bluuebunny/crossref_metadata_2025 huggingface dataset:
An Increased Risk of School-Aged Children with Viral Infection among Diarrhea Clusters in Taiwan during 2011–2019
Authors: Lin Fu-Huang , Chou Yu-Ching , Chen Bao-Chung , Lu Jui-Cheng , Liu Chung-Jung , Hsieh Chi-Jeng , Yu Chia-Peng
Published: September 2021

Acute diarrhea is mainly caused by norovirus and rotavirus. Numerous factors modify the risk of diarrhea cluster infections and outbreaks. The purpose of this study was to explore the epidemiological characteristics, differences, and trends in the distribution of viral and bacterial pathogens that cause diarrhea cluster events as well as the public places where diarrhea cluster events took place in Taiwan from 2011 to 2019. We examined publicly available, annual summary data on 2865 diarrhea clusters confirmed by the Taiwan Centers for Disease Control (CDC) from 2011 to 2019. There were statistically significant differences (p < 0.001) in event numbers of diarrhea clusters among viral and bacterial pathogens, and statistically significant differences (p < 0.001) in event numbers of diarrhea clusters among bacterial pathogens. There were also statistically significant differences (p < 0.001) in the event numbers of diarrhea clusters among public places. Norovirus infections were the first most numerous (77.1%, 1810/2347) diarrhea clusters among viral and bacterial infections. Among bacterial infections, Staphylococcus aureus infections accounted for the greatest number of diarrhea clusters (35.5%, 104/293). Schools were the places with the greatest number of diarrhea clusters (49.1%, 1406/2865) among various institutions. Norovirus single infection (odds ratio, OR = 4.423), Staphylococcus aureus single infection (OR = 2.238), and school (OR = 1.983) were identified as risk factors. This is the first report of confirmed events of diarrhea clusters taken from surveillance data compiled by Taiwan’s CDC (2011–2019). This study highlights the importance of long-term and geographically extended studies, particularly for highly fluctuating pathogens, to understand the implications of the transmission of diarrhea clusters in Taiwan’s populations. Importantly, big data have been identified that can inform future surveillance and research efforts in Taiwan.
Is There a Dose-Response Relationship between Acute Physical Activity and Sleep Length? A Longitudinal Study with Children and Adolescents Living in Sweden
Authors: Nordman Alexandra , Friberg Marita , Forsell Yvonne
Published: September 2021

A declining physical activity (PA) and sleep in children and adolescents have been observed during the previous decades. PA could benefit sleep, but the findings are mixed. The aim of the present study was to examine if there is a dose-response relationship between time spent in acute moderate and vigorous physical activity (MVPA) and sleep length in children and adolescents. Additional aims were to examine if the sleep length is higher for children and adolescents who conduct at least an average of 60 min in MVPA/day and to study differences between sex and school years. The study population consists of 262 participants in school year 5 (aged 11 years), 7 (aged 13 years), and 9 (aged 15 years). Accelerometers measured MVPA while sleep diaries measured sleep length. A linear and longitudinal mixed effect linear regression was conducted to study the primary aim. The secondary aims were studied with linear regressions. Included confounders were sex, school year, school stress, screen time, menstruation onset, family household economy, and health status. A stratified regression for sex and school year was conducted. The linear regression showed no statistically significant findings in the crude or adjusted model. The stratified linear regression found a significant positive association for girls but a negative association for school year 5. No associations were found in the longitudinal regression or when comparing sleep length for participants that did and did not spend an average of at least 60 min in MVPA/day. A dose-response relationship was found in the stratified linear regression, implying a possible weak association. The statistically non-significant differences between participants that did and did not spend an average of at least 60 min in MVPA/day implies that spending an average of at least 60 min in MVPA/day may not be associated with a higher mean sleep length.
Combined Transcriptome and Proteome Analysis of Maize (Zea mays L.) Reveals A Complementary Profile in Response to Phosphate Deficiency
Authors: Nie Zhi , Luo Bowen , Zhang Xiao , Wu Ling , Liu Dan , Guo Jialei , He Xuan , Gao Duojiang , Gao Shiqiang , Gao Shibin
Published: September 2021

A deficiency in the macronutrient phosphate (Pi) brings about various changes in plants at the morphological, physiological and molecular levels. However, the molecular mechanism for regulating Pi homeostasis in response to low-Pi remains poorly understood, particularly in maize (Zea mays L.), which is a staple crop and requires massive amounts of Pi. Therefore, in this study, we performed expression profiling of the shoots and roots of maize seedlings with Pi-tolerant genotype at both the transcriptomic and proteomic levels using RNA sequencing and isobaric tags for relative and absolute quantitation (iTRAQ). We identified 1944 differentially expressed transcripts and 340 differentially expressed proteins under low-Pi conditions. Most of the differentially expressed genes were clustered as regulators, such as transcription factors involved in the Pi signaling pathway at the transcript level. However, the more functional and metabolism-related genes showed expression changes at the protein level. Moreover, under low-Pi conditions, Pi transporters and phosphatases were specifically induced in the roots at both the transcript and protein levels, and increased amounts of mRNA and protein of two purple acid phosphatases (PAPs) and one UDP-sulfoquinovose synthase (SQD) were specifically detected in the roots. The new insights provided by this study will help to improve the P-utilization efficiency of maize.
Ensembles for Viticulture Climate Classifications of the Willamette Valley Wine Region
Authors: Skahill Brian , Berenguer Bryan , Stoll Manfred
Published: September 2021

Future climate projections provide an opportunity to evaluate cultivar climate classification and preferred styles of wine production for a wine grape growing region. However, ensemble selection must account for downscaled archive model skills and interdependence rather than be arbitrary and subjective. Relatedly, methods for generalizing climate model choice remain uncertain, particularly for identifying optimal ensemble subsets. In this study we consider the complete archive of the thirty-two Coupled Model Intercomparison Project Phase 5 (CMIP5) daily Localized Constructed Analogs (LOCA) downscaled historic datasets and their observational data that were used for downscaling and bias corrections. We apply four model averaging methods to determine optimal ensembles for the computation of six common climate classification indices for the Willamette Valley (WV) American Viticultural Area (AVA). Among the four methods evaluated, elastic-net regularization consistently performed best with identifying optimal ensemble subsets. Variation exists among the optimal ensembles computed for each of the six bioclimatic indices. However, a subset of approximately seven to ten climate models were consistently excluded across all six indices’ ensembles. While specific to the archive and wine region, optimal ensemble sizes were noticeably larger than ensemble sizes commonly employed in published studies. Results are reported such that they can be used by researchers to independently perform analyses involving any one of the six bioclimatic indices throughout the WV AVA while using historic and future LOCA CMIP5 climate projections. The data and methods employed herein are applicable for other wine regions.
Process Parameter Optimization and Characterization for an Edible Film: Flaxseed Concern
Authors: Bangar Sneh Punia , Singh Ajay , Trif Monica , Kumar Manoj , Kumar Pradyuman , Kaur Ramandeep , Kaur Navjeet
Published: September 2021

Consumer demands for biocompatible, minimally processed and eco-friendly foods have increased drastically and are currently trending. Polysaccharides derived from various plant seeds exhibiting structure conformational diversity are among such foods and used for the development of edible films. In this study, the physical properties of flaxseed, proximate characterization and rheological, mechanical and thermal features of flaxseed meal-based edible films were investigated. A development strategy worked through adding pectin + flaxseed meal to a plasticizer (glycerol) with a ratio of 7:3 w/v, whereas, in the control group, the flaxseed meal remained unaltered. The rheological results showed the non-Newtonian behavior of film-forming solutions and data were well fitted into the power law model. The developed film (flaxseed + pectin) was slightly brownish and exhibited a transparency of 17.78, which is clear enough to be used as see-through packaging material, whereas the control sample had a transparency of 38.25, indicating its fair transparency. The water vapor permeability of the test sample was also beneficial (0.992 g/cm2/24 h) and was competitively close to the control (0.981 g/cm2/24 h). The developed blended films were 98–99% soluble in water and acid, indicating their usefulness when applied as a coating. The mechanical properties, tensile strength and elongation value of the test sample were less than the control. This study will be helpful in the development of a novel biodegradable film for extending the life of different foods.
Vertical Graphene Growth on AlCu4Mg Alloy by PECVD Technique
Authors: Polzer Ales , Sedlak Josef , Sedlacek Jan , Benes Libor , Mouralova Katerina
Published: September 2021

Vertical graphene, which belongs to nanomaterials, is a very promising tool for improving the useful properties of long-used and proven materials. Since the growth of vertical graphene is different on each base material and has specific deposition setting parameters, it is necessary to examine each base material separately. For this reason, a full factor design of experiment was performed with 26 = 64 rounds, which contained additional 5 central points, i.e., a total of 69 rounds of individual experiments, which was to examine the effect of input factors Temperature, Pressure, Flow, CH4, Plasma Power, and Annealing in H2 on the growth of vertical graphene on aluminum alloy AlCu4Mg. The deposition was performed using plasma-enhanced chemical vapor deposition (PECVD) technology. Mainly, the occurrence of graphene was analyzed, which was confirmed by Raman spectroscopy, as well as its thickness. The characterization was performed using electron and transmission microscopy, including an atomic force microscope. It was found that the growth of graphene occurred in 7 cases and its thickness is affected only by the interaction flow (sccm) × pretreatment H2 (sccm).
Expression of Concern: Al-Baqami, N.M.; Hamza, R.Z. Protective Effect of Resveratrol against Hepatotoxicity of Cadmium in Male Rats: Antioxidant and Histopathological Approaches. Coatings 2021, 11, 594
Authors:   Coatings Editorial Office
Published: September 2021

Following acceptance of the Special Issue article by the Guest Editor, El-Sayed Abd El-Aziz, concerns were raised regarding the integrity of the peer review process [...]
A Facile Nitriding Approach for Improved Impact Wear of Martensitic Cold-Work Steel Using H2/N2 Mixture Gas in an AC Pulsed Atmospheric Plasma Jet
Authors: Guo Jhao-Yu , Kuo Yu-Lin , Wang Hsien-Po
Published: September 2021

In this study, we propose a rapid plasma-assisted nitriding process using H2/N2 mixture gas in an atmospheric pressure plasma jet (APPJ) system to treat the surface of SKD11 cold-working steel in order to increase its surface hardness. The generated NH radicals in the plasma region are used to implement an ion-bombardment for nitriding the tempered martensite structure of SKD11 within 18 min to form the functional nitride layer with an increased microhardness around 1095 HV0.3. Higher ratios of H/E and H3/E2 were obtained for the values of 4.514 × 10−2 and 2.244 × 10−2, referring to a higher deformation resistance as compared with the pristine sample. After multi-cycling impact tests, smaller and shallower impact craters with less surface oxidation on plasma-treated SKD11 were distinctly proven to have the higher impact wear resistance. Therefore, the atmospheric pressure plasma nitriding process can enable a rapid thermochemical nitriding process to form a protective layer with unique advantages that increase the deformation-resistance and impact-resistance, improving the lifetime of SKD11 tool steel as die materials.
An Experimental Study on Centrality Measures Using Clustering
Authors: Marjai Péter , Szabari Bence , Kiss Attila
Published: September 2021

Graphs can be found in almost every part of modern life: social networks, road networks, biology, and so on. Finding the most important node is a vital issue. Up to this date, numerous centrality measures were proposed to address this problem; however, each has its drawbacks, for example, not scaling well on large graphs. In this paper, we investigate the ranking efficiency and the execution time of a method that uses graph clustering to reduce the time that is needed to define the vital nodes. With graph clustering, the neighboring nodes representing communities are selected into groups. These groups are then used to create subgraphs from the original graph, which are smaller and easier to measure. To classify the efficiency, we investigate different aspects of accuracy. First, we compare the top 10 nodes that resulted from the original closeness and betweenness methods with the nodes that resulted from the use of this method. Then, we examine what percentage of the first n nodes are equal between the original and the clustered ranking. Centrality measures also assign a value to each node, so lastly we investigate the sum of the centrality values of the top n nodes. We also evaluate the runtime of the investigated method, and the original measures in plain implementation, with the use of a graph database. Based on our experiments, our method greatly reduces the time consumption of the investigated centrality measures, especially in the case of the Louvain algorithm. The first experiment regarding the accuracy yielded that the examination of the top 10 nodes is not good enough to properly evaluate the precision. The second experiment showed that the investigated algorithm in par with the Paris algorithm has around 45–60% accuracy in the case of betweenness centrality. On the other hand, the last experiment resulted that the investigated method has great accuracy in the case of closeness centrality especially in the case of Louvain clustering algorithm.
Photo-Excited Switchable Terahertz Metamaterial Polarization Converter/Absorber
Authors: Yu Dingwang , Dong Yanfei , Ruan Youde , Li Guochao , Li Gaosheng , Ma Haomin , Deng Song , Liu Zhenpeng
Published: September 2021

In this paper, a photo-excited switchable terahertz metamaterial (MM) polarization converter/absorber has been presented. The switchable structure comprises an orthogonal double split-ring resonator (ODSRR) and a metallic ground, separated by a dielectric spacer. The gaps of ODSRR are filled with semiconductor photoconductive silicon (Si), whose conductivity can be dynamically tuned by the incident pump beam with different power. From the simulated results, it can be observed that the proposed structure implements a wide polarization-conversion band in 2.01–2.56 THz with the conversion ratio of more than 90% and no pump beam power incident illuminating the structure, whereas two absorption peaks operate at 1.98 THz and 3.24 THz with the absorption rates of 70.5% and 94.2%, respectively, in the case of the maximum pump power. Equivalent circuit models are constructed for absorption states to provide physical insight into their operation. Meanwhile, the surface current distributions are also illustrated to explain the working principle. The simulated results show that this design has the advantage of the switchable performance afforded by semiconductor photoconductive Si, creating a path towards THz imaging, active switcher, etc.
New Radical-Cation Salts Based on the TMTTF and TMTSF Donors with Iron and Chromium Bis(Dicarbollide) Complexes: Synthesis, Structure, Properties
Authors: Chudak Denis M. , Kazheva Olga N. , Kosenko Irina D. , Shilov Gennady V. , Sivaev Igor B. , Abashev Georgy G. , Shklyaeva Elena V. , Buravov Lev I. , Pevtsov Dmitry N. , Starodub Tatiana N. , Bregadze Vladimir I. , Dyachenko Oleg A.
Published: September 2021

New radical-cation salts based on tetramethyltetrathiafulvalene (TMTTF) and tetramethyltetraselenefulvalene (TMsTSF) with metallacarborane anions (TMTTF)[3,3′-Cr(1,2-C2B9H11)2], (TMTTF)[3,3′-Fe(1,2-C2B9H11)2], and (TMTSF)2[3,3′-Cr(1,2-C2B9H11)2] were synthesized by electrocrystallization. Their crystal structures were determined by single crystal X-ray diffraction, and their electrophysical properties in a wide temperature range were studied. The first two salts are dielectrics, while the third one is a narrow-gap semiconductor: σRT = 5 × 10−3 Ohm−1cm−1; Ea ≈ 0.04 eV (aprox. 320 cm−1).
Investigation of a Separated Short-Wavelength Peak in InGaN Red Light-Emitting Diodes
Authors: Kirilenko Pavel , Zhuang Zhe , Iida Daisuke , Velazquez-Rizo Martin , Ohkawa Kazuhiro
Published: September 2021

We fabricated indium gallium nitride (InGaN) red light-emitting diodes (LEDs) with a peak emission wavelength of 649 nm and investigated their electroluminescence (EL) properties. An additional separated peak in the EL spectrum of the red LEDs at 20 mA was observed at 465 nm. This additional peak also exhibits a blue-shift with increasing currents as does the main emission peak. Using high-resolution microscopy, we observed many point-like emission spots in the EL emission images at the currents below 1 mA. However, these emission spots cannot be identified at currents above 5 mA because the red emission from quantum wells (QWs) is much stronger than that emitted by these spots. Finally, we demonstrate that these emission spots are related to the defects generated in red QWs. The measured In content was lower at the vicinity of the defects, which was regarded as the reason for separated short-wavelength emission in red InGaN LEDs.
Hydroxyapatite and Silicon-Modified Hydroxyapatite as Drug Carriers for 4-Aminopyridine
Authors: Marincaș Laura , Turdean Graziella Liana , Toșa Monica , Kovács Zsolt , Kovács Béla , Barabás Réka , Farkas Noémi-Izabella , Bizo Liliana
Published: September 2021

Adsorption and desorption properties of nano-hydroxyapatite (HAP) and silicon-modified hydroxyapatite (Si–HAP) were investigated with 4-aminopyridine (fampridine-4AP). The novelty of this research is the investigation of the suitability of the previously mentioned carriers for drug-delivery of 4AP. UV-VIS spectrophotometric results showed that the presence of silicon in the carrier did not significantly affect its adsorption capacity. The success of the adsorption was confirmed by thermal analysis (TG/DTA), scanning electron microscopy (SEM)/energy dispersive X-ray (EDX), Fourier transform infrared (FTIR) spectroscopy, and X-ray powder diffraction (XRPD). Drug release experiments, performed in simulated body fluid (SBF), revealed a drug release from Si–HAP that was five times slower than HAP, explained by the good chemical bonding between the silanol groups of the carrier and the 4AP functional groups. The electrochemical measurements showed a value of the polarization resistance of the charge transfer (Rct) more than five times smaller in the case of Si–HAP coating loaded with 4AP, so the charge transfer process was hindered. The electrochemical impedance results revealed that electron transfer was inhibited in the presence of 4AP, in concordance with the previously mentioned strong bonds. The silicon substitution in HAP leads to good chemical bonding with the drug and a slow release, respectively.
Could New Generations of Sensors Reshape the Management of Parkinson’s Disease?
Authors: Levin Oleg S. , Iakovleva Olga V. , Coloman Irina I. , Kuzmina Anastasia V.
Published: September 2021

Parkinson's disease (PD) is a chronic neurologic disease that has a great impact on the patient’s quality of life. The natural course of the disease is characterized by an insidious onset of symptoms, such as rest tremor, shuffling gait, bradykinesia, followed by improvement with the initiation of dopaminergic therapy. However, this “honeymoon period” gradually comes to an end with the emergence of motor fluctuations and dyskinesia. PD patients need long-term treatments and monitoring throughout the day; however, clinical examinations in hospitals are often not sufficient for optimal management of the disease. Technology-based devices are a new comprehensive assessment method of PD patient’s symptoms that are easy to use and give unbiased measurements. This review article provides an exhaustive overview of motor complications of advanced PD and new approaches to the management of the disease using sensors.
Forecasting FOMC Forecasts
Authors: Kalfa S. Yanki , Marquez Jaime
Published: September 2021

(Hendry 1980, p. 403) The three golden rules of econometrics are “test, test, and test”. The current paper applies that approach to model the forecasts of the Federal Open Market Committee over 1992–2019 and to forecast those forecasts themselves. Monetary policy is forward-looking, and as part of the FOMC’s effort toward transparency, the FOMC publishes its (forward-looking) economic projections. The overall views on the economy of the FOMC participants–as characterized by the median of their projections for inflation, unemployment, and the Fed’s policy rate–are themselves predictable by information publicly available at the time of the FOMC’s meeting. Their projections also communicate systematic behavior on the part of the FOMC’s participants.
Portuguese Primary and Secondary Education in Times of COVID-19 Pandemic: An Exploratory Study on Teacher Training and Challenges
Authors: Henriques Susana , Correia Joana Duarte , Dias-Trindade Sara
Published: September 2021

The discussion about the use of digital technologies in education is not new. However, the COVID-19 pandemic and the total closure of schools around the world, that forced millions of students to attend their classes from home, has demonstrated the importance of this discussion. It has highlighted the need to revisit debates about the interactions between technology and education, and the added value of digital resources to enhance the educational process. This article, based on an exploratory analysis, aims to understand how the transition from face-to-face to digital was accomplished in Portuguese primary and secondary education, namely regarding teacher training and the difficulties experienced during the emergency remote education period. The data analysed in this article were collected through an online questionnaire, disseminated through online social networks, and answered by 136 Portuguese primary and secondary education teachers. The questions focused on this article were open-ended, and the information collected was analysed using content analysis methodology. The results show how teachers have been forced to modify their pedagogical work, the importance of training, and the inherent challenges and critical reflections associated with the process, as well as the opportunities presented in a post-pandemic educational reality.
Lessons in the Use of Technology for Science Education during COVID-19 Age under a Teachers’ Collaboration Cluster
Authors: Delgado Francisco , Enríquez-Flores Marco , Jaimes-Nájera Alfonso
Published: September 2021

The COVID-19 confinement has represented both opportunities and losses for education. Rarely before has any other period moved the human spirit into such discipline or submission—depending on one’s personal and emotional points of view. Both extremes have been widely influenced by external factors on each individual’s life path. Education in the sciences and engineering has encountered more issues than other disciplines due to specialized mathematical handwriting, experimental demonstrations, abstract complexity, and lab practices. This work analyses three aspects of science education courses taught by university professors in a collaborative teacher cluster, sharing technology applications and education methodologies in science over three semesters when the COVID-19 lockdown was in effect. The first aspect was a didactic design coming from several educational frameworks through adoption or sharing. The second one was an analysis by discipline of multiple factors affecting student engagement during the health contingency. The third analysis examined the gains and losses in our students caused by the university closure and the pandemic’s intrusions. The report explores the correlations of the exiting student perceptions with their academic performance in the courses and survey results about the impact of decisions or happenings during the crisis. This work’s value lies in the lessons for the future of education concerning the teacher dominions of didactic design, support, and collaboration in a broader sense than only for teaching.
Implementation of a Thematic Analysis Method to Develop a Qualitative Model on the Authentic Foreign Language Learning Perspective: A Case Study in the University of Northern Cyprus
Authors: Mortazavi Mohsen , Davarpanah Afshin
Published: September 2021

Environmentally friendly occasions allow foreign language learners to further concentrate on realizing their extensive knowledge of the English language. Exercises and activities performed in foreign language classes have been criticized for a lack of authenticity, which prevents language learners from learning the real-life usage of language. In this paper, we developed a qualitative model based on the thematic analysis method (TAM) to distinguish the efficacy of research strategies. The number of participants was defined based on theoretical saturation. To collect the data, 18 participants were selected from the Eastern Mediterranean University (EMU) in Cyprus. The selection of participants was according to their involvement in research-based projects. Theoretical saturation occurred after 15 semi-structured interview forms from participants; however, we selected three extra participants to obtain more reliable results. The reliability of the qualitative model was explicitly illustrated by colleagues who were experts in this field by reviewing and analyzing the proposed model with previous models. It was concluded that the two principles of motivation (principle 11) and provision of collaborative opportunities (principle 4) had the highest frequencies, of 22.47% and 19.66%.
Supporting the Transition from Primary to Postprimary Education in 2021: Perspectives from Irish Postprimary Practitioners
Authors: O’Connor Hilary , Flynn Paul
Published: September 2021

The transition from primary to postprimary education is a significant milestone in children’s education and can be characterised by the multiple challenges that they experience, specifically the move from childhood to adolescence, from one institutional context to another, and from established social groups into new social relations. This research employs a theoretical framework that describes this transition from the perspective of secondary school inservice practitioners as they aim to help students to make a successful transition. An incremental, sequential mixed-methods data collection strategy took the form of an exploratory survey followed by qualitative semistructured interviews. Current transition practices in the context of the challenges presented in Irish secondary schools are reported on in five key areas: administration, social and emotional supports, curriculum support, pedagogical support, and management/autonomy of learning. The findings of this research also highlight a need to reflect on the purpose and timing of current practices, along with calls for continuing professional development programmes to be developed that specifically target the challenges faced by Irish inservice teaching practitioners. It is hoped that this paper will spark discourse relating to the development of transitional supports for students and associated training for those who are best placed to provide those supports.
W-band MIMO GB-SAR for Bridge Testing/Monitoring
Authors: Miccinesi Lapo , Consumi Tommaso , Beni Alessandra , Pieraccini Massimiliano
Published: September 2021

Interferometric radars are widely used for static and dynamic monitoring of large structures such as bridges, culverts, wind turbine towers, chimneys, masonry towers, stay cables, buildings, and monuments. Most of these radars operate in Ku-band (17 GHz). Nevertheless, a higher operative frequency could allow the design of smaller, lighter, and faster equipment. In this paper, a fast MIMO-GBSAR (Multiple-Input Multiple-Output Ground-Based Synthetic Aperture Radar) operating in W-band (77 GHz) has been proposed. The radar can complete a scan in less than 8 s. Furthermore, as its overall dimension is smaller than 230 mm, it can be easily fixed to the head of a camera tripod, which makes its deployment in the field very easy, even by a single operator. The performance of this radar was tested in a controlled environment and in a realistic case study.
An Eleven-Level Switched-Capacitor Inverter with Boosting Capability
Authors: Hussan Md Reyaz , Sarwar Adil , Khan Irfan , Tariq Mohd , Tayyab Mohammad , Alhosaini Waleed
Published: September 2021

An 11-level switched-capacitor multilevel inverter (SCMLI) with 2.5 times boosting feature is presented in this paper. It can produce an 11-level output voltage waveform by utilizing 14 switches, 3 capacitors, 2 diodes, and 1 DC source. Only nine driver circuits are needed as the topology has three pairs of complementary switches and two bidirectional switches. It has inherent capacitor self-balancing property as the capacitors are connected across the DC voltage source during several states within a fundamental cycle to charge the capacitors to the input voltage. A detailed comparison shows the effectiveness of the proposed topology in terms of the number of switches, number of capacitors, number of sources, total standing voltage (TSV), efficiency, and boosting ability with the state-of-art recently proposed circuits. Subsequently, the performance of the proposed SCMLI is validated experimentally utilizing the nearest level control (NLC), a fundamental frequency-based switching technique.
Person Re-Identification Microservice over Artificial Intelligence Internet of Things Edge Computing Gateway
Authors: Chen Ching-Han , Liu Chao-Tsu
Published: September 2021

With the increase in the number of surveillance cameras being deployed globally, an important topic is person re-identification (Re-ID), which identifies the same person from multiple different angles and different directions across multiple cameras. However, because of the privacy issues involved in the identification of individuals, Re-ID systems cannot send the image data to cloud, and these data must be processed on edge servers. However, there has been a significant increase in computing resources owing to the processing of artificial intelligence (AI) algorithms through edge computing (EC). Consequently, the traditional AI Internet of Things (AIoT) architecture is no longer sufficient. In this study, we designed a Re-ID system at the AIoT EC gateway, which utilizes a microservice to perform Re-ID calculations on EC and balances efficiency with privacy protection. Experimental results indicate that this architecture can provide sufficient Re-ID computing resources to allow the system to scale up or down flexibly to support different scenarios and demand loads.
The Potential of Variable Renewable Energy Sources in Mexico: A Temporally Evaluated and Geospatially Constrained Techno-Economical Assessment
Authors: Peña Sánchez Edgar Ubaldo , Ryberg Severin David , Heinrichs Heidi Ursula , Stolten Detlef , Robinius Martin
Published: September 2021

Due to the increasing global importance of decarbonizing human activities, especially the production of electricity, the optimal deployment of renewable energy technologies will play a crucial role in future energy systems. To accomplish this, particular attention must be accorded to the geospatial and temporal distribution of variable renewable energy sources (VRES), such as wind and solar radiation, in order to match electricity supply and demand. This study presents a techno-economical assessment of four energy technologies in the hypothetical context of Mexico in 2050, namely: onshore and offshore wind turbines and open-field and rooftop photovoltaics. A land eligibility analysis incorporating physical, environmental, and sociopolitical eligibility constraints and individual turbine and photovoltaic park simulations, drawing on 39 years of climate data, is performed for individual sites across the country in an effort to determine the installable potential and the associated levelized costs of electricity. The results reveal that up to 54 PWh of renewable electricity can be produced at a levelized cost of electricity of less than 70 EUR·MWh−1. Around 91% (49 PWh) of this electricity would originate from 23 TW of open-field photovoltaic parks that could occupy up to 578,000 km2 of eligible land across the country. The remaining 9% (4.8 PWh) could be produced by 1.9 TW of onshore wind installations allocated to approximately 68,500 km2 of eligible land that is almost fully adjacent to three mountainous zones. The combination of rooftop photovoltaic and offshore wind turbines accounts for a very small share of less than 0.03% of the overall techno-economical potential.
Power Enhancement of a Vertical Axis Wind Turbine Equipped with an Improved Duct
Authors: Ranjbar Mohammad Hassan , Rafiei Behnam , Nasrazadani Seyyed Abolfazl , Gharali Kobra , Soltani Madjid , Al-Haq Armughan , Nathwani Jatin
Published: September 2021

Efforts to increase the power output of wind turbines include Diffuser Augmented Wind Turbines (DAWT) or a shroud for the rotor of a wind turbine. The selected duct has three main components: a nozzle, a diffuser, and a flange. The combined effect of these components results in enriched upstream velocity for the rotor installed in the throat of the duct. To obtain the maximum velocity in the throat of the duct, the optimum angles of the three parts have been analyzed. A code was developed to allow all the numerical steps including changing the geometries, generating the meshes, and setting up the numerical solver simultaneously. Finally, the optimum geometry of the duct has been established that allows a doubling of the flow velocity. The flow characteristics inside the duct have also been analyzed in detail. An H-Darrieus Vertical Axis Wind Turbine (VAWT) has been simulated inside the optimized duct. The results show that the power coefficient of the DAWT can be enhanced up to 2.9 times. Deep dynamic stall phenomena are captured perfectly. The duct advances the leading-edge vortex generation and delays the vortex separation.
Optimal Allocation for Electric Vehicle Charging Stations
Authors: Lee Jiwon , An Midam , Kim Yongku , Seo Jung-In
Published: September 2021

Currently, more than 30% of the fine dust generated in the Seoul metropolitan area is a pollutant emitted from automobiles such as diesel vehicles, and air pollution caused by this is becoming increasingly serious. In addition, the importance of electric vehicle distribution is increasing due to the strengthening of international environmental regulations on automobile exhaust gas and increasing the possibility of depletion of petroleum resources. This manuscript proposes a method for selecting an optimal electric vehicle charging station location in expanding charging facilities to activate electric vehicle distribution. For the sake of illustration, directions will be provided on how to select the best location for electric vehicle charging stations using data from Seoul, which has the best access. As the features, the number of living population and work force people and the number of guest facilities, which are determined to affect demand for quick charging, are considered. The missing values of the observed data are imputed based on the kriging technique from spatial correlation, and by segmenting the data through clustering, a representative technique of unsupervised learning, the characteristics of each cluster are examined and the characteristics of the clusters are identified. In addition, machine learning techniques such as the elastic net, random forest, support vector machine, and extreme gradient boosting are applied to examine the influence of the features used in predicting classes of data. In clustering analysis, the optimal number of clusters was determined to be 3 based on the heuristic and information-theoretic methods, and all the machine learning techniques considered showed that the number of work force population is the most important feature in predicting classes of data. All things considered from our results, it is reasonable to install quick electric vehicle charging stations in the places with the highest concentration of work force population and guest facility.
Forecasting Natural Gas Spot Prices with Machine Learning
Authors: Mouchtaris Dimitrios , Sofianos Emmanouil , Gogas Periklis , Papadimitriou Theophilos
Published: September 2021

The ability to accurately forecast the spot price of natural gas benefits stakeholders and is a valuable tool for all market participants in the competitive gas market. In this paper, we attempt to forecast the natural gas spot price 1, 3, 5, and 10 days ahead using machine learning methods: support vector machines (SVM), regression trees, linear regression, Gaussian process regression (GPR), and ensemble of trees. These models are trained with a set of 21 explanatory variables in a 5-fold cross-validation scheme with 90% of the dataset used for training and the remaining 10% used for testing the out-of-sample generalization ability. The results show that these machine learning methods all have different forecasting accuracy for every time frame when it comes to forecasting natural gas spot prices. However, the bagged trees (belonging to the ensemble of trees method) and the linear SVM models have superior forecasting performance compared to the rest of the models.
Steady-State Stand-Alone Power Flow Solvers for Integrated Transmission-Distribution Networks: A Comparison Study and Numerical Assessment
Authors: Kootte Maria Eliza , Vuik Cornelis
Published: September 2021

This paper compares and assesses several numerical methods that solve the steady-state power flow problem on integrated transmission-distribution networks. The integrated network model consists of a balanced transmission and an unbalanced distribution network. It is important to analyze these integrated electrical power systems due to the changes related to the energy transition. We classified the existing integration methods as unified and splitting methods. These methods can be applied to homogeneous (complete three-phase) and hybrid (single-phase/three-phase) network models, which results in four approaches in total. These approaches were compared on their accuracy and numerical performance—CPU time and number of iterations—to demonstrate their applicability on large-scale electricity networks. Furthermore, their sensitivity towards the amount of distributed generation and the addition of multiple distribution feeders was investigated. The methods were assessed by running power flow simulations using the Newton–Raphson method on several integrated power systems up to 25,000 unknowns. The assessment showed that unified methods applied to hybrid networks performed the best on these test cases. The splitting methods are advantageous when complete network data sharing between system operators is not allowed. The use of high-performance techniques for larger test cases containing multiple distribution networks will make the difference in speed less significant.
Impact Investing in Digital Business Models
Authors: Jabłoński Adam , Jabłoński Marek
Published: September 2021

In recent years, the role of digital enterprises in the global economy has been growing. The issue of assessing their impact on social aspects is noticeable. The aim of the article is to show social impact as a key factor in the development of digital business models. The Analytic Hierarchy Process (AHP) method used and the criteria for social impact assessments based on heuristic methods allowed for the components of business models that relate to social impact to be ranked, and subsequently for socially oriented enterprises functioning in the digital economy to be ranked. The companies selected for the research are understood by the authors as digital business models, the concept of which is embedded in a pro-social management intention. Purposive sampling, which in this situation was considered to be the most effective in terms of the objective of the paper, was applied. The literature review, analyses and heuristic research have demonstrated that the social factor in modern applications is a driver of value creation and is conducive to social profit. The ranking of the criteria responsible for shaping the social impact of digital business models showed that the most important ones are value proposition (pro-social), social profit and economic profit. This means a strong relationship between social and economic aspects.
Energy Monitoring in the Wild: Platform Development and Lessons Learned from a Real-World Demonstrator
Authors: Quintal Filipe , Garigali Daniel , Vasconcelos Dino , Cavaleiro Jonathan , Santos Wilson , Pereira Lucas
Published: September 2021

This paper presents the development and evaluation of EnnerSpectrum, a platform for electricity monitoring. The development was motivated by a gap between academic, fully custom-made monitoring solutions and commercial proprietary monitoring approaches. EnnerSpectrum is composed of two main entities, the back end, and the Gateway. The back end is a server comprised of flexible entities that can be configured to different monitoring scenarios. The Gateway interacts with equipment at a site that cannot interact directly with the back end. The paper presents the architecture and configuration of EnnerSpectrum for a long-term case study with 13 prosumers of electricity for approximately 36 months. During this period, the proposed system was able to adapt to several building and monitoring conditions while acquiring 95% of all the available consumption data. To finalize, the paper presents a set of lessons learned from running such a long-term study in the real world.
Sustainable Consumption in Consumer Behavior in the Time of COVID-19: Topic Modeling on Twitter Data Using LDA
Authors: Brzustewicz Paweł , Singh Anupam
Published: September 2021

By using text mining techniques, this study identifies the topics of sustainable consumption that are important during the COVID-19 pandemic. An Application Programming Interface (API) streaming method was used to extract the data from Twitter. A total of 14,591 tweets were collected using Twitter streaming API. However, after data cleaning, 13,635 tweets were considered for analysis. The objectives of the study are to identify (1) the topics users tweet about sustainable consumption and (2) to detect the emotion-based sentiments in the tweets. The study used Latent Dirichlet Allocation (LDA) algorithm for topic modeling and the Louvain algorithm for semantic network clustering. NRC emotion lexicon was used for sentiment analysis. The LDA model discovers six topics: organic food consumption, food waste, vegan food, sustainable tourism, sustainable transport, and sustainable energy consumption. While the Louvain algorithm detects four clusters—lifestyle and climate change, responsible consumption, energy consumption, and renewable energy, sentiment analysis results show more positive emotions among the users than the negative ones. The study contributes to existing literature by providing a fresh perspective on various interconnected topics of sustainable consumption that bring global consumption to a sustainable level.
Evaluation of Subsurface Heat Capacity through Oscillatory Thermal Response Tests
Authors: Giordano Nicolò , Lamarche Louis , Raymond Jasmin
Published: September 2021

Two methods are currently available to estimate in a relatively short time span the subsurface heat capacity: (1) laboratory analysis of rock/soil samples; (2) measure the heat diffusion with temperature sensors in an observation well. Since the first may not be representative of in-situ conditions, and the second imply economical and logistical issues, a third option might be possible by means of so-called oscillatory thermal response tests (OTRT). The aim of the study was to evaluate the effectiveness of an OTRT as a tool to infer the subsurface heat capacity without the need of an observation well. To achieve this goal, an OTRT was carried out in a borehole heat exchanger (BHE). The total duration of injection was 6 days, with oscillation period of 12 h and amplitude of 10 W m−1. The results of the proposed methodology were compared 3-D numerical simulations and to a TRT with a constant heat injection rate with temperature response monitored from a nearby observation well. Results show that the OTRT succeeded to infer the expected subsurface heat capacity, but uncertainty is about 15% and the radial depth of penetration is only 12 cm. The parameters having most impact on the results are the subsurface thermal conductivity and the borehole thermal resistance. The OTRT performed and analyzed in this study also allowed to evaluate the thermal conductivity with similar accuracy compared to conventional TRTs (3%). On the other hand, it returned borehole thermal resistance with high uncertainty (15%), in particular due to the duration of the test. The final range of heat capacity is wide, highlighting challenges to currently use OTRT in the scope of ground-coupled heat pump system design. OTRT appears a promising tool to evaluate the heat capacity, but more field testing and mathematical interpretation of the sinusoidal response is needed to better isolate the subsurface from the BHE contribution and reduce the uncertainty.
Cash Flow Optimization for Renewable Energy Construction Projects with a New Approach to Critical Chain Scheduling
Authors: Kulejewski Janusz , Ibadov Nabi , Rosłon Jerzy , Zawistowski Jacek
Published: September 2021

This study concerns the use of the critical chain method to schedule the construction of renewable energy facilities. The critical chain method is recognized as a useful project management tool, transforming a stochastic problem of uncertainty in activity durations into a deterministic one. However, this method has some shortcomings. There are no clear principles of grouping non-critical activities into feeding chains. Another ambiguity is sizing the feeding buffers with regard to the topology of the network model and the resulting dependencies between activities, located in different chains. As a result, it is often necessary to arbitrarily adjust the calculated sizes of feeding buffers before inserting them into the schedule. The authors present the new approach to sizing the time buffers in the schedule, enabling a quick assessment of the quality of a given solution variant and finding a solution that best meets the established criteria, conditions, and constraints. The essence of the presented approach is the two-step sizing of time buffers with the use of deterministic optimization and stochastic optimization techniques. Taking into account construction management needs, the optimization criteria are based on the construction project cash flow analysis. The effectiveness of the presented approach is illustrated by an example of developing a wind power plant construction schedule. According to the results, the presented approach ensures the protection of the scheduled completion date of the construction and the stability of the schedule.