bluuebunny/crossref_metadata_2025 huggingface dataset:
Antioxidant and Anti-Proliferative Properties of Hagenia abyssinica Roots and Their Potentially Active Components
Authors: Fan Minxia , Chen Guilin , Zhang Yongli , Nahar Lutfun , Sarker Satyajit Dey , Hu Guangwan , Guo Mingquan
Published: February 2020

Hagenia abyssinica (Bruce) J. F. Gmel. is a multipurpose dioecious tree that has been used to treat various ailments, for example, the flowers of H. abyssinica have been widely used as a tea to treat intestinal parasites by local residents and the roots of H. abyssinica could also be used for anticancer purposes. Antioxidant activity could be one of the most important pathways to suppress cancer and there is hardly any information available on the specific chemical components corresponding to the bioactivities of H. abyssinica to date. The present study intended to screen and evaluate the antioxidant and anti-proliferative properties of five different fractions from H. abyssinica along with their corresponding total flavonoid and phenolic contents and then further identify those compounds with the most potent antioxidant and anti-proliferative activities using high performance liquid chromatography (HPLC) coupled to mass spectrometry (MS) and nuclear magnetic resonance (NMR). The total flavonoid and phenolic content assays showed that the ethyl acetate (EA) fraction of H. abyssinica had higher flavonoid and phenolic levels than the other four fractions. Furthermore, the 2,2-diphenyl-1-picrylhydrazyl (DPPH) superoxide radical scavenging abilities, total antioxidant capacity (TAC) assay with 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid (ABTS), and ferric-reducing antioxidant power (FRAP) were measured to evaluate the antioxidant activities of the five fractions and some pure compounds isolated from the EA fraction, which displayed higher antioxidant properties than that of the other fractions. Caffeic acid from the EA fraction showed even stronger DPPH scavenging ability (IC50 7.858 ± 0.31 µg/mL) than that of Vc (IC50 8.27 ± 0.11 µg/mL) as the positive control. The anti-proliferative properties of four fractions and the ethanol extract were evaluated by the 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) assay and the EA fraction exhibited higher anti-proliferative activities against three cancer cell lines than that of the other fractions. Additionally, the compounds with good antioxidant activity from the EA fraction of H. abyssinica were screened and identified using LC-MS and NMR and were also found to possess good anti-proliferative activity. In the MTT assay, the quercetin showed the strongest dose-dependent anti-proliferative activities to colon cancer cells (HT-29) and liver cancer cells (HepG2) among all of the compounds isolated. This study provided valuable information on the synergistic antioxidant and anti-proliferative properties of H. abyssinica.
Video-Based Parking Occupancy Detection for Smart Control System
Authors: Chen Lun-Chi , Sheu Ruey-Kai , Peng Wen-Yi , Wu Jyh-Horng , Tseng Chien-Hao
Published: February 2020

Street lighting is a fundamental aspect of security systems in homes, industrial facilities, and public places. To detect parking lot occupancy in outdoor environments, street light control plays a crucial role in smart surveillance applications that can perform robustly in extreme surveillance environments. However, traditional parking occupancy systems are mostly implemented for outdoor environments using costly sensor-based techniques. This study uses the Jetson TX2 to develop a method that can accurately identify street parking occupancy and control streetlights to assist occupancy detection, thereby reducing costs, and can adapt to various weather conditions. The proposed method adopts You Only Look Once version 3 (YOLO v3, Seattle, WA, USA) based on MobileNet version 2 (MobileNet v2, Salt Lake City, UT, USA), which is area-based and uses voting to stably recognize occupancy status. This solution was verified using the CNRPark + EXT dataset, a simulated model, and real scenes photographed with a camera. Our experiments revealed that the proposed framework can achieve stable parking occupancy detection in streets.
Extending BIM Interoperability for Real-Time Concrete Formwork Process Monitoring
Authors: Hamooni Morteza , Maghrebi Mojtaba , Majrouhi Sardroud Javad , Kim Sungjin
Published: February 2020

The concrete formwork process is a critical component of construction project control because failing to gain the necessary concrete strength can lead to reworks and, consequently, project delays and cost overruns during the project’s execution. The goal of this study is to develop a novel method of monitoring the maturity of concrete and providing reduced formwork removal time with the strength ensured in real-time. This method addresses the wireless sensors and building information modeling (BIM) needed to help project management personnel monitor the concrete’s status and efficiently decide on the appropriate formwork removal timing. Previous studies have focused only on the monitoring of concrete’s status using sensor data or planning the formwork layout by integrating the BIM environment into the design process. This study contributes to extending BIM’s interoperability for monitoring concrete’s maturity in real-time during construction, as well as determining the formwork removal time for project control. A case study was conducted at a building construction project to validate the developed framework. It was concluded that BIM can interoperate with the data collected from sensors embedded in concrete, and that this system can reduce formwork removal time while retaining sufficient strength in the concrete, rather than adhering to the removal time given in building code standards.
Data-Efficient Domain Adaptation for Semantic Segmentation of Aerial Imagery Using Generative Adversarial Networks
Authors: Benjdira Bilel , Ammar Adel , Koubaa Anis , Ouni Kais
Published: February 2020

Despite the significant advances noted in semantic segmentation of aerial imagery, a considerable limitation is blocking its adoption in real cases. If we test a segmentation model on a new area that is not included in its initial training set, accuracy will decrease remarkably. This is caused by the domain shift between the new targeted domain and the source domain used to train the model. In this paper, we addressed this challenge and proposed a new algorithm that uses Generative Adversarial Networks (GAN) architecture to minimize the domain shift and increase the ability of the model to work on new targeted domains. The proposed GAN architecture contains two GAN networks. The first GAN network converts the chosen image from the target domain into a semantic label. The second GAN network converts this generated semantic label into an image that belongs to the source domain but conserves the semantic map of the target image. This resulting image will be used by the semantic segmentation model to generate a better semantic label of the first chosen image. Our algorithm is tested on the ISPRS semantic segmentation dataset and improved the global accuracy by a margin up to 24% when passing from Potsdam domain to Vaihingen domain. This margin can be increased by addition of other labeled data from the target domain. To minimize the cost of supervision in the translation process, we proposed a methodology to use these labeled data efficiently.
Odour Emissions of Municipal Waste Biogas Plants—Impact of Technological Factors, Air Temperature and Humidity
Authors: Wiśniewska Marta , Kulig Andrzej , Lelicińska-Serafin Krystyna
Published: February 2020

Biogas plants processing municipal waste are an important part of a circular economy (energy generation from biogas and organic fertiliser production for the treatment of selectively collected biowaste). However, the technological processes taking place may be associated with odour nuisance. The paper presents the results of pilot research conducted at six municipal waste biogas plants in Poland. It shows the relations between odour intensity and concentration and the occurring meteorological and ambient conditions (air temperature and relative humidity) and technological factors at biogas plants processing municipal waste. The impact of meteorological and ambient conditions was identified by measuring air temperature and relative humidity and observing their changes. The impact of technological factors was identified by measuring odorant concentration (volatile organic compounds and ammonia) and observing their changes between individual measurement series. At most analysed biogas plants, the influence of technological factors on odour emissions took place and was clearly noted. The elements of biogas installations characterised by the highest concentration of these odorants were indicated. Special attention should be paid to the choice of technological solutions and technical and organisational measures to reduce the impact of unfavourable atmospheric conditions on odour emissions.
A Density Clustering Algorithm for Simultaneous Modulation Format Identification and OSNR Estimation
Authors: Zhao Zhao , Yang Aiying , Guo Peng , Tan Qingzhao
Published: February 2020

In this work, we propose a combined method to implement both modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) estimation, a method based on density-based spatial clustering of applications with a noise (DBSCAN) algorithm. The proposed method can automatically extract the cluster number and density information of samples. The cluster number can be used for MFI and the density information combined with a fourth-order polynomial fitting can correctly estimate OSNR. We verify the feasibility of the method through simulation and conceptual proof experiments. The results show that the MFI can achieve 100% accuracy when the OSNR values are higher than the 7% forward error correction (FEC) thresholds for five commonly used modulation formats (MFs) like polarization division multiplexing (PDM)-QPSK, PDM-8PSK, PDM-16QAM, PDM-32QAM, and PDM-64QAM. Mean absolute OSNR estimation errors are not higher than 1 dB for different signals. There is no additional hardware required, so the proposed method has the ability to be integrated into existing optical performance monitoring systems without burden. Furthermore, the proposed method has the potential to be used in bit-error ratio (BER) calculation, linear, or nonlinear impairments monitoring. We believe that our multifunctional and simple method would be favorable to a future elastic optical network (EON).
Feasibility Study for Spatial Distribution of Diesel Oil in Contaminated Soils by Laser Induced Fluorescence
Authors: Gu Yanhong , Zuo Zhaolu , Shi Chaoyi , Hu Xueyou
Published: February 2020

Laser induced fluorescence (LIF) technique has been demonstrated as a powerful technology for analyzing the contamination of petroleum due to its excellent attributes of rapid analysis speed and slight sample preparation. This study focuses on the monitoring application of LIF in petroleum hydrocarbon-contaminated soils by establishing the three-dimensional diffusion models. In this paper, to improve the analysis accuracy, the effects of soil matrix difference for fluorescence intensities were considered. In order to validate the practicability of LIF, the longitudinal penetration laws and the lateral diffusion laws of diesel oil in different humidity soils were analyzed. These laws indicate that the longitudinal penetration depth decreases and the lateral diffusion range increases with the increase of soil moisture. Then, the three-dimensional diffusion models were established, the relative standard deviation (RSD) of the predictions for diesel oil in different soil moisture are 5.09%, 9.62%, 7.92%, and the contaminated volumes of soils by diesel oil are 233.90 cm3, 332.70 cm3, and 660.05 cm3, respectively. These results express that the soil moisture extends the extent of diesel-contaminated soils. The present work shows the feasibility of LIF technique for the field monitoring of petroleum.
Biological Effects of Paullinia cupana (Guarana) in Combination with Whole-Body Vibration Exercise in Wistar Rats
Authors: Cardoso André L.B.D. , Frederico Éric H.F.F. , Guimarães Carlos A.S. , Reis-Silva Aline , de Oliveira Guedes-Aguiar Eliane , Francisca Santos Arlete , Cristina Moura-Fernandes Márcia , Felipe Ferreira-Souza Luiz , Eduardo-Santos Tiago , Eduardo-Santos Diego , Guimarães Mendonça Rubens , da Cunha de Sá-Caputo Danúbia , Liane Paineiras-Domingos Laisa , Taiar Redha , Asad Nasser R. , Bernardo-Filho Mario
Published: February 2020

In addition to its nutritional value, Paullinia cupana (guarana) is commonly used in traditional medicine, known for its stimulant and medicinal properties. This investigation evaluated the effects of a guarana extract in combination with whole-body vibration (WBV) exercises on Wistar rats. Rats (male, n = 20) were divided into the following four groups: control (CON), treated with guarana (GUA), submitted to 50 Hz of WBV (WBV-E), treated with guarana and submitted to 50 Hz of WBV (GUA + WBV-E), daily for 6-weeks. Guarana altered (p < 0.05) the uptake of the radiopharmaceutical sodium pertechnetate (Na99mTcO4) in muscle. Additionally, it modified the stool consistency, and in combination with WBV decreased the food intake without modifying body mass. The levels of calcium increased in the groups submitted to WBV exercises (WBV-E and GUA + WBV-E) as compared with the GUA group. The outcomes provide additional evidence of the biological effects of guarana separately or in combination with WBV and supports the use of guarana as a functional food.
Application of Texture Descriptors to Facial Emotion Recognition in Infants
Authors: Martínez Ana , Pujol Francisco A. , Mora Higinio
Published: February 2020

The recognition of facial emotions is an important issue in computer vision and artificial intelligence due to its important academic and commercial potential. If we focus on the health sector, the ability to detect and control patients’ emotions, mainly pain, is a fundamental objective within any medical service. Nowadays, the evaluation of pain in patients depends mainly on the continuous monitoring of the medical staff when the patient is unable to express verbally his/her experience of pain, as is the case of patients under sedation or babies. Therefore, it is necessary to provide alternative methods for its evaluation and detection. Facial expressions can be considered as a valid indicator of a person’s degree of pain. Consequently, this paper presents a monitoring system for babies that uses an automatic pain detection system by means of image analysis. This system could be accessed through wearable or mobile devices. To do this, this paper makes use of three different texture descriptors for pain detection: Local Binary Patterns, Local Ternary Patterns, and Radon Barcodes. These descriptors are used together with Support Vector Machines (SVM) for their classification. The experimental results show that the proposed features give a very promising classification accuracy of around 95% for the Infant COPE database, which proves the validity of the proposed method.
Hyphenated TLC as a Tool in the Effect-Directed Discovery of Bioactive Natural Products
Authors: Agatonovic-Kustrin Snezana , Morton David W.
Published: February 2020

Complex samples such as botanical extracts contain hundreds of compounds. Since we can only identify compounds that are stable, extractable, separable and detectable from complex botanical extracts, minimal sample treatment and different detection methods are essential. A combination of high-performance thin-layer chromatography (HPTLC) with non-targeted screening via bioassays (enzymes), microchemical and biological (microorganisms) detection allows for the fast and quantitative bioprofiling of complex samples. Further hyphenation of HPTLC with spectroscopic methods of identification enables targeted identification of bioactive natural products via Effect Directed Analysis (EDA).
Reducing Computational Complexity and Memory Usage of Iterative Hologram Optimization Using Scaled Diffraction
Authors: Shimobaba Tomoyoshi , Makowski Michal , Takahashi Takayuki , Yamamoto Yota , Hoshi Ikuo , Nishitsuji Takashi , Hoshikawa Naoto , Kakue Takashi , Ito Tomoyoshi
Published: February 2020

A complex amplitude hologram can reconstruct perfect light waves. However, as there are no spatial light modulators that are able to display complex amplitudes, we need to use amplitude, binary, or phase-only holograms. The images reconstructed from such holograms will deteriorate; to address this problem, iterative hologram optimization algorithms have been proposed. One of the iterative algorithms utilizes a blank area to help converge the optimization; however, the calculation time and memory usage involved increases. In this study, we propose to reduce the computational complexity and memory usage of the iterative optimization using scaled diffraction, which can calculate light propagation with different sampling pitches on a hologram plane and object plane. Scaled diffraction can introduce a virtual blank area without using physical memory. We further propose a combination of scaled diffraction-based optimization and conventional methods. The combination algorithm improves the quality of a reconstructed complex amplitude while accelerating optimization.
From Seabed to Bedside: A Review on Promising Marine Anticancer Compounds
Authors: Wang Edina , Sorolla Maria Alba , Gopal Krishnan Priya Darshini , Sorolla Anabel
Published: February 2020

The marine environment represents an outstanding source of antitumoral compounds and, at the same time, remains highly unexplored. Organisms living in the sea synthesize a wide variety of chemicals used as defense mechanisms. Interestingly, a large number of these compounds exert excellent antitumoral properties and have been developed as promising anticancer drugs that have later been approved or are currently under validation in clinical trials. However, due to the high need for these compounds, new methodologies ensuring its sustainable supply are required. Also, optimization of marine bioactives is an important step for their success in the clinical setting. Such optimization involves chemical modifications to improve their half-life in circulation, potency and tumor selectivity. In this review, we outline the most promising marine bioactives that have been investigated in cancer models and/or tested in patients as anticancer agents. Moreover, we describe the current state of development of anticancer marine compounds and discuss their therapeutic limitations as well as different strategies used to overcome these limitations. The search for new marine antitumoral agents together with novel identification and chemical engineering approaches open the door for novel, more specific and efficient therapeutic agents for cancer treatment.
Modified Potentiometric Screen-Printed Electrodes Based on Imprinting Character for Sodium Deoxycholate Determination
Authors: H. Kamel Ayman , Ezzat Samar , Ahmed Mona A. , Amr Abd El-Galil E. , A. Almehizia Abdulrahman , Al-Omar Mohamed A.
Published: February 2020

Potentiometric sensors have a great influence on the determination of most various compounds in their matrices. Therefore, efficient and new sensors were introduced to measure sodium Deoxycholate (NaDC) as a bile acid salt. These sensors are based on NaDC imprinted polymer (MIP) as sensory element. The MIP beads were synthesized using thermal polymerization pathway, in which acrylamide (AAm), ethylene glycol dimethacrylate (EGDMA), NaDC, and benzoyl peroxide (BPO) were used as the functional monomer, cross-linker, template, and initiator, respectively. The proposed sensors were fabricated using a coated screen-printed platform and the sensing membrane was modified by single-walled carbon nanotubes (SWCNTs) as an ion-to-electron transducer. The sensors exhibited high sensitivity that reached 4.7 × 10−5 M of near-Nernestian slope (−60.1 ± 0.9 mV/decade, r2 = 0.999 (n= 5)). In addition, the sensors revealed high selectivity, long lifetime, high potential stability, and conductivity that ensure reproducible and accurate results over a long time. MIP characterization was performed using Fourier Transform-Infrared (FT-IR) and a scanning electron microscope (SEM). Regarding the interaction of NaDC with serum albumin (SA), albumin is determined in human serum samples as human serum albumin (HSA), which was collected from different volunteers of different ages and gender.
Fluorescence and Physico-Chemical Properties of Hydrogenated Detonation Nanodiamonds
Authors: Thalassinos Giannis , Stacey Alastair , Dontschuk Nikolai , Murdoch Billy J. , Mayes Edwin , Girard Hugues A. , Abdullahi Ibrahim M. , Thomsen Lars , Tadich Anton , Arnault Jean-Charles , Mochalin Vadym N. , Gibson Brant C. , Reineck Philipp
Published: February 2020

Hydrogenated detonation nanodiamonds are of great interest for emerging applications in areas from biology and medicine to lubrication. Here, we compare the two main hydrogenation techniques—annealing in hydrogen and plasma-assisted hydrogenation—for the creation of detonation nanodiamonds with a hydrogen terminated surface from the same starting material. Synchrotron-based soft X-ray spectroscopy, infrared absorption spectroscopy, and electron energy loss spectroscopy were employed to quantify diamond and non-diamond carbon contents and determine the surface chemistries of all samples. Dynamic light scattering was used to study the particles’ colloidal properties in water. For the first time, steady-state and time-resolved fluorescence spectroscopy analysis at temperatures from room temperature down to 10 K was performed to investigate the particles’ fluorescence properties. Our results show that both hydrogenation techniques produce hydrogenated detonation nanodiamonds with overall similar physico-chemical and fluorescence properties.
Perceptions of Climate Change and Drivers of Insect Pest Outbreaks in Vegetable Crops in Limpopo Province of South Africa
Authors: Phophi Mutondwa Masindi , Mafongoya Paramu , Lottering Shenelle
Published: February 2020

Vegetable production is a source of income for smallholder farmers in Limpopo Province, South Africa. Vegetable production is constrained by the negative impacts of climate change and pests. This study assessed farmers’ awareness of climate change, farmers’ knowledge of insect pests and factors that influence insect pests’ prevalence. The data were collected using quantitative and qualitative methods. The data were subjected to descriptive and bivariate analysis. About 84.5% of smallholder farmers were aware of climate change. Late rainfall (24.4%), long dry spells (15%) and increased drought frequency (19.4%) were highlighted as dominant indicators of climate change by farmers. Aphids (22.2%), Bagrada hilaris (12.5%) and Spodoptera frugiperda (10.2%) were the most prevalent insect pests within the Vhembe District. Warmer winters, dry spells and high temperatures were perceived by farmers to influence insect pests’ prevalence within the district. It can be concluded that farmers are aware of climate change and climatic factors influencing pest prevalence within the district. Pest risk maps are needed to improve the preparedness of the government and farmers in controlling insect pests under changing climates.
Experimental and Numerical Investigation of Tip Leakage Flows in a Roots Blower
Authors: Sun Shuaihui , Singh Gursharanjit , Kovacevic Ahmed , Bruecker Christoph
Published: February 2020

Computational fluid dynamics (CFD) can help in understanding the nature of leakage flow phenomena inside the rotary positive displacement machines (PDMs). However, due to the lack of experimental results, the analysis of leakage flows in rotary PDMs by CFD has not yet been fully validated. Particle image velocimetry (PIV) tests with a microscopic lens and phase-lock were conducted to obtain the velocity field around the tip gap in an optical Roots blower. The three-dimensional unsteady CFD model of the Roots blower with the dynamic grids generated by Screw Compressor Rotor Grid Generation (SCORG) was established to predict the gap flow under the same operating conditions. The images obtained by the PIV tests were analyzed and some factors which compromise the quality of test results in the gap flow were identified, such as reflections and transparency of the window. The flow fields obtained by CFD have the same flow pattern and velocity magnitude as the experimental results in the majority of observed regions but overestimate the leakage flow velocity. The CFD results show a vortex induced by the leakage flow in the downstream region of the gap. The flow losses in the tip gap mainly happen at the entrance upstream of the gap. Finally, some suggestions for future work are discussed.
Craniofacial Morphology in Children with Growth Hormone Deficiency and Turner Syndrome
Authors: Wójcik Dorota , Beń-Skowronek Iwona
Published: February 2020

The review aims to collect and demonstrate recent knowledge about craniofacial morphology in growth hormone (GH)-deficient children and children with Turner syndrome. The review describes also the effects of growth hormone treatment on craniofacial morphology of children with growth hormone deficiency and Turner syndrome. Regardless of the disorder it accompanies, short stature is associated with similar craniofacial features characteristic of all short-statured children. Characteristic craniofacial features involve lesser dimensions of the cranial base and mandibular length, proportionately smaller posterior than anterior facial height, retrognathic face, and posterior rotation of the mandible. We also analyze orthodontic treatment in children affected by disorders associated with GH deficiency or provided with growth hormone treatment in the aspect of craniofacial growth. Recent publications show also the connection between growth hormone receptor polymorphism and craniofacial growth. Specialists and orthodontists treating short-statured children must be aware of the results of studies on craniofacial morphology and educate themselves on the topic of craniofacial growth in children with short stature. Moreover, knowledge of the influence of GH therapy on growth of craniofacial structures is necessary to decide the proper timing and planning of orthodontic treatment.
One Single Nucleotide Polymorphism of the TRPM2 Channel Gene Identified as a Risk Factor in Bipolar Disorder Associates With Autism Spectrum Disorder in a Japanese Population
Authors: Mahmuda Naila Al , Yokoyama Shigeru , Munesue Toshio , Hayashi Kenshi , Yagi Kunimasa , Tsuji Chiharu , Higashida Haruhiro
Published: February 2020

The transient receptor potential melastatin 2 (TRPM2) is a non-specific cation channel, resulting in Ca2+ influx at warm temperatures from 34 °C to 47 °C, thus including the body temperature range in mammals. TRPM2 channels are activated by β-NAD+, ADP-ribose (ADPR), cyclic ADPR, and 2′-deoxyadenosine 5′-diphosphoribose. It has been shown that TRPM2 cation channels and CD38, a type II or type III transmembrane protein with ADP-ribosyl cyclase activity, simultaneously play a role in heat-sensitive and NAD+ metabolite-dependent intracellular free Ca2+ concentration increases in hypothalamic oxytocinergic neurons. Subsequently, oxytocin (OT) is released to the brain. Impairment of OT release may induce social amnesia, one of the core symptoms of autism spectrum disorder (ASD). The risk of single nucleotide polymorphisms (SNPs) and variants of TRPM2 have been reported in bipolar disorder, but not in ASD. Therefore, it is reasonable to examine whether SNPs or haplotypes in TRPM2 are associated with ASD. Here, we report a case-control study with 147 ASD patients and 150 unselected volunteers at Kanazawa University Hospital in Japan. The sequence-specific primer-polymerase chain reaction method together with fluorescence correlation spectroscopy was applied. Of 14 SNPs examined, one SNP (rs933151) displayed a significant p-value (OR = 0.1798, 95% CI = 0.039, 0.83; Fisher’s exact test; p = 0.0196). The present research data suggest that rs93315, identified as a risk factor for bipolar disorder, is a possible association factor for ASD.
Wavelet-Based Entropy Measures to Characterize Two-Dimensional Fractional Brownian Fields
Authors: Nicolis Orietta , Mateu Jorge , Contreras-Reyes Javier E.
Published: February 2020

The aim of this work was to extend the results of Perez et al. (Physica A (2006), 365 (2), 282–288) to the two-dimensional (2D) fractional Brownian field. In particular, we defined Shannon entropy using the wavelet spectrum from which the Hurst exponent is estimated by the regression of the logarithm of the square coefficients over the levels of resolutions. Using the same methodology. we also defined two other entropies in 2D: Tsallis and the Rényi entropies. A simulation study was performed for showing the ability of the method to characterize 2D (in this case, α = 2 ) self-similar processes.
Didactics of Mathematics Profile of Engineering Students: A Case Study in a Multimedia Engineering Degree
Authors: Pertegal-Felices Maria Luisa
Published: February 2020

Multimedia engineers develop digital content in a wide range of fields that require them to acquire skills in the development of web solutions for those fields. In this study, we evaluated the level of didactic knowledge of mathematics that Multimedia Engineering degree students possess. The aim was to determine whether they are prepared to conceive, design and develop educational multimedia tools for teaching mathematics to primary school children. For this evaluation, the Didactic–Mathematical Knowledge and Elementary Algebraic Reasoning (DMK/EAR) test was carried out on a sample of 50 students in the second year of a Multimedia Engineering Degree. The results were compared with those of teacher training students who receive specific training in mathematics didactics. The study shows that, for most of the variables analysed, the Multimedia student scored better or comparatively equal to the teaching trainee. In conclusion, students of Multimedia Engineering have a solid foundation in the didactics of mathematics, although some deficiencies have been detected in the cognitive dimension and the content in structures, which indicate that they would need to complete their training in these areas.
Feasibility Study of Interleaving Approach for Quasi-Z-Source Inverter
Authors: Stepenko Serhii , Husev Oleksandr , Vinnikov Dmitri , Fesenko Artem , Matiushkin Oleksandr
Published: February 2020

This paper presents a comprehensive feasibility study of an interleaving approach for a quasi-Z-source inverter. The state-of-the-art approach revealed that an interleaving approach is often used to improve the efficiency and power density that can overcome the problem of oversized passive elements of quasi-Z-source-based converters. The focus is on the application of the interleaving approach in terms of the comparison of several important parameters of a quasi-Z-source inverter. Our analysis includes losses, capacitor and inductor sizes, as well as semiconductor costs. The theoretical comparison is based on the quasi-Z-source inverter model and the losses model. Simulation and experimental verification of theoretical statements are provided. It was found that a 40% reduction of inductor volume, along with 15–20% of efficiency improvements, are achievable. The results are discussed in the conclusion.
A Virtual Sensor for Electric Vehicles’ State of Charge Estimation
Authors: Gruosso Giambattista , Storti Gajani Giancarlo , Ruiz Fredy , Valladolid Juan Diego , Patino Diego
Published: February 2020

The estimation of the state of charge is a critical function in the operation of electric vehicles. The battery management system must provide accurate information about the battery state, even in the presence of failures in the vehicle sensors. This article presents a new methodology for the state of charge estimation (SOC) in electric vehicles without the use of a battery current sensor, relying on a virtual sensor, based on other available vehicle measurements, such as speed, battery voltage and acceleration pedal position. The estimator was derived from experimental data, employing support vector regression (SVR), principal component analysis (PCA) and a dual polarization (DP) battery model (BM). It is shown that the obtained model is able to predict the state of charge of the battery with acceptable precision in the case of a failure of the current sensor.
Minimization of Network Induced Jitter Impact on FPGA-Based Control Systems for Power Electronics through Forward Error Correction
Authors: Bianchi Valentina , Savi Filippo , De Munari Ilaria , Barater Davide , Buticchi Giampaolo , Franceschini Giovanni
Published: February 2020

In modular distributed architectures, the adoption of a communication method that is at the same time robust and has a low and predictable latency is of utmost importance in order to support the required system dynamics. The aim of this paper is to evaluate the consequences of the random jitter on machine drives distributed control, caused by the messages’ re-transmission in case of an error in the received data. To achieve this goal, two different Forward Error Correction (FEC) techniques are introduced in the chosen protocol, so that the recipient of the message can correct random errors without the need of any additional round trip delays needed to request and obtain a re-transmission. Experimentally validated simulations are used to evaluate the impact of random network derived jitter on a real world closed loop control system for distributed power electronic converters.
An Attribute-Based Collaborative Access Control Scheme Using Blockchain for IoT Devices
Authors: Zhang Yan , Li Bing , Liu Ben , Wu Jiaxin , Wang Yazhou , Yang Xia
Published: February 2020

The Internet of Things (IoT) benefits our lives by integrating physical devices to the real world and offers a crucial internet infrastructure for future civilization. Because IoT devices are widely distributed and restricted in resources, it is difficult for them to adopt traditional security methods to resist malicious attacks. Unauthorized access to IoT devices, which results in severe privacy and security problems, has become a major challenge that has impeded IoT technology from being widely adopted. Therefore, the access control for IoT devices urgently needs to be improved when dealing with authorization issues. In this paper, we propose an attribute-based access control scheme that provides decentralized, flexible, and fine-grained authorization for IoT devices. Blockchain is utilized to provide authentic and reliable credentials. More importantly, a verifiable collaboration mechanism is designed to meet the needs of controlled access authorization in emergencies. Authority nodes are constructed to execute major computation tasks and interact with the blockchain. The security analysis shows that our scheme can reliably guarantee the security of authorized access. More than security assurance, a proof-of-concept prototype has been implemented to prove that our scheme is scalable, efficient, and accommodates IoT devices well.
Analysis of Very Fast Transients Using Black Box Macromodels in ATP-EMTP
Authors: James Jonathan , Albano Maurizio , Clark David , Guo Dongsheng , Haddad Abderrahmane (Manu)
Published: February 2020

Modelling for very fast transients (VFTs) requires good knowledge of the behaviour of gas insulated substation (GIS) components when subjected to high frequencies. Modelling usually takes the form of circuit-based insulation coordination type studies, in an effort to determine the maximum overvoltages and waveshapes present around the system. At very high frequencies, standard transmission line modelling assumptions may not be valid. Therefore, the approach to modelling of these transients must be re-evaluated. In this work, the high frequency finite element analysis (FEA) was used to enhance circuit-based models, allowing direct computation of parameters from geometric and material characteristics. Equivalent models that replicate a finite element model’s frequency response for bus-spacer and 90° elbow components were incorporated in alternative transients program-electromagnetic transients program (ATP-EMTP) using a pole-residue equivalent circuit derived following rational fitting using the well-established and robust method of vector fitting (VF). A large model order is often required to represent this frequency dependent behaviour through admittance matrices, leading to increased computational burden. Moreover, while highly accurate models can be derived, the data extracted from finite element solutions can be non-passive, leading to instability when included in time domain simulations. A simple method of improved stability for FEA derived responses along with a method for identification of a minimum required model order for stability of transient simulations is proposed.
Massively Parallel Large Eddy Simulation of Rotating Turbomachinery for Variable Speed Gas Turbine Engine Operation
Authors: Jain Nishan , Bravo Luis , Kim Dokyun , Murugan Muthuvel , Ghoshal Anindya , Ham Frank , Flatau Alison
Published: February 2020

Gas turbine engines are required to operate at both design and off-design conditions that can lead to strongly unsteady flow-fields and aerodynamic losses severely impacting performance. Addressing this problem requires effective use of computational fluid dynamics tools and emerging models that resolve the large scale fields in detail while accurately modeling the under-resolved scale dynamics. The objective of the current study is to conduct massively parallel large eddy simulations (LES) of rotating turbomachinery that handle the near-wall dynamics using accurate wall models at relevant operating conditions. The finite volume compressible CharLES solver was employed to conduct the simulations over moving grids generated through Voronoi-based unstructured cells. A grid sensitivity analysis was carried out first to establish reliable parameters and assess the quality of the results. LES simulations were then conducted to understand the impact of blade tip clearance and operating conditions on the stage performance. Variations in tip clearance of 3% and 16% chord were considered in the analysis. Other design points included operation at 100% rotor speed and off-design conditions at 75% and 50% of the rotor speed. The simulation results showed that the adiabatic efficiency improves dramatically with reduction in tip gap due to the decrease in tip leakage flow and the resulting flow structures. The analysis also showed that the internal flow becomes highly unsteady, undergoing massive separation, as the rotor speed deviates from the design point. This study demonstrates the capability of the framework to simulate highly turbulent unsteady flows in a rotating turbomachinery environment. The results provide much needed insight and massive data to investigate novel design concepts for the US Army Future Vertical Lift program.
Medium- and Long-Term Integrated Demand Response of Integrated Energy System Based on System Dynamics
Authors: Ren Shuhui , Dou Xun , Wang Zhen , Wang Jun , Wang Xiangyan
Published: February 2020

For the integrated energy system of coupling electrical, cool and heat energy and gas and other forms of energy, the medium- and long-term integrated demand response of flexible load, energy storage and electric vehicles and other demand side resources is studied. It is helpful to mine the potentials of demand response of various energy sources in the medium- and long-term, stimulate the flexibility of integrated energy system, and improve the efficiency of energy utilization. Firstly, based on system dynamics, the response mode of demand response resources is analyzed from different time dimensions, and the long-term, medium-term and short-term behaviors of users participating in integrated demand response are considered comprehensively. An integrated demand response model based on medium-and long-term time dimension is established. Then the integrated demand response model of integrated energy system scheduling and flexible load, energy storage and electric vehicles as the main participants is established to simulate the response income of users participating in the integrated demand response project, and to provide data sources for the medium- and long-term integrated demand response system dynamics model. Finally, an example is given to analyze the differences in response behaviors of flexible load, energy storage and electric vehicle users in different time dimensions under the conditions of policy subsidy, regional location and user energy preferences in different stages of the integrated energy system.
Formalization of Cost and Utility in Microeconomics
Authors: Ahmed Asad , Hasan Osman , Awwad Falah , Bastaki Nabil
Published: February 2020

Cost and utility modeling of economics agents based on the differential theory is fundamental to the analysis of the microeconomics models. In particular, the first and second-order derivative tests are used to specify the desired properties of the cost and utility models. Traditionally, paper-and-pencil proof methods and computer-based tools are used to investigate the mathematical properties of these models. However, these techniques do not provide an accurate analysis due to their inability to exhaustively specify and verify the mathematical properties of the cost and utility models. Additionally, these techniques cannot accurately model and analyze pure continuous behaviors of the economic agents due to the utilization of computer arithmetic. On the other hand, an accurate analysis is direly needed in many safety and cost-critical microeconomics applications, such as agriculture and smart grids. To overcome the issues pertaining to the above-mentioned techniques, in this paper, we propose a theorem proving based methodology to formally analyze and specify the mathematical properties of functions used in microeconomics modeling. The proposed methodology is primarily based on a formalization of the derivative tests and root analysis of the polynomial functions, within the sound core of the HOL-Light theorem prover. We also provide a formalization of the first-order condition, which is used to analyze the maximum of the profit function in a higher-order-logic theorem prover. We then present the formal analysis of the utility, cost and first-order condition based on the polynomial functions. To illustrate the usefulness of proposed formalization, the proposed formalization is used to formally analyze and verify the quadratic cost and utility functions, which have been used in an optimal power flow problem and demand response (DR) program, respectively.
Potential for Optimization in European Power Plant Fleet Operation
Authors: Jesse Bernhard-Johannes , Morgenthaler Simon , Gillessen Bastian , Burges Simon , Kuckshinrichs Wilhelm
Published: February 2020

Energy policy makers need information about the greenhouse gas reduction potential that could be realized by changes to the operation of the currently existing European power plant fleet to enable short-term actions. Possible measures could reduce the climate impact of the European electricity system and, additionally, be realized quickly as new investments are avoided. In this paper, the Calliope based energy system model Stella of the European electricity system is presented and used for the first time, with the goal to quantify cost and CO 2 emissions optimal operation strategies of the existing European power plant fleet. By applying the model to six scenarios the results show that the greenhouse gas emissions of the European power plant fleet could be reduced by more than 50% with little additional costs compared to today’s power generation mix. It is shown that historic power plant operation follows only economic considerations while not fully covering its climate impact. The results demonstrate to policy makers the scale of reduction potential that could be achieved by short-term actions.
Forecasting Solar PV Output Using Convolutional Neural Networks with a Sliding Window Algorithm
Authors: Suresh Vishnu , Janik Przemyslaw , Rezmer Jacek , Leonowicz Zbigniew
Published: February 2020

The stochastic nature of renewable energy sources, especially solar PV output, has created uncertainties for the power sector. It threatens the stability of the power system and results in an inability to match power consumption and production. This paper presents a Convolutional Neural Network (CNN) approach consisting of different architectures, such as the regular CNN, multi-headed CNN, and CNN-LSTM (CNN-Long Short-Term Memory), which utilizes a sliding window data-level approach and other data pre-processing techniques to make accurate forecasts. The output of the solar panels is linked to input parameters such as irradiation, module temperature, ambient temperature, and windspeed. The benchmarking and accuracy metrics are calculated for 1 h, 1 day, and 1 week for the CNN based methods which are then compared with the results from the autoregressive moving average and multiple linear regression models in order to demonstrate its efficacy in making short-term and medium-term forecasts.
Wireless Sensor Network Energy Model and Its Use in the Optimization of Routing Protocols
Authors: Del-Valle-Soto Carolina , Mex-Perera Carlos , Nolazco-Flores Juan Arturo , Velázquez Ramiro , Rossa-Sierra Alberto
Published: February 2020

In this study, a Wireless Sensor Network (WSN) energy model is proposed by defining the energy consumption at each node. Such a model calculates the energy at each node by estimating the energy of the main functions developed at sensing and transmitting data when running the routing protocol. These functions are related to wireless communications and measured and compared to the most relevant impact on an energy standpoint and performance metrics. The energy model is validated using a Texas Instruments CC2530 system-on-chip (SoC), as a proof-of-concept. The proposed energy model is then used to calculate the energy consumption of a Multi-Parent Hierarchical (MPH) routing protocol and five widely known network sensors routing protocols: Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR), ZigBee Tree Routing (ZTR), Low Energy Adaptive Clustering Hierarchy (LEACH), and Power Efficient Gathering in Sensor Information Systems (PEGASIS). Experimental test-bed simulations were performed on a random layout topology with two collector nodes. Each node was running under different wireless technologies: Zigbee, Bluetooth Low Energy, and LoRa by WiFi. The objective of this work is to analyze the performance of the proposed energy model in routing protocols of diverse nature: reactive, proactive, hybrid and energy-aware. Experimental results show that the MPH routing protocol consumes 16%, 13%, and 5% less energy when compared to AODV, DSR, and ZTR, respectively; and it presents only 2% and 3% of greater energy consumption with respect to the energy-aware PEGASIS and LEACH protocols, respectively. The proposed model achieves a 97% accuracy compared to the actual performance of a network. Tests are performed to analyze the consumption of the main tasks of a node in a network.
Application Study on a New Hybrid Canning Structure of After-Treatment System for Diesel Engine
Authors: Zhao Chuang , Lou Diming , Zhang Yunhua , Lu Kai , Liu Shusen
Published: February 2020

Based on the airflow rotation concept, a new packaging structure was designed to meet the performance requirements of China-VI stage emission regulations. The new structure is a hybrid structure of spiral space with small blades and conical plates. The Computational Fluid Dynamics (CFD) simulation was used to analyze the velocity uniformity and ammonia uniformity of the flow field, and the results showed that velocity uniformity and ammonia uniformity were higher than 0.95, and the possibility of crystallization risk was very low. The actual performance of the new structural prototype was verified by means of engine bench testing. The test results were excellent and the conversion efficiency reached 0.96. The new selective catalytic reduction (SCR) urea mixed structure design greatly improved the conversion efficiency of the after-treatment system and has excellent anti-crystallization performance.