence against plans for urban development of that area.
Quality, Equity and Utility of Observational Studies during 10 Years of Implementing the Structured Operational Research and Training Initiative in 72 Countries
Authors: Zachariah Rony , Rust Stefanie , Thekkur Pruthu , Khogali Mohammed , Kumar Ajay MV , Davtyan Karapet , Diro Ermias , Satyanarayana Srinath , Denisiuk Olga , Griensven Johan van , Hermans Veerle , Berger Selma Dar , Saw Saw , Reid Anthony , Aseffa Abraham , Harries Anthony D , Reeder John C
Published: November 2020

Introduction: Observational studies are often inadequately reported, making it difficult to assess their validity and generalizability and judge whether they can be included in systematic reviews. We assessed the publication characteristics and quality of reporting of observational studies generated by the Structured Operational Research and Training Initiative (SORT IT). Methods: A cross-sectional analysis of original publications from SORT IT courses. SORT IT is a global partnership-based initiative aimed at building sustainable capacity for conducting operational research according to country priorities and using the generated evidence for informed decision-making to improve public health. Reporting quality was independently assessed using an adapted version of ‘Strengthening the Reporting of Observational Studies in Epidemiology’ (STROBE) checklist. Results: In 392 publications, involving 72 countries, 50 journals, 28 publishers and 24 disease domains, low- and middle-income countries (LMICs) first authorship was seen in 370 (94%) and LMIC last authorship in 214 (55%). Publications involved LMIC-LMIC collaboration in 90% and high-income-country-LMIC collaboration in 87%. The majority (89%) of publications were in immediate open access journals. A total of 346 (88.3%) publications achieved a STROBE reporting quality score of >85% (excellent), 41 (10.4%) achieved a score of 76–85% (good) and 5 (1.3%) a score of 65–75% (fair). Conclusion: The majority of publications from SORT IT adhere to STROBE guidelines, while also ensuring LMIC equity and collaborative partnerships. SORT IT is, thus, playing an important role in ensuring high-quality reporting of evidence for informed decision-making in public health.
VIRIDIC—A Novel Tool to Calculate the Intergenomic Similarities of Prokaryote-Infecting Viruses
Authors: Moraru Cristina , Varsani Arvind , Kropinski Andrew M.
Published: November 2020

Nucleotide-based intergenomic similarities are useful to understand how viruses are related with each other and to classify them. Here we have developed VIRIDIC, which implements the traditional algorithm used by the International Committee on Taxonomy of Viruses (ICTV), Bacterial and Archaeal Viruses Subcommittee, to calculate virus intergenomic similarities. When compared with other software, VIRIDIC gave the best agreement with the traditional algorithm, which is based on the percent identity between two genomes determined by BLASTN. Furthermore, VIRIDIC proved best at estimating the relatedness between more distantly-related phages, relatedness that other tools can significantly overestimate. In addition to the intergenomic similarities, VIRIDIC also calculates three indicators of the alignment ability to capture the relatedness between viruses: the aligned fractions for each genome in a pair and the length ratio between the two genomes. The main output of VIRIDIC is a heatmap integrating the intergenomic similarity values with information regarding the genome lengths and the aligned genome fraction. Additionally, VIRIDIC can group viruses into clusters, based on user-defined intergenomic similarity thresholds. The sensitivity of VIRIDIC is given by the BLASTN. Thus, it is able to capture relationships between viruses having in common even short genomic regions, with as low as 65% similarity. Below this similarity level, protein-based analyses should be used, as they are the best suited to capture distant relationships. VIRIDIC is available at viridic.icbm.de, both as a web-service and a stand-alone tool. It allows fast analysis of large phage genome datasets, especially in the stand-alone version, which can be run on the user’s own servers and can be integrated in bioinformatics pipelines. VIRIDIC was developed having viruses of Bacteria and Archaea in mind; however, it could potentially be used for eukaryotic viruses as well, as long as they are monopartite.
Particle Swarm Optimization and Real-Road/Driving-Cycle Analysis Based Powertrain System Design for Dual Motor Coupling Electric Vehicle
Authors: Ma Chao , Jin Shiwei , Yang Kun , Tan Di , Gao Jie , Yan Dechao
Published: November 2020

In this study, a planetary gear based dual motor coupling electric vehicle is proposed, which achieves higher system efficiency by enabling motor working under high operating efficiency area. Firstly, the dynamic characteristics of the proposed configuration are analyzed and the reasonable working modes are established. Secondly, the optimal dual motor parameters are derived according to the statistical analysis on the typical driving conditions and the collected real road driving data. Especially, the optimal parameters of planetary gear and final transmission ratio are obtained using particle swarm optimization algorithm. Finally, based on the developed mode shift algorithm, the dual motor coupling full vehicle model is developed and the vehicle performance is analyzed using MATLAB/Simulink. For the UDDS (Urban Dynamometer Driving Schedule) driving cycle, it is seen from the simulation results of motor operating points that the proposed dual motor configuration is mostly operated under the high efficiency range, and the power consumption is significantly reduced by 7.6% compared with the single motor configuration. For the NEDC (New European Driving Cycle), WLTC (Worldwide Harmonized Light Vehicles Test Cycle) and real road driving conditions, the proposed dual motor configuration also achieves system efficiency improvement of 5.0%~16.3%, which confirms the validity of the proposed configuration and its corresponding parameter matching and control algorithm development.
IMPLEMENTATION OF ENTREPRENEURIAL COMPETENCE IN THE EDUCATIONAL PROCESS OF INSTITUTIONS OF POSTGRADUATE PEDAGOGICAL EDUCATION
Authors: Kurish Natalya
Published: November 2020

The conducted analysis of educational and professional training programs for teachers of natural specialties and curricula on the possibility of forming entrepreneurial competence revealed problems and encouraged the implementation of entrepreneurial competence in the educational process of postgraduate pedagogical education institutions through the developed algorithm of individual educational trajectory of natural science teachers.