bluuebunny/crossref_metadata_2025 huggingface dataset:
UV-Responsive Screen-Printed Porous ZnO Nanostructures on Office Paper for Sustainable and Foldable Electronics
Authors: Ferreira Sofia Henriques , Cunha Inês , Pinto Joana Vaz , Neto Joana Pereira , Pereira Luís , Fortunato Elvira , Martins Rodrigo
Published: July 2021

The fabrication of low-cost, flexible, and recyclable electronic devices has been the focus of many research groups, particularly for integration in wearable technology and the Internet of Things (IoT). In this work, porous zinc oxide (ZnO) nanostructures are incorporated as a UV sensing material into the composition of a sustainable water-based screen-printable ink composed of carboxymethyl cellulose (CMC). The formulated ink is used to fabricate flexible and foldable UV sensors on ubiquitous office paper. The screen-printed CMC/ZnO UV sensors operate under low voltage (≤2 V) and reveal a stable response over several on/off cycles of UV light exposure. The devices reach a response current of 1.34 ± 0.15 mA and a rise and fall time of 8.2 ± 1.0 and 22.0 ± 2.3 s, respectively. The responsivity of the sensor is 432 ± 48 mA W−1, which is the highest value reported in the literature for ZnO-based UV sensors on paper substrates. The UV-responsive devices display impressive mechanical endurance under folding, showing a decrease in responsivity of only 21% after being folded 1000 times. Their low-voltage operation and extreme folding stability indicate a bright future for low-cost and sustainable flexible electronics, showing potential for low-power wearable applications and smart packaging.
Renal Involvement in Children with Type 2 Diabetes Mellitus Onset: A Pilot Study
Authors: Marzuillo Pierluigi , Di Sessa Anna , Palma Pier Luigi , Umano Giuseppina Rosaria , Polito Cesare , Iafusco Dario , Guarino Stefano , Miraglia del Giudice Emanuele
Published: July 2021

Type 2 Diabetes Mellitus (T2DM) is a main cause of chronic kidney disease (CKD) in adulthood. No studies have examined the occurrence of acute kidney injury (AKI)—that enhances the risk of later CKD—and renal tubular damage (RTD)—that can evolve to AKI—in children with onset of T2DM. We aimed to evaluate the prevalence and possible features of AKI and RTD in a prospectively enrolled population of children with onset of T2DM. We consecutively enrolled 10 children aged 12.9 ± 2.3 years with newly diagnosed T2DM. AKI was defined according to the KDIGO criteria. RTD was defined by abnormal urinary beta-2-microglobulin and/or tubular reabsorption of phosphate (TRP) <85% and/or fractional excretion of Na >2%. None of the patients developed AKI, whereas 3/10 developed RTD with high beta-2-microglobulin levels (range: 0.6–1.06 mg/L). One of these three patients also presented with reduced TRP levels (TRP = 70%). Proteinuria was observed in two out of three patients with RTD, while none of patients without RTD had proteinuria. Patients with RTD presented higher beta-2-microglobulin, acute creatinine/estimated basal creatinine ratio, and serum ketones levels compared with patients without RTD. In conclusion, in our pilot observation, we found that none of the 10 children with T2DM onset developed AKI, whereas three of them developed RTD.
Bituminous Pavement Reinforcement with Fiber: A Review
Authors: Mashaan Nuha , Karim Mohamed , Khodary Farag , Saboo Nikhil , Milad Abdalrhman
Published: July 2021

This paper attempts to display, analyze and discuss the literature affiliated to the previous research data on road surfacing in pavement engineering reinforcement. In this paper, a review of the background and present status of road surfacing is also provided for supportive explanation of the significance of fiber-reinforced asphalt pavement HMA and its role in providing effective and durable surfacing for heavy-trafficked roads. The paper attempts to clarify some of the terms and notions related to the discussions to give the readers the needed background, to be able to actively understand the experiments and discussions. Results from many studies confirm that fiber specifically enhances the optimum bitumen content in the design of the mixture and halts the bitumen leakage due to its asphalt absorbing susceptibility. Fiber modifies the visco-elastic response, susceptibility against moisture, increase resistance to rutting, as well as lowers the pavement fatigue cracking.
Investigation of Performance and Emission Parameters of Hydroxygen (HHO)-Enriched Diesel Fuel with Water Injection in the Compression Ignition Engine
Authors: Juknelevičius Romualdas , Rimkus Alfredas , Pukalskas Saugirdas , Szwaja Stanislaw
Published: July 2021

The development of engine technologies and research on combustion processes are focused on finding new generation CI engines with simple control of the combustion process while efficiently maintaining desirable engine performance and meeting emission regulations. This comprehensive study on the relatively low hydrogen energy fraction (0.65–1.80%), supplied by onboard water electrolysers and on water injection, was performed on the performance and emission parameters of the CI engine. The article presents results of both experiment and simulation about the effect of hydroxygen and water injection on the combustion process, auto-ignition delay, combustion intensity, the temperature of the mixture and engine performance at BMEP of 0.2 MPa, 0.4 MPa, 0.6 MPa, and 0.8 MPa at a speed of 1900 rpm. For the first part, the test engine operated with diesel fuel with 3.5 L/min of hydroxygen gas supplied with an external mixture formation. The HHO has an effect on the combustion process at all range of BMEP. A decrease in BTE and increase in BSFC were noticed during tests. The peak pressure and the rate of heat release decreased, but the NOx decreased as well. The second part of experiment was performed with the injection of a substantial amount of water, 8.4–17.4 kg/h (140–290 cm3/min), and the same amount of hydroxygen. The injection of water further decreased the NOx; therefore, HHO and WI can be used to meet emission regulations. A simulation of the combustion process was carried out with the AVL BOOST sub-program BURN. The AVL BOOST simulation provided a detailed view of the in-cylinder pressure, pressure-rise, combustion intensity shape parameter and SOC.
Study on the Characteristics of a TBC System Containing a PVD-Al Interlayer under Isothermal Loading
Authors: Ali Ibrahim , Sokołowski Paweł , Pawłowski Lech , Wett Daniel , Grund Thomas , Lampke Thomas
Published: July 2021

In this work, the oxidation behavior of an atmospheric plasma-sprayed thermal barrier coating (TBC) system with a thin Al physical vapor deposition (PVD) film deposited over the bond coat is discussed. The TBC consisted of: (i) CoNiCrAlY bond coat sprayed on the Inconel 600 substrate; (ii) a thin Al interlayer deposited by direct current DC magnetron sputtering; and (iii) yttria-stabilized zirconia (YSZ) sprayed as the top coat. Such thermal barrier coatings (Al-TBC) were isothermally oxidized at 1150 °C with different holding times, and then they were compared with the reference TBC (R-TBC) systems without an Al interlayer (R-TBC). Scanning electron microscopy with energy-dispersive X-ray analysis was used to study the oxide formation along the bond coat (BC) and top coat (TC) interface, as well as crack formation in the yttria-stabilized zirconia top coat. Then, using Image Analysis, the oxide formation and crack formation were characterized in all specimens after a slow heating and cooling cycle, and after 100, 300, and 600 h of isothermal exposure. The results showed that the Al-TBC system proposed here exhibits higher oxidation resistance at the bond coat and top coat interface, less crack formation in the YSZ top coat, and enhanced mechanical stability compared to the conventional TBCs. It was found that enrichment of the bond coat and top coat interface with Al limited the formation of detrimental transition metal oxides during isothermal loading. Finally, the corresponding failure caused by thermally grown oxide (TGO) phenomena is “mixed failure mode” for both studied TBCs.
Effect of Hot Working Processes on Microstructure and Mechanical Properties of Pipeline Steel
Authors: Ji Huiling , Zhang Yiwei , Lu Wenzhao , Wei Bang , Yuan Xiaomin
Published: July 2021

The microstructure and microhardness of X70 pipeline steel were investigated after conducting different processing routes. The microstructure was characterized using optical and electron microscopy. Scanning electron microscopy equipped with electron backscattered diffraction (EBSD) and transmission electron microscopy techniques were applied for investigation of different thermal processing treatment conditions. Mechanical properties were characterized by a microhardness tester. The results show that the microstructure mainly consists of granular bainite, acicular ferrite and a small amount of M/A constituents under hot rolling states. There are many dislocations inside the acicular ferrite. The thermal simulation experiments show that the microstructure becomes homogeneous with the increase in cooling rate. The acicular ferrite morphology becomes fine and uniform, and the content of M/A constituents increases at the same compression amount. The compression gives rise to the accumulated strain and stored energy, which accelerate the transformation of acicular ferrite and refine the microstructure of the pipeline steel. The microhardness rises with the increase in deformation ratio and cooling rate. The microstructure of the pipeline steel subjected to the isothermal quenching process is ultrafine ferrite and M/A islands. When the isothermal quenching temperature reaches 550 °C, a small amount of upper bainite appears in the microstructure. With the increase in isothermal quenching temperature, the microhardness decreases. Acicular ferrite is a better candidate microstructure than ultrafine ferrite for the pipeline steels.
The Extreme Values of Young’s Modulus and the Negative Poisson’s Ratios of Rhombic Crystals
Authors: Gorodtsov Valentin A. , Lisovenko Dmitry S.
Published: July 2021

The extreme values of Young’s modulus for rhombic (orthorhombic) crystals using the necessary and sufficient conditions for the extremum of the function of two variables are analyzed herein. Seven stationary expressions of Young’s modulus are obtained. For three stationary values of Young’s modulus, simple analytical dependences included in the sufficient conditions for the extremum of the function of two variables are revealed. The numerical values of the stationary and extreme values of Young’s modulus for all rhombic crystals with experimental data on elastic constants from the well-known Landolt-Börnstein reference book are calculated. For three stationary values of Young’s modulus of rhombic crystals, a classification scheme based on two dimensionless parameters is presented. Rhombic crystals ((CH3)3NCH2COO·(CH)2(COOH)2, I, SC(NH2)2, (CH3)3NCH2COO·H3BO3, Cu-14 wt%Al, 3.0wt%Ni, NH4B5O8·4H2O, NH4HC2O4·1/2H2O, C6N2O3H6 and CaSO4) having a large difference between maximum and minimum Young’s modulus values were revealed. The highest Young’s modulus among the rhombic crystals was found to be 478 GPa for a BeAl2O4 crystal. More rigid materials were revealed among tetragonal (PdPb2; maximum Young’s modulus, 684 GPa), hexagonal (graphite; maximum Young’s modulus, 1020 GPa) and cubic (diamond; maximum Young’s modulus, 1207 GPa) crystals. The analytical stationary values of Young’s modulus for tetragonal, hexagonal and cubic crystals are presented as special cases of stationary values for rhombic crystals. It was found that rhombic, tetragonal and cubic crystals that have large differences between their maximum and minimum values of Young’s modulus often have negative minimum values of Poisson’s ratio (auxetics). We use the abbreviated term auxetics instead of partial auxetics, since only the latter were found. No similar relationship between a negative Poisson’s ratio and a large difference between the maximum and minimum values of Young’s modulus was found for hexagonal crystals.
AgSn[Bi1−xSbx]Se3: Synthesis, Structural Characterization, and Electrical Behavior
Authors: Valencia-Gálvez Paulina , Delgado Daniela , López María Luisa , Álvarez-Serrano Inmaculada , Moris Silvana , Galdámez Antonio
Published: July 2021

Herein, we report the synthesis, characterization, and electrical properties of lead-free AgSnm[Bi1−xSbx]Se2+m (m = 1, 2) selenides. Powder X-ray diffraction patterns and Rietveld refinement data revealed that these selenides consisted of phases related to NaCl-type crystal structure. The microstructures and morphologies of the selenides were investigated by backscattered scanning electron microscopy, energy-dispersive X-ray spectroscopy, and high-resolution transmission electron microscopy. The studied AgSnm[Bi1−xSbx]Se2+m systems exhibited typical p-type semiconductor behavior with a carrier concentration of approximately ~+1020 cm−3. The electrical conductivity of AgSnm[Bi1−xSbx]Se2+m decreased from ~3.0 to ~10−3 S·cm−1 at room temperature (RT) with an increase in m from 1 to 2, and the Seebeck coefficient increased almost linearly with increasing temperature. Furthermore, the Seebeck coefficient of AgSn[Bi1−xSbx]Se3 increased from ~+36 to +50 μV·K−1 with increasing Sb content (x) at RT, while its average value determined for AgSn2[Bi1−xSbx]Se4 was approximately ~+4.5 μV·K−1.
Supportive Management of Patients with Advanced Pheochromocytomas and Paragangliomas Receiving PRRT
Authors: Tsang Erica S. , Funk Gayle , Leung Janet , Kalish Grace , Kennecke Hagen F.
Published: July 2021

Peptide receptor radionuclide therapy (PRRT) is used to treat patients with advanced malignant pheochromocytomas (PCCs) and paragangliomas (PGLs). Patients are at risk of a PRRT-induced catecholamine crisis, and standard guidelines regarding the prevention and management of infusion reactions are lacking. In this case series, the institutional experience of five sequential patients with metastatic PCCs and PGLs receiving PRRT on an outpatient basis is described, of which four had symptomatic tumors and three had a high burden of disease. All patients with symptomatic tumors were treated with preventive management prior to the initiation of PRRT, and no infusion reactions or catecholamine crises were documented. PRRT may be delivered safely on an outpatient basis for patients with metastatic PCCs and PGLs with the involvement of an interdisciplinary team.
Temporal Changes in Delaware Waters Using Long-Term (1967–2019) Water Temperature Data
Authors: Paudel Bhanu , Brown Lori M.
Published: July 2021

The present article provides long-term (1967–2019) water temperature data collected from Delaware water quality monitoring sites. In Delaware, there are approximately 140 water quality monitoring sites in Piedmont, Delaware Bay, Chesapeake Bay, and Inland Bay drainage basins. Long-term quarterly (i.e., four times a year: Q1—January–February–March; Q2—April–May–June; Q3—July–August–September; Q4—October–November–December) water temperature data were calculated from each water quality monitoring sites’ continuous monthly data. This study focuses on water quality monitoring sites with significant (p-value identifying linear regression model) increasing or decreasing trends of water temperature. Quarterly water temperature data, statistical analysis, and maps showing increasing and decreasing trend from water quality monitoring sites with significant trends are presented in this article.
The Value of Interleukin-6 among Several Inflammatory Markers as a Predictor of Respiratory Failure in COVID-19 Patients
Authors: Fujino Mitsuhiro , Ishii Michiyo , Taniguchi Takuya , Chiba Hiroya , Kimata Masaki , Hitosugi Masahito
Published: July 2021

Patients with coronavirus disease 2019 (COVID-19) develop severe respiratory failure within a short period during the clinical course. It is essential to predict respiratory deterioration in the short term. We investigated the use of inflammatory markers to predict respiratory distress within three days from their analysis in COVID-19 patients. This retrospective observational study included 81 patients admitted with COVID-19. Patients were divided into two groups according to whether the maximum fraction of inspired oxygen (FiO2) for three days from the blood marker measurements was ≥0.4 (high FiO2 group; HFG) or <0.4 (low FiO2 group; LFG). Interleukin-6 (IL-6), C-reactive protein (CRP), lactate dehydrogenase (LDH), white blood cell, D-dimer, and creatinine levels were compared between the two groups. The levels of all markers were significantly higher in HFG patients. Areas under the receiver operating characteristic curve of IL-6, CRP, and LDH had high values of 0.85, 0.82, and 0.81, respectively. The odds ratio of IL-6 which was crude and adjusted for dexamethasone administration initiated before laboratory measurement, showed the high value of 29.1 (5.6–295.6) and 53.9 (4.5–3242.8), respectively. IL-6 can be used as a reliable marker for predicting respiratory illness within three days after assessment.
Reduction in Pulse Pressure during Standing Can Distinguish Neurogenic Orthostatic Hypotension
Authors: Jung Kyu-On , Heo Deok-Hyun , Lee Eek-Sung , Lee Tae-Kyeong
Published: July 2021

Background: We investigated whether changes in the pulse pressure (PP) reduction ratio during the head-up tilt test (HUTT) can aid in distinguishing neurogenic orthostatic hypotension (OH) from non-neurogenic OH. Methods: We enrolled consecutive patients with NOH and non-neurogenic OH between January 2015 and October 2018. We compared the Valsalva ratio, the presence or absence of late phase II and IV overshoot, the pressure recovery time, and the PP reduction ratio during HUTT between the two OH groups. Results: The expiratory–inspiratory (E:I) ratio and Valsalva ratio were significantly decreased in the NOH group (p = 0.026, p < 0.001, respectively). The absence of late phase II and phase IV overshoot was more frequent in the NOH group than in the non-neurogenic OH group (p = 0.001, p < 0.001, respectively). The pressure recovery time was significantly prolonged in the NOH group (p < 0.001), which exhibited increases in the PP reduction ratio (1—minimal PP/baseline PP) during the HUTT (p < 0.001). We calculated the cutoff point for the PP reduction ratio during HUTT, which exhibited an area under the receiver operating characteristic curve of 0.766 (0.659–0.840, 95% confidence interval). The cutoff value for the PP reduction ratio during HUTT (0.571) exhibited sensitivity of 0.879 and specificity of 0.516. Conclusions: Increases in the PP reduction ratio during HUTT may be a meaningful NOH laboratory marker.
Plotting the Words of Econophysics
Authors: Tusset Gianfranco
Published: July 2021

Text mining is applied to 510 articles on econophysics to reconstruct the lexical evolution of the discipline from 1999 to 2020. The analysis of the relative frequency of the words used in the articles and their “visualization” allow us to draw some conclusions about the evolution of the discipline. The traditional areas of research, financial markets and distribution of wealth, remain central, but they are flanked by other strands of research—production, currencies, networks—which broaden the discipline by pushing towards a dialectical application of traditional concepts and tools drawn from statistical physics.
Statistical Approach of Gene Set Analysis with Quantitative Trait Loci for Crop Gene Expression Studies
Authors: Das Samarendra , Rai Shesh N.
Published: July 2021

Genome-wide expression study is a powerful genomic technology to quantify expression dynamics of genes in a genome. In gene expression study, gene set analysis has become the first choice to gain insights into the underlying biology of diseases or stresses in plants. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results from the primary downstream differential expression analysis. The gene set analysis approaches are well developed in microarrays and RNA-seq gene expression data analysis. These approaches mainly focus on analyzing the gene sets with gene ontology or pathway annotation data. However, in plant biology, such methods may not establish any formal relationship between the genotypes and the phenotypes, as most of the traits are quantitative and controlled by polygenes. The existing Quantitative Trait Loci (QTL)-based gene set analysis approaches only focus on the over-representation analysis of the selected genes while ignoring their associated gene scores. Therefore, we developed an innovative statistical approach, GSQSeq, to analyze the gene sets with trait enriched QTL data. This approach considers the associated differential expression scores of genes while analyzing the gene sets. The performance of the developed method was tested on five different crop gene expression datasets obtained from real crop gene expression studies. Our analytical results indicated that the trait-specific analysis of gene sets was more robust and successful through the proposed approach than existing techniques. Further, the developed method provides a valuable platform for integrating the gene expression data with QTL data.
Improving Perceived Quality of Live Adaptative Video Streaming
Authors: Santos Carlos Eduardo Maffini , da Silva Carlos Alexandre Gouvea , Pedroso Carlos Marcelo
Published: July 2021

Quality of service (QoS) requirements for live streaming are most required for video-on-demand (VoD), where they are more sensitive to variations in delay, jitter, and packet loss. Dynamic Adaptive Streaming over HTTP (DASH) is the most popular technology for live streaming and VoD, where it has been massively deployed on the Internet. DASH is an over-the-top application using unmanaged networks to distribute content with the best possible quality. Widely, it uses large reception buffers in order to keep a seamless playback for VoD applications. However, the use of large buffers in live streaming services is not allowed because of the induced delay. Hence, network congestion caused by insufficient queues could decrease the user-perceived video quality. Active Queue Management (AQM) arises as an alternative to control the congestion in a router’s queue, pressing the TCP traffic sources to reduce their transmission rate when it detects incipient congestion. As a consequence, the DASH client tends to decrease the quality of the streamed video. In this article, we evaluate the performance of recent AQM strategies for real-time adaptive video streaming and propose a new AQM algorithm using Long Short-Term Memory (LSTM) neural networks to improve the user-perceived video quality. The LSTM forecast the trend of queue delay to allow earlier packet discard in order to avoid the network congestion. The results show that the proposed method outperforms the competing AQM algorithms, mainly in scenarios where there are congested networks.
Early Prediction of Physical Performance in Elite Soccer Matches—A Machine Learning Approach to Support Substitutions
Authors: Dijkhuis Talko B. , Kempe Matthias , Lemmink Koen A. P. M.
Published: July 2021

Substitution is an essential tool for a coach to influence the match. Factors like the injury of a player, required tactical changes, or underperformance of a player initiates substitutions. This study aims to predict the physical performance of individual players in an early phase of the match to provide additional information to the coach for his decision on substitutions. Tracking data of individual players, except for goalkeepers, from 302 elite soccer matches of the Dutch ‘Eredivisie’ 2018–2019 season were used to enable the prediction of the individual physical performance. The players’ physical performance is expressed in the variables distance covered, distance in speed category, and energy expenditure in power category. The individualized normalized variables were used to build machine learning models that predict whether players will achieve 100%, 95%, or 90% of their average physical performance in a match. The tree-based algorithms Random Forest and Decision Tree were applied to build the models. A simple Naïve Bayes algorithm was used as the baseline model to support the superiority of the tree-based algorithms. The machine learning technique Random Forest combined with the variable energy expenditure in the power category was the most precise. The combination of Random Forest and energy expenditure in the power category resulted in precision in predicting performance and underperformance after 15 min in a match, and the values were 0.91, 0.88, and 0.92 for the thresholds 100%, 95%, and 90%, respectively. To conclude, it is possible to predict the physical performance of individual players in an early phase of the match. These findings offer opportunities to support coaches in making more informed decisions on player substitutions in elite soccer.
Recent Status and Prospects on Thermochemical Heat Storage Processes and Applications
Authors: Gbenou Tadagbe , Fopah-Lele Armand , Wang Kejian
Published: July 2021

Recent contributions to thermochemical heat storage (TCHS) technology have been reviewed and have revealed that there are four main branches whose mastery could significantly contribute to the field. These are the control of the processes to store or release heat, a perfect understanding and designing of the materials used for each storage process, the good sizing of the reactor, and the mastery of the whole system connected to design an efficient system. The above-mentioned fields constitute a very complex area of investigation, and most of the works focus on one of the branches to deepen their research. For this purpose, significant contributions have been and continue to be made. However, the technology is still not mature, and, up to now, no definitive, efficient, autonomous, practical, and commercial TCHS device is available. This paper highlights several issues that impede the maturity of the technology. These are the limited number of research works dedicated to the topic, the simulation results that are too illusory and impossible to implement in real prototypes, the incomplete analysis of the proposed works (simulation works without experimentation or experimentations without prior simulation study), and the endless problem of heat and mass transfer limitation. This paper provides insights and recommendations to better analyze and solve the problems that still challenge the technology.
Facilitating Student Understanding through Incorporating Digital Images and 3D-Printed Models in a Human Anatomy Course
Authors: Kazoka Dzintra , Pilmane Mara , Edelmers Edgars
Published: July 2021

Combining classical educational methods with interactive three-dimensional (3D) visualization technology has great power to support and provide students with a unique opportunity to use them in the study process, training, and/or simulation of different medical procedures in terms of a Human Anatomy course. In 2016, Rīga Stradiņš University (RSU) offered students the 3D Virtual Dissection Table “Anatomage” with possibilities of virtual dissection and digital images at the Department of Morphology. The first 3D models were printed in 2018 and a new printing course was integrated into the Human Anatomy curriculum. This study was focused on the interaction of students with digital images, 3D models, and their combinations. The incorporation and use of digital technologies offered students great tools for their creativity, increased the level of knowledge and skills, and gave them a possibility to study human body structures and to develop relationships between basic and clinical studies.
Macrosystems EDDIE Teaching Modules Increase Students’ Ability to Define, Interpret, and Apply Concepts in Macrosystems Ecology
Authors: Hounshell Alexandria G. , Farrell Kaitlin J. , Carey Cayelan C.
Published: July 2021

Ecologists are increasingly using macrosystems approaches to understand population, community, and ecosystem dynamics across interconnected spatial and temporal scales. Consequently, integrating macrosystems skills, including simulation modeling and sensor data analysis, into undergraduate and graduate curricula is needed to train future environmental biologists. Through the Macrosystems EDDIE (Environmental Data-Driven Inquiry and Exploration) program, we developed four teaching modules to introduce macrosystems ecology to ecology and biology students. Modules combine high-frequency sensor data from GLEON (Global Lake Ecological Observatory Network) and NEON (National Ecological Observatory Network) sites with ecosystem simulation models. Pre- and post-module assessments of 319 students across 24 classrooms indicate that hands-on, inquiry-based modules increase students’ understanding of macrosystems ecology, including complex processes that occur across multiple spatial and temporal scales. Following module use, students were more likely to correctly define macrosystems concepts, interpret complex data visualizations and apply macrosystems approaches in new contexts. In addition, there was an increase in student’s self-perceived proficiency and confidence using both long-term and high-frequency data; key macrosystems ecology techniques. Our results suggest that integrating short (1–3 h) macrosystems activities into ecology courses can improve students’ ability to interpret complex and non-linear ecological processes. In addition, our study serves as one of the first documented instances for directly incorporating concepts in macrosystems ecology into undergraduate and graduate ecology and biology curricula.
Reduction of Cd(II) Ions in the Presence of Tetraethylammonium Cations. Adsorption Effect on the Electrode Process
Authors: Torrent-Burgués Juan
Published: July 2021

The effect of the adsorption of tetraethylammonium (TEA) cations, which present both ionic and organic characteristics, on the reduction of Cd(II) ions have been studied from dc and ac measurements at the dropping mercury electrode. The resistance to the charge transfer (Rct) and Warburg coefficient (σ) parameters have been determined through impedance measurements. Thus, the global velocity constant has been obtained. The reduction process of Cd(II) in perchloric media is reversible and is affected by the adsorption of TEA cations, especially at high TEA concentrations. Values of E1/2, half wave potential, and DO, diffusion coefficient, obtained from both dc and ac measurements agree. The velocity constants show a decrease as TEA concentration increases, with values ranging from 0.6 to 0.01 cm·s−1. The inhibitory effect of TEA adsorption on the electrode process and the relationship between electrode coverage, θ, and velocity constants, K, using several isotherm equations, have been discussed. The best fit was obtained with the equation K = 0K(1 − θ)a with an a value close to three, indicating a blocking effect and electrostatic repulsion due to TEA.
Blockchain-Enabled Transaction Scanning Method for Money Laundering Detection
Authors: Oad Ammar , Razaque Abdul , Tolemyssov Askar , Alotaibi Munif , Alotaibi Bandar , Zhao Chenglin
Published: July 2021

Currently, life cannot be imagined without the use of bank cards for purchases or money transfers; however, their use provides new opportunities for money launderers and terrorist organizations. This paper proposes a blockchain-enabled transaction scanning (BTS) method for the detection of anomalous actions. The BTS method specifies the rules for outlier detection and rapid movements of funds, which restrict anomalous actions in transactions. The specified rules determine the specific patterns of malicious activities in the transactions. Furthermore, the rules of the BTS method scan the transaction history and provide a list of entities that receive money suspiciously. Finally, the blockchain-enabled process is used to restrict money laundering. To validate the performance of the proposed BTS method, a Spring Boot application is built based on the Java programming language. Based on experimental results, the proposed BTS method automates the process of investigating transactions and restricts money laundering incidents.
A Novel Emotion-Aware Hybrid Music Recommendation Method Using Deep Neural Network
Authors: Wang Shu , Xu Chonghuan , Ding Austin Shijun , Tang Zhongyun
Published: July 2021

Emotion-aware music recommendations has gained increasing attention in recent years, as music comes with the ability to regulate human emotions. Exploiting emotional information has the potential to improve recommendation performances. However, conventional studies identified emotion as discrete representations, and could not predict users’ emotional states at time points when no user activity data exists, let alone the awareness of the influences posed by social events. In this study, we proposed an emotion-aware music recommendation method using deep neural networks (emoMR). We modeled a representation of music emotion using low-level audio features and music metadata, model the users’ emotion states using an artificial emotion generation model with endogenous factors exogenous factors capable of expressing the influences posed by events on emotions. The two models were trained using a designed deep neural network architecture (emoDNN) to predict the music emotions for the music and the music emotion preferences for the users in a continuous form. Based on the models, we proposed a hybrid approach of combining content-based and collaborative filtering for generating emotion-aware music recommendations. Experiment results show that emoMR performs better in the metrics of Precision, Recall, F1, and HitRate than the other baseline algorithms. We also tested the performance of emoMR on two major events (the death of Yuan Longping and the Coronavirus Disease 2019 (COVID-19) cases in Zhejiang). Results show that emoMR takes advantage of event information and outperforms other baseline algorithms.
A Summary of F-Transform Techniques in Data Analysis
Authors: Martino Ferdinando Di , Perfilieva Irina , Sessa Salvatore
Published: July 2021

Fuzzy transform is a technique applied to approximate a function of one or more variables applied by researchers in various image and data analysis. In this work we present a summary of a fuzzy transform method proposed in recent years in different data mining disciplines, such as the detection of relationships between features and the extraction of association rules, time series analysis, data classification. After having given the definition of the concept of Fuzzy Transform in one or more dimensions in which the constraint of sufficient data density with respect to fuzzy partitions is also explored, the data analysis approaches recently proposed in the literature based on the use of the Fuzzy Transform are analyzed. In particular, the strategies adopted in these approaches for managing the constraint of sufficient data density and the performance results obtained, compared with those measured by adopting other methods in the literature, are explored. The last section is dedicated to final considerations and future scenarios for using the Fuzzy Transform for the analysis of massive and high-dimensional data.
Bandwidth-Aware Rescheduling Mechanism in SDN-Based Data Center Networks
Authors: Chuang Ming-Chin , Yen Chia-Cheng , Hung Chia-Jui
Published: July 2021

Recently, with the increase in network bandwidth, various cloud computing applications have become popular. A large number of network data packets will be generated in such a network. However, most existing network architectures cannot effectively handle big data, thereby necessitating an efficient mechanism to reduce task completion time when large amounts of data are processed in data center networks. Unfortunately, achieving the minimum task completion time in the Hadoop system is an NP-complete problem. Although many studies have proposed schemes for improving network performance, they have shortcomings that degrade their performance. For this reason, in this study, we propose a centralized solution, called the bandwidth-aware rescheduling (BARE) mechanism for software-defined network (SDN)-based data center networks. BARE improves network performance by employing a prefetching mechanism and a centralized network monitor to collect global information, sorting out the locality data process, splitting tasks, and executing a rescheduling mechanism with a scheduler to reduce task completion time. Finally, we used simulations to demonstrate our scheme’s effectiveness. Simulation results show that our scheme outperforms other existing schemes in terms of task completion time and the ratio of data locality.
Multi-Objective Function-Based Node-Disjoint Multipath Routing for Mobile Ad Hoc Networks
Authors: Velusamy Bhanumathi , Karunanithy Kalaivanan , Sauveron Damien , Akram Raja Naeem , Cho Jaehyuk
Published: July 2021

The main goal is to find multiple node-disjoint paths that meet the multi-objective optimization problem in terms of energy consumption minimization and network lifetime improvement. Due to the battery-dependent nodes in mobile ad hoc networks, the performance of the network will degrade. Hence, it is necessary to choose multiple optimal node-disjoint paths between source and destination for data transfer. Additionally, it improves the Quality of Service (QoS) of wireless networks. Multi-objective function is used to select a path such that it gives an optimum result based on the energy consumption, hop, and traffic load. From the simulation results, it is proved that the proposed system is achieving less energy consumption and improved network lifetime compared with existing Dynamic Source Routing (DSR), Hopfield Neural Network-based Disjoint Path set Selection (HNNDPS) and Multipath DSR (MDSR).
On-line Detection and Classification of PMSM Stator Winding Faults Based on Stator Current Symmetrical Components Analysis and the KNN Algorithm
Authors: Pietrzak Przemyslaw , Wolkiewicz Marcin
Published: July 2021

The significant advantages of permanent magnet synchronous motors, such as very good dynamic properties, high efficiency and power density, have led to their frequent use in many drive systems today. However, like other types of electric motors, they are exposed to various types of faults, including stator winding faults. Stator winding faults are mainly inter-turn short circuits and are among the most common faults in electric motors. In this paper, the possibility of using the spectral analysis of symmetrical current components to extract fault symptoms and the machine-learning-based K-Nearest Neighbors (KNN) algorithm for the detection and classification of the PMSM stator winding fault is presented. The impact of the key parameters of this classifier on the effectiveness of stator winding fault detection and classification is presented and discussed in detail, which has not been researched in the literature so far. The proposed solution was verified experimentally using a 2.5 kW PMSM, the construction of which was specially prepared for carrying out controlled inter-turn short circuits.
Sodium Radiofrequency Coils for Magnetic Resonance: From Design to Applications
Authors: Giovannetti Giulio , Flori Alessandra , Martini Nicola , Francischello Roberto , Aquaro Giovanni Donato , Pingitore Alessandro , Frijia Francesca
Published: July 2021

Sodium (23Na) is the most abundant cation present in the human body and is involved in a large number of vital body functions. In the last few years, the interest in Sodium Magnetic Resonance Imaging (23Na MRI) has considerably increased for its relevance in physiological and physiopathological aspects. Indeed, sodium MRI offers the possibility to extend the anatomical imaging information by providing additional and complementary information on physiology and cellular metabolism with the heteronuclear Magnetic Resonance Spectroscopy (MRS). Constraints are the rapidly decaying of sodium signal, the sensitivity lack due to the low sodium concentration versus 1H-MRI induce scan times not clinically acceptable and it also constitutes a challenge for sodium MRI. With the available magnetic fields for clinical MRI scanners (1.5 T, 3 T, 7 T), and the hardware capabilities such as strong gradient strengths with high slew rates and new dedicated radiofrequency (RF) sodium coils, it is possible to reach reasonable measurement times (~10–15 min) with a resolution of a few millimeters, where it has already been applied in vivo in many human organs such as the brain, cartilage, kidneys, heart, as well as in muscle and the breast. In this work, we review the different geometries and setup of sodium coils described in the available literature for different in vivo applications in human organs with clinical MR scanners, by providing details of the design, modeling and construction of the coils.
A Non-Intrusive Signal-Based Fault Diagnosis Method for Proton Exchange Membrane Water Electrolyzer Using Empirical Mode Decomposition
Authors: Aubras Farid , Damour Cedric , Benne Michel , Boulevard Sebastien , Bessafi Miloud , Grondin-Perez Brigitte , Kadjo Amangoua J.-J. , Deseure Jonathan
Published: July 2021

This work focuses on a signal-based diagnosis approach dedicated to proton exchange membrane water electrolyzer (PEM WE) anode pump fault. The PEM WE cell measurements are performed with an experimental test bench to highlight the impact of water flow rate in the anode compartment. This approach is non-intrusive, and it can detect anode flow rate variation during the electrolysis and is designed to fulfill online diagnosis requirements. Contrary to electrochemical impedance spectroscopy-based approaches (EIS), this method stands out from existing procedures as a result of its few requirements, excluding any signal with perturbing amplitude. Therefore, the electrolyzer remains continuously available, even while the analysis is performed. The empirical mode decomposition (EMD) is used to decompose the signal variation into a sum of amplitude modulation and frequency modulation (AM-FM) components, called intrinsic mode functions (IMFs). In this work, the PEM WE current signal is decomposed into several IMFs using EMD. Then, the energetic contribution of each IMF is calculated. Experimental results exhibited that the energetic contribution of IMFs can be used as relevant criteria for fault diagnosis in PEM WE systems. This process only requires monitoring of the PEM WE current and has a low computational cost, which is a significant economic and technical advantage.
How to Procure Flexibility Services within the Electricity Distribution System: Lessons from an International Review of Innovation Projects
Authors: Anaya Karim L. , Pollitt Michael G.
Published: July 2021

The aim of this paper is to analyse and evaluate the deployment of smart platforms (operated by distribution system operators—DSOs—or by independent parties) in key jurisdictions that facilitate the trading of flexibility services—primarily by DSOs. We look at key innovation projects/initiatives from seven jurisdictions, including Australia, France, Germany, Great Britain, Japan, The Netherlands and Norway. We have deliberately selected 13 use cases that operate under different regulatory frameworks and market rules, and have been recently implemented (from 2017 onwards). With the selection of key use cases this study seeks to discuss the different smart architecture solutions and main capabilities across different demonstrators and their relationship to business as usual. It also analyses flexibility market designs, identifies main characteristics, and compares different price formation schemes and procurement methods. The value of flexibility for DSOs is also discussed.
Numerical Study of Hydrocarbon Charge Reduction Methods in HVAC Heat Exchangers
Authors: Allymehr Ehsan , Skaugen Geir , Will Torsten , Pardiñas Ángel Álvarez , Eikevik Trygve Magne , Hafner Armin , Schnabel Lena
Published: July 2021

Required refrigerant charge in heat pump systems with propane is analyzed. Two systems are compared: the first a direct heat pump, with fin-and-tube heat exchangers, and the second an indirect system, with plate heat exchangers with an additional brine-to-air heat exchanger. Each system was considered to be able to work reversibly, with 5 kW design cooling capacity in summer and 8 kW design heating capacity in winter. Two separately developed simulation codes were used to calculate the required refrigerant charge and the efficiency of each of the systems. The charge was reduced by the use of microfinned tubes up to 22% in direct system reduced using microfinned tubes compared to the smooth tube. For the indirect system using specially designed plate heat exchangers with the minimum internal volume, their charge was reduced by up to 66% compared to normal plate heat exchangers.
Impact of Spanish Offshore Wind Generation in the Iberian Electricity Market: Potential Savings and Policy Implications
Authors: Roldan-Fernandez Juan-Manuel , Serrano-Gonzalez Javier , Gonzalez-Longatt Francisco , Burgos-Payan Manuel
Published: July 2021

The European Union considers that offshore wind power will play a key role in making the EU the first climate-neutral continent by 2050. Currently, the potential of offshore wind energy is still untapped in Spain. Furthermore, the characteristics of the coastline in Spain require floating technology, making it challenging to install wind farms due to their current high cost. This work seeks to quantify the impact that Spanish offshore wind energy would have on the Iberian electricity market. Several offshore wind scenarios are evaluated by combining available information in relation to areas suitable for installing wind farms and wind resource data. The impact on the day-ahead electricity market has been obtained by reproducing the market, including these new offshore wind generation scenarios. The introduction of this renewable energy results in a market cost reduction in what is known as the merit-order effect. According to our estimates, for each MWh of offshore wind energy introduced in the market, there would be a market cost reduction of 45 €. These savings can serve as a reference for regulators to adjust their policy framework to boost floating wind offshore generation.