bluuebunny/crossref_metadata_2025 huggingface dataset:
Phytochemical Profiles, Antioxidant and Antibacterial Activities of Grape (Vitis vinifera L.) Seeds and Skin from Organic and Conventional Vineyards
Authors: Radulescu Cristiana , Buruleanu Lavinia Claudia , Nicolescu Cristina Mihaela , Olteanu Radu Lucian , Bumbac Marius , Holban Georgeta Carmen , Simal-Gandara Jesus
Published: October 2020

The therapeutic benefits of extracts obtained from different red grape fractions were thoroughly studied, however, data regarding the comparison of phytochemical extracts prepared from the same varieties coming from organic versus conventional management systems are rather lacking. The present study aimed at comparing some of the phytochemical characteristics and antimicrobial activity of hydroalcoholic (50% v/v) extracts obtained from four varieties of red grapes cultivated respectively in organic and conventional vineyards. Total flavonoid content, total phenolic compounds, and antioxidant activity were determined by molecular absorption spectroscopy. Antimicrobial activity of the studied extracts was evaluated against common bacterial strains isolated from different habitats according to specific lab procedures. The analyses were performed in solid broths by applying the disk diffusion method, which allowed for the simultaneous determination of the spectrum of the sensitivity of the tested bacteria as well as the values of the minimum inhibition concentration (MIC). It was found that favorable antagonistic activities against the tested bacteria strains were exhibited by the hydroalcoholic extracts from the seeds of the organic varieties, respectively the skin of the conventional varieties.
A New Approach Based on Glued Multi-Ultra High Molecular Weight Polyethylene Forms to Fabricate Bone Replacement Products
Authors: Dayyoub Tarek , Maksimkin Aleksey , Senatov Fedor , Kaloshkin Sergey , Anisimova Natalia , Kiselevskiy Mikhail
Published: October 2020

Three types of glue based on thiol-ene reaction, polyvinyl alcohol (PVA)/cellulose, and phenol formaldehyde were prepared and applied on modified ultra-high molecular weight polyethylene (UHMWPE) samples grafted by cellulose. In comparison with unmodified UHMWPE samples, T-peel tests on the modified and grafted UHMWPE films showed an increase in the peel strength values for the glues based on thiol-ene reaction, PVA/cellulose, and phenol formaldehyde by 40, 29, and 41 times, respectively. The maximum peel strength value of 0.62 Kg/cm was obtained for the glue based on phenol formaldehyde. Mechanical tests for the cylindrical multi-UHMWPE forms samples, made of porous UHMWPE as a trabecular layer and an armored layer (cortical layer) that consists of bulk and UHMWPE films, indicated an improvement in the mechanical properties of these samples for all glue types, as a result of the UHMWPE films existence and the increase in the number of their layers. The maximum compressive yield strength and compressive modulus values for the armored layer (bulk and six layers of the UHMWPE films using the glue based on thiol-ene reaction) were 44.1 MPa (an increase of 17%) and 1130 MPa (an increase of 36%), respectively, in comparison with one armored layer of bulk UHMWPE. A hemocompatibility test carried out on these glues clarified that the modified UHMWPE grafted by cellulose with glues based on PVA/cellulose and thiol-ene reaction were classified as biocompatible materials. These multi-UHMWPE forms composites can be considered a promising development for joint reconstruction.
High Silica Content Graphene/Natural Rubber Composites Prepared by a Wet Compounding and Latex Mixing Process
Authors: Wang Jian , Zhang Kaiye , Fei Guoxia , Salzano de Luna Martina , Lavorgna Marino , Xia Hesheng
Published: October 2020

The reduced graphene oxide (rGO) modified natural rubber composite (NR) filled with high contents of silica was prepared by a wet compounding and latex mixing process using a novel interface modifier cystamine dihydrochloride (CDHC) with coagulation ability. CDHC acts as a coagulation agent through electrostatic interaction with rGO, SiO2, and latex rubber particles during the latex-based preparation process, while in the obtained silica/graphene/natural rubber composites, CDHC acts as an interface modifier. Compared with the composites prepared by the conventional mechanical mixing method, the dispersion of both rGO and SiO2 in the composites made by a wet compounding and latex mixing process is improved. As a result, the obtained silica/graphene/natural rubber composite prepared by this new method has good comprehensive properties. A Dynamic Mechanical Test suggests that the tan δ values of the composites at 60 °C decrease, indicating a low rolling resistance with increasing the graphene content at a low strain, but it increases at a higher strain. This unique feature for this material provides an advantage in the rubber tire application.
Nanoparticles of Quaternary Ammonium Polyethylenimine Derivatives for Application in Dental Materials
Authors: Chrószcz Marta , Barszczewska-Rybarek Izabela
Published: October 2020

Various quaternary ammonium polyethylenimine (QA-PEI) derivatives have been synthesized in order to obtain nanoparticles. Due to their antibacterial activity and non-toxicity towards mammalian cells, the QA-PEI nanoparticles have been tested extensively regarding potential applications as biocidal additives in various dental composite materials. Their impact has been examined mostly for dimethacrylate-based restorative materials; however, dental cements, root canal pastes, and orthodontic adhesives have also been tested. Results of those studies showed that the addition of small quantities of QA-PEI nanoparticles, from 0.5 to 2 wt.%, led to efficient and long-lasting antibacterial effects. However, it was also discovered that the intensity of the biocidal activity strongly depended on several chemical factors, including the degree of crosslinking, length of alkyl telomeric chains, degree of N-alkylation, degree of N-methylation, counterion type, and pH. Importantly, the presence of QA-PEI nanoparticles in the studied dental composites did not negatively impact the degree of conversion in the composite matrix, nor its mechanical properties. In this review, we summarized these features and functions in order to present QA-PEI nanoparticles as modern and promising additives for dental materials that can impart unique antibacterial characteristics without deteriorating the products’ structures or mechanical properties.
A Local-Exchange Model of Folding Chain Surface of Polymer Crystal Based on Worm-Like Chain Model within Single-Chain in Mean-Field Theory
Authors: Xiao Hongyi , Zhang Xinghua , Yan Dadong
Published: October 2020

The structure of amorphous layer of folding surface controls the properties of the polymer lamellar crystal, which consists of chains with a loop conformation. The surface tension depends on the length and the distance between two injection points of the loop which involving the reptation motion and lateral exchange motion of the stems. In the present work, a local-exchange motion model based on the worm-like chain model is developed to investigate the effects of lateral motion of stems on the release the surface tension. The optimal distance between two injection points is determined by the balance of chain bending energy and conformational entropy. The numerical results provide evidences to the adjacent re-entry model for various loop lengths. A possible explanation involving density of injection points is proposed to interpret the mechanism.
Effect of Drying and Steeping Temperatures on the Phenolic Content, Antioxidant Activity, Aromatic Compounds and Sensory Properties of Cunila polyantha Benth. Infusions
Authors: Silva-Ramírez Karla Araceli , Álvarez-Bernal Dioselina , Oregel-Zamudio Ernesto , Guízar-González Cecilia , Medina-Medrano José Roberto
Published: October 2020

Cunila polyantha Benth. (Lamiaceae), an aromatic plant endemic to Mexico, is used in traditional medicine as tea infusions. In this study, the effects of different drying and steeping temperatures on the phenolic content and composition, antioxidant activity, volatile composition, and sensory properties of C. polyantha infusions were determined. Commercial green tea (Camellia sinensis L. Kuntze) was used as a control. The phenolic compounds identified in the C. polyantha infusions by high-performance liquid chromatography (HPLC) include phenolic acids such as gallic acid, chlorogenic acid, caffeic acid, and p-coumaric acid, flavonoids such as epigallocatechin gallate, protocatechin, quercetin, and naringenin, as well as the phenolic aldehyde vanillin. The C. polyantha infusions showed scavenging activity of DPPH• and ABTS•+ radicals as well as relevant antioxidant capacity, which was dependent on tea preparation conditions. A total of 46 volatile organic compounds (VOCs) were detected from the leaves and flowers of C. polyantha, while in the control group, a total of 30 VOCs were identified. Differences in consumer acceptability of C. polyantha infusions prepared at different conditions were observed. This research highlights the importance of linking sensory and chemical data to obtain the best sensorial quality and the optimal nutraceutical properties in C. polyantha infusions.
Mixing in Turbulent Flows: An Overview of Physics and Modelling
Authors: Pozorski Jacek , Wacławczyk Marta
Published: October 2020

Turbulent flows featuring additional scalar fields, such as chemical species or temperature, are common in environmental and industrial applications. Their physics is complex because of a broad range of scales involved; hence, efficient computational approaches remain a challenge. In this paper, we present an overview of such flows (with no particular emphasis on combustion, however) and we recall the major types of micro-mixing models developed within the statistical approaches to turbulence (the probability density function approach) as well as in the large-eddy simulation context (the filtered density function). We also report on some trends in algorithm development with respect to the recent progress in computing technology.
Review of Sulfuric Acid Decomposition Processes for Sulfur-Based Thermochemical Hydrogen Production Cycles
Authors: Corgnale Claudio , Gorensek Maximilian B. , Summers William A.
Published: October 2020

Thermochemical processes based on sulfur compounds are among the most developed systems to produce hydrogen through water splitting. Due to their operating conditions, sulfur cycles are suited to be coupled with either nuclear or solar plants for renewable hydrogen production. A critical review of the most promising sulfur cycles, namely the Hybrid Sulfur, the Sulfur Iodine, the Sulfur Bromine and the Sulfur Ammonia processes, is given, including the work being performed for each cycle and discussing their maturity and performance for nuclear and solar applications. Each sulfur-based process is comprised of a sulfuric acid thermal section, where sulfuric acid is concentrated and decomposed to sulfur dioxide, water and oxygen, which is then separated from the other products and extracted. A critical review of the main solutions adopted for the H2SO4 thermal section, including reactor configurations, catalytic formulations, constitutive materials and chemical process configurations, is presented.
Non-Intrusive Monitoring Algorithm for Resident Loads with Similar Electrical Characteristic
Authors: Wu Sheng , Lo Kwok L.
Published: October 2020

Non-intrusive load monitoring is a vital part of an overall load management scheme. One major disadvantage of existing non-intrusive load monitoring methods is the difficulty to accurately identify loads with similar electrical characteristics. To overcome the various switching probability of loads with similar characteristics in a specific time period, a new non-intrusive load monitoring method is proposed in this paper which will modify monitoring results based on load switching probability distribution curve. Firstly, according to the addition theorem of load working currents, the complex current is decomposed into the independently working current of each load. Secondly, based on the load working current, the initial identification of load is achieved with current frequency domain components, and then the load switching times in each hour is counted due to the initial identified results. Thirdly, a back propagation (BP) neural network is trained by the counted results, the switching probability distribution curve of an identified load is fitted with the BP neural network. Finally, the load operation pattern is profiled according to the switching probability distribution curve, the load operation pattern is used to modify identification result. The effectiveness of the method is verified by the measured data. This approach combines the operation pattern of load to modify the identification results, which improves the ability to identify loads with similar electrical characteristics.
Mining and Restoration Monitoring of Rare Earth Element (REE) Exploitation by New Remote Sensing Indicators in Southern Jiangxi, China
Authors: Xie Lifeng , Wu Weicheng , Huang Xiaolan , Ou Penghui , Lin Ziyu , Zhiling Wang , Song Yong , Lang Tao , Huangfu Wenchao , Zhang Yang , Zhou Xiaoting , Fu Xiao , Li Jie , Jiang Jingheng , Zhang Ming , Zhang Zhenjiang , Qin Yaozu , Peng Shanling , Shao Chongjian , Bai Yonghui
Published: October 2020

Rare earth elements (REEs) are widely used in various industries. The open-pit mining and chemical extraction of REEs in the weathered crust in southern Jiangxi, China, since the 1970s have provoked severe damages to the environment. After 2010, different restorations have been implemented by various enterprises, which seem to have a spatial variability in both management techniques and efficiency from one mine to another. A number of vegetation indices, e.g., normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), enhanced vegetation index (EVI) and atmospherically resistant vegetation index (ARVI), can be used for this kind of monitoring and assessment but lack sensitivity to subtle differences. For this reason, the main objective of this study was to explore the possibility to develop new, mining-tailored remote sensing indicators to monitor the impacts of REE mining on the environment and to assess the effectiveness of its related restoration using multitemporal Landsat data from 1988 to 2019. The new indicators, termed mining and restoration assessment indicators (MRAIs), were developed based on the strong contrast of spectral reflectance, albedo, land surface temperature (LST) and tasseled cap brightness (TCB) of REE mines between mining and postmining restoration management. These indicators were tested against vegetation indices such as NDVI, EVI, SAVI and generalized difference vegetation index (GDVI), and found to be more sensitive. Of similar sensitivity to each other, one of the new indicators was employed to conduct the restoration assessment of the mined areas. Six typically managed mines with different restoration degrees and management approaches were selected as hotspots for a comparative analysis to highlight their temporal trajectories using the selected MRAI. The results show that REE mining had experienced a rapid expansion in 1988–2010 with a total mined area of about 66.29 km2 in the observed counties. With implementation of the post-2010 restoration measures, an improvement of varying degrees in vegetation cover in most mines was distinguished and quantified. Hence, this study with the newly developed indicators provides a relevant approach for assessing the sustainable exploitation and management of REE resources in the study area.
Application of Google Earth Engine Cloud Computing Platform, Sentinel Imagery, and Neural Networks for Crop Mapping in Canada
Authors: Amani Meisam , Kakooei Mohammad , Moghimi Armin , Ghorbanian Arsalan , Ranjgar Babak , Mahdavi Sahel , Davidson Andrew , Fisette Thierry , Rollin Patrick , Brisco Brian , Mohammadzadeh Ali
Published: October 2020

The ability of the Canadian agriculture sector to make better decisions and manage its operations more competitively in the long term is only as good as the information available to inform decision-making. At all levels of Government, a reliable flow of information between scientists, practitioners, policy-makers, and commodity groups is critical for developing and supporting agricultural policies and programs. Given the vastness and complexity of Canada’s agricultural regions, space-based remote sensing is one of the most reliable approaches to get detailed information describing the evolving state of the country’s environment. Agriculture and Agri-Food Canada (AAFC)—the Canadian federal department responsible for agriculture—produces the Annual Space-Based Crop Inventory (ACI) maps for Canada. These maps are valuable operational space-based remote sensing products which cover the agricultural land use and non-agricultural land cover found within Canada’s agricultural extent. Developing and implementing novel methods for improving these products are an ongoing priority of AAFC. Consequently, it is beneficial to implement advanced machine learning and big data processing methods along with open-access satellite imagery to effectively produce accurate ACI maps. In this study, for the first time, the Google Earth Engine (GEE) cloud computing platform was used along with an Artificial Neural Networks (ANN) algorithm and Sentinel-1, -2 images to produce an object-based ACI map for 2018. Furthermore, different limitations of the proposed method were discussed, and several suggestions were provided for future studies. The Overall Accuracy (OA) and Kappa Coefficient (KC) of the final 2018 ACI map using the proposed GEE cloud method were 77% and 0.74, respectively. Moreover, the average Producer Accuracy (PA) and User Accuracy (UA) for the 17 cropland classes were 79% and 77%, respectively. Although these levels of accuracies were slightly lower than those of the AAFC’s ACI map, this study demonstrated that the proposed cloud computing method should be investigated further because it was more efficient in terms of cost, time, computation, and automation.
Radiological Identification of Near-Surface Mineralogical Deposits Using Low-Altitude Unmanned Aerial Vehicle
Authors: Martin Peter G. , Connor Dean T. , Estrada Natalia , El-Turke Adel , Megson-Smith David , Jones Chris P. , Kreamer David K. , Scott Thomas B.
Published: October 2020

An ever-increasing global population and unabating technological growth have resulted in a relentless appetite for mineral resources, namely rare earth elements, fuel minerals and those utilised in electronics applications, with the price of such species continuing to climb. In contrast to more established large-scale and high-cost exploration methodologies, this work details the application of novel multi-rotor unmanned aerial vehicles equipped with miniaturised radiation detectors for the objective of undertaking resource exploration at lower costs, with greater autonomy and at considerably enhanced higher spatial resolutions; utilizing the ore material’s inherent low levels of characteristic radioactivity. As we demonstrate at the former Wooley Mine site in Arizona, USA, a legacy Cu/Fe prospect where the 600 by 275 m ore body (with a maximum deposit depth of 150 m), it is shown that such a fusion of commercially available low-altitude multi-rotor aerial technology combined with cutting-edge micro-electronics and detector materials is capable of accurately assessing the spatial distribution and associated radiogenic signatures of commercially valuable surface/near-surface ore bodies. This integrated system, deployed at an autonomously controlled consistent survey altitude and using constant grid transects/separations, is shown to be able to delineate the mineral-containing ore deposits on the site, the location(s) of former mine workings and other surface manifestations. Owing to its advantageous costs alongside its ease of operation and subsequent data-processing, through the adoption of this system, it is envisaged that less economically developed countries would now possess the means through which to evaluate and appropriately quantify their mineral wealth without the significant initial expenditure needed to equip themselves with otherwise prohibitively expensive technologies.
Development of a Mobile Device for Odor Identification and Optimization of Its Measurement Protocol Based on the Free-Hand Measurement
Authors: Imamura Gaku , Yoshikawa Genki
Published: October 2020

Practical applications of machine olfaction have been eagerly awaited. A free-hand measurement, in which a measurement device is manually exposed to sample odors, is expected to be a key technology to realize practical machine olfaction. To implement odor identification systems based on the free-hand measurement, the comprehensive development of a measurement system including hardware, measurement protocols, and data analysis is necessary. In this study, we developed palm-size wireless odor measurement devices equipped with Membrane-type Surface stress Sensors (MSS) and investigated the effect of measurement protocols and feature selection on odor identification. By using the device, we measured vapors of liquids as odor samples through the free-hand measurement in different protocols. From the measurement data obtained with these protocols, datasets of transfer function ratios (TFRs) were created and analyzed by clustering and machine learning classification. It has been revealed that TFRs in the low-frequency range below 1 Hz notably contributed to vapor identification because the frequency components in that range reflect the dynamics of the detection mechanism of MSS. We also showed the optimal measurement protocol for accurate classification. This study has shown a guideline of the free-hand measurement and will contribute to the practical implementation of machine olfaction in society.
Addressed Fiber Bragg Structures in Load-Sensing Wheel Hub Bearings
Authors: Agliullin Timur , Gubaidullin Robert , Sakhabutdinov Airat , Morozov Oleg , Kuznetsov Artem , Ivanov Valentin
Published: October 2020

The work presents an approach to instrument the load-sensing bearings for automotive applications for estimation of the loads acting on the wheels. The system comprises fiber-optic sensors based on addressed fiber Bragg structures (AFBS) with two symmetrical phase shifts. A mathematical model for load–deformation relation is presented, and the AFBS interrogation principle is described. The simulation includes (i) modeling of vehicle dynamics in a split-mu braking test, during which the longitudinal wheel loads are obtained, (ii) the subsequent estimation of bearing outer ring deformation using a beam model with simply supported boundary conditions, (iii) the conversion of strain into central frequency shift of AFBS, and (iv) modeling of the beating signal at the photodetector. The simulation results show that the estimation error of the longitudinal wheel force from the strain data acquired from a single measurement point was 5.44% with a root-mean-square error of 113.64 N. A prototype load-sensing bearing was instrumented with a single AFBS sensor and mounted in a front right wheel hub of an experimental vehicle. The experimental setup demonstrated comparable results with the simulation during the braking test. The proposed system with load-sensing bearings is aimed at estimation of the loads acting on the wheels, which serve as input parameters for active safety systems, such as automatic braking, adaptive cruise control, or fully automated driving, in order to enhance their effectiveness and the safety of the vehicle.
An Efficient Residual-Based Method for Railway Image Dehazing
Authors: Liu Qinghong , Qin Yong , Xie Zhengyu , Cao Zhiwei , Jia Limin
Published: October 2020

Trains shuttle in semiopen environments, and the surrounding environment plays an important role in the safety of train operation. The weather is one of the factors that affect the surrounding environment of railways. Under haze conditions, railway monitoring and staff vision could be blurred, threatening railway safety. This paper tackles image dehazing for railways. The contributions of this paper for railway video image dehazing are as follows: (1) this paper proposes an end-to-end residual block-based haze removal method that consists of two subnetworks, namely fine-grained and coarse-grained network can directly generate the clean image from input hazy image, called RID-Net (Railway Image Dehazing Network). (2) The combined loss function (per-pixel loss and perceptual loss functions) is proposed to achieve both low-level features and high-level features so to generate the high-quality restored images. (3) We take the full-reference criterion (PSNR&SSIM), object detection, running time, and sensory vision to evaluate the proposed dehazing method. Experimental results on railway synthesized dataset, benchmark indoor dataset, and real-world dataset demonstrate our method has superior performance compared to the state-of-the-art methods.
Development of Test Equipment for Pedestrian-Automatic Emergency Braking Based on C-NCAP (2018)
Authors: Song Zhiqiang , Cao Libo , Chou Clifford C.
Published: October 2020

In order to evaluate the effectiveness of a pedestrian-automatic emergency braking (PAEB) system on pedestrian protection, a set of PAEB test equipment was developed according to the test requirement of China-New Car Assessment Program (C-NCAP) (2018) in this study. In the aspect of system control strategy, global positioning system (GPS) differential positioning was used to achieve the required measurement and positioning accuracy, the collaborative control between the PAEB test equipment and automated driving robot (ADR) was achieved by wireless communication, and the motion state of the dummy target in the PAEB system was controlled by using the S-shaped-curve velocity control method. Part of the simulations and field tests were conducted according to the scenario requirements specified in C-NCAP (2018). The experimental and simulated results showed that the test equipment demonstrated high accuracy and precision in the process of testing, the dummy target movement was smooth and stable, complying with the requirements of PAEB tests set forth in C-NCAP (2018), and yielding satisfactory results as designed. Subsequently, the performance of the AEB of a vehicle under test (VUT) was conducted and the score for star-rating to evaluate the performance level of AEB calculated. Results indicated the developed test equipment in this study could be used to evaluate the performance of the PAEB system with effectiveness.
Processing of Bathymetric Data: The Fusion of New Reduction Methods for Spatial Big Data
Authors: Wlodarczyk-Sielicka Marta , Blaszczak-Bak Wioleta
Published: October 2020

Floating autonomous vehicles are very often equipped with modern systems that collect information about the situation under the water surface, e.g., the depth or type of bottom and obstructions on the seafloor. One such system is the multibeam echosounder (MBES), which collects very large sets of bathymetric data. The development and analysis of such large sets are laborious and expensive. Reduction of the spatial data obtained from bathymetric and other systems collecting spatial data is currently widely used. In commercial programs used in the development of data from hydrographic systems, methods of interpolation to a specific mesh size are very frequently used. The authors of this article previously proposed original the true bathymetric data reduction method (TBDRed) and Optimum Dataset (OptD) reduction methods, which maintain the actual position and depth for each of the measured points, without their interpolation. The effectiveness of the proposed methods has already been presented in previous articles. This article proposes the fusion of original reduction methods, which is a new and innovative approach to the problem of bathymetric data reduction. The article contains a description of the methods used and the methodology of developing bathymetric data. The proposed fusion of reduction methods allows the generation of numerical models that can be a safe, reliable source of information, and a basis for design. Numerical models can also be used in comparative navigation, during the creation of electronic navigation maps and other hydrographic products.
MongoDB Database as Storage for GPON Frames
Authors: Holik Martin , Horvath Tomas , Oujezsky Vaclav , Munster Petr , Tomasov Adrian , Valach Sobeslav
Published: October 2020

This work is focused on creating an open-source software-based solution for monitoring traffic transmitted through gigabit passive optical network. In this case, the data are captured by the field-programmable gate array (FPGA) card and reassembled using parsing software from a passive optical network built on the International Telecommunication Unit telecommunication section (ITU-T) G.984 gigabit-capable passive optical network GPON recommendation. Then, the captured frames are converted by suitable software into GPON frames, which will be further processed for analysis. Due to the high transfer rate of GPON recommendations, the work describes the issue of writing to the Mongo database system. In order to achieve the best possible results and minimal loss of transmitted frames, a series of tests were performed. The proposed test scenarios are based on different database writing approaches and are implemented in the Python and C# programming languages. Based on our results, it has been shown that the high processing speed is too high for Python processing. Critical operations must be implemented in the C# programming language. Due to rapid application development, Python can only be used for noncritical time-consuming data processing operations.
A Multi-Node Magnetic Positioning System with a Distributed Data Acquisition Architecture
Authors: Santoni Francesco , De Angelis Alessio , Moschitta Antonio , Carbone Paolo
Published: October 2020

We present a short-range magnetic positioning system that can track in real-time both the position and attitude (i.e., the orientation of the principal axes of an object in space) of up to six moving nodes. Moving nodes are small solenoids coupled with a capacitor (resonant circuit) and supplied with an oscillating voltage. Active moving nodes are detected by measuring the voltage that they induce on a three-dimensional matrix of passive coils. Data on each receiving coil are acquired simultaneously by a distributed data-acquisition architecture. Then, they are sent to a computer that calculates the position and attitude of each moving node. The entire process is run in real-time: the system can perform 62 position and attitude measurements per second when tracking six nodes simultaneously and up to 124 measurements per second when tracking one node only. Different active nodes are identified using a frequency-division multiple access technique. The position and angular resolution of the system have been experimentally estimated by tracking active nodes along a reference trajectory traced by a robotic arm. The factors limiting the viability of upscaling the system with more than six active nodes are discussed.
Virtual Reality as a Portable Alternative to Chromotherapy Rooms for Stress Relief: A Preliminary Study
Authors: Vaquero-Blasco Miguel A. , Perez-Valero Eduardo , Lopez-Gordo Miguel Angel , Morillas Christian
Published: October 2020

Chromotherapy rooms are comfortable spaces, used in places like special needs schools, where stimuli are carefully selected to cope with stress. However, these rooms are expensive and require a space that cannot be reutilized. In this article, we propose the use of virtual reality (VR) as an inexpensive and portable alternative to chromotherapy rooms for stress relief. We recreated a chromotherapy room stress relief program using a commercial head mounted display (HD). We assessed the stress level of two groups (test and control) through an EEG biomarker, the relative gamma, while they experienced a relaxation session. First, participants were stressed using the Montreal imaging stress task (MIST). Then, for relaxing, the control group utilized a chromotherapy room while the test group used virtual reality. We performed a hypothesis test to compare the self- perceived stress level at different stages of the experiment and it yielded no significant differences in reducing stress for both groups, during relaxing (p-value: 0.8379, α = 0.05) or any other block. Furthermore, according to participant surveys, the use of virtual reality was deemed immersive, comfortable and pleasant (3.9 out of 5). Our preliminary results validate our approach as an inexpensive and portable alternative to chromotherapy rooms for stress relief.
Optimizing Router Placement of Indoor Wireless Sensor Networks in Smart Buildings for IoT Applications
Authors: Alanezi Mohammed A. , Bouchekara Houssem R. E. H. , Javaid Muhammad S.
Published: October 2020

Internet of Things (IoT) is characterized by a system of interconnected devices capable of communicating with each other to carry out specific useful tasks. The connection between these devices is ensured by routers distributed in a network. Optimizing the placement of these routers in a distributed wireless sensor network (WSN) in a smart building is a tedious task. Computer-Aided Design (CAD) programs and software can simplify this task since they provide a robust and efficient tool. At the same time, experienced engineers from different backgrounds must play a prominent role in the abovementioned task. Therefore, specialized companies rely on both; a useful CAD tool along with the experience and the flair of a sound expert/engineer to optimally place routers in a WSN. This paper aims to develop a new approach based on the interaction between an efficient CAD tool and an experienced engineer for the optimal placement of routers in smart buildings for IoT applications. The approach follows a step-by-step procedure to weave an optimal network infrastructure, having both automatic and designer-intervention modes. Several case studies have been investigated, and the obtained results show that the developed approach produces a synthesized network with full coverage and a reduced number of routers.
Pilot Decontamination Using Asynchronous Fractional Pilot Scheduling in Massive MIMO Systems
Authors: Zahoor Muhammad Irshad , Dou Zheng , Shah Syed Bilal Hussain , Khan Imran Ullah , Ayub Sikander , Reddy Gadekallu Thippa
Published: October 2020

Due to large spectral efficiency and low power consumption, the Massive Multiple-Input-Multiple-Output (MIMO) became a promising technology for the 5G system. However, pilot contamination (PC) limits the performance of massive MIMO systems. Therefore, two pilot scheduling schemes (i.e., Fractional Pilot Reuse (FPR) and asynchronous fractional pilot scheduling scheme (AFPS)) are proposed, which significantly mitigated the PC in the uplink time division duplex (TDD) massive MIMO system. In the FPR scheme, all the users are distributed into the central cell and edge cell users depending upon their signal to interference plus noise ratio (SINR). Further, the capacity of central and edge users is derived in terms of sum-rate, and the ideal number of the pilot is calculated which significantly maximized the sum rate. In the proposed AFPS scheme, the users are grouped into central users and edge users depending upon the interference they receive. The central users are assigned the same set of pilots because these users are less affected by interference, while the edge users are assigned the orthogonal pilots because these users are severely affected by interference. Consequently, the pilot overhead is reduced and inter-cell interference (ICI) is minimized. Further, results verify that the proposed schemes outperform the previous proposed traditional schemes, in terms of improved sum rates.
Indonesian Science, Mathematics, and Engineering Preservice Teachers’ Experiences in STEM-TPACK Design-Based Learning
Authors: Chai Ching Sing , Rahmawati Yuli , Jong Morris Siu-Yung
Published: October 2020

This paper presents Indonesian preservice teachers’ experiences in designing a Science Technology Engineering and Mathematics-Technological Pedagogical Content Knowledge (STEM-TPACK) learning website. The framework of TPACK was expanded to include all STEM subjects for the synthesis of the theoretical/design framework. The STEM-TPACK framework is further epitomized as a replicable website to support preservice teachers in designing STEM lesson activities. The framework is also employed to examine preservice teachers’ efficacies and experiences in learning how to design the learning website. Thirty-seven second- and third-year Indonesian preservice teachers from science, mathematics, computer science, and engineering backgrounds formed interdisciplinary groups to design the STEM-TPACK website based on the current secondary school curricula. Data were collected from TPACK-STEM questionnaires, interviews, reflective journals, and observation. The preservice teachers’ efficacy for their STEM-TPACK developed significantly, with large effect sizes, after they co-designed the websites. The results also indicate that the preservice teachers faced challenges in communicating their discipline-based content knowledge when developing the STEM projects. Contextualizing and connecting their content knowledge with real-world design challenges was also difficult for them. Consequently, the preservice teachers realized that teaching is a complex matter, especially when they need to integrate the different disciplines for STEM education. However, this was viewed in a positive light for professional development. This study implies that preservice teachers may benefit from learning by design, employing the TPACK framework in the social setting of interdisciplinary STEM communities.
Water Scarcity and Wastewater Reuse in Crop Irrigation
Authors: Ungureanu Nicoleta , Vlăduț Valentin , Voicu Gheorghe
Published: October 2020

Due to climate change, two-thirds of mankind will face water scarcity by 2025, while by 2050, global food production must increase by at least 50% to feed 9 billion people. To overcome water scarcity, 15 million m3/day of untreated wastewater is used globally for crop irrigation, polluting the soil with pathogens, heavy metals and excess salts. Since 10% of the global population consumes food from crops irrigated with wastewater, pathogens transmitted through the food chain cause diseases especially in young children and women. In this paper, we discuss the status of water scarcity and the challenges to food security, the reuse of wastewater in agriculture and the possible risks to human and environmental health. The efficiency of different irrigation systems in limiting the risks of wastewater reuse and the latest regulations of the European Commission on effluent recovery are also presented. Hence, we emphasize that irrigation offers real perspectives for large-scale recovery of wastewater, helping to reduce the deficit and conserve water resources, and increasing food safety, with the express mention that investments must be made in wastewater treatment plants and wastewater must be properly treated before recovery, to limit the risks on human health and the environment.
A Review on Practical Application and Potentials of Phytohormone-Producing Plant Growth-Promoting Rhizobacteria for Inducing Heavy Metal Tolerance in Crops
Authors: Nazli Farheen , Mustafa Adnan , Ahmad Maqshoof , Hussain Azhar , Jamil Moazzam , Wang Xiukang , Shakeel Qaiser , Imtiaz Muhammad , El-Esawi Mohamed A.
Published: October 2020

Water scarcity and high input costs have compelled farmers to use untreated wastewater and industrial effluents to increase profitability of their farms. Normally, these effluents improve crop productivity by serving as carbon source for microbes, providing nutrients to plants and microbes, and improving soil physicochemical and biological properties. They, however, may also contain significant concentrations of potential heavy metals, the main inorganic pollutants affecting plant systems, in addition to soil deterioration. The continuous use of untreated industrial wastes and agrochemicals may lead to accumulation of phytotoxic concentration of heavy metals in soils. Phytotoxic concentration of heavy metals in soils has been reported in Pakistan along the road sides and around metropolitan areas, which may cause its higher accumulation in edible plant parts. A number of bacterial that can induce heavy metal tolerance in plants due to their ability to produce phytohormones strains have been reported. Inoculation of crop plants with these microbes can help to improve their growth and productivity under normal, as well as stressed, conditions. This review reports the recent developments in heavy metal pollution as one of the major inorganic sources, the response of plants to these contaminants, and heavy metal stress mitigation strategies. We have also summarized the exogenous application of phytohormones and, more importantly, the use of phytohormone-producing, heavy metal-tolerant rhizobacteria as one of the recent tools to deal with heavy metal contamination and improvement in productivity of agricultural systems.
Mechanical Properties of Cement-Based Materials with Recycled Plastic: A Review
Authors: Park Jun Kil , Kim Min Ook
Published: October 2020

This study summarizes existing studies on plastic recycling to determine whether ocean plastics with high pollution degrees could be used for cement-based materials. In particular, the methods to recycle plastic waste, the effects of recycled plastic on the physical and mechanical properties of cement-based materials, and their effective usage were investigated. Workability, density, compressive strength, split tensile strength, and flexural strength of cement-based materials with recycled plastics were reviewed and divided into recycled aggregates and fibers. Based on the previous investigation, the direction of research necessary to recycle marine plastics is suggested. As the amount of recycled plastic aggregate increased, the mechanical strength of cement-based materials decreased. The recycled plastic aggregate lowered the density and increased porosity of the cement-based material. Meanwhile, recycled plastic fibers reduced the compressive strength but improved the tensile strength; to effectively improve tensile strength, a volume content of less than 1.5% should be added to prevent balling fibers. Furthermore, an appropriate aspect ratio should be determined based on the type of plastic to be used.
Resting EEG Asymmetry Markers of Multiple Facets of the Behavioral Approach System: A LORETA Analysis
Authors: Pascalis Vilfredo De , Cirillo Giuliana , Vecchio Arianna
Published: October 2020

Previously published models of frontal activity linked high relative left frontal activity to the behavioral approach system (BAS) and impulsivity. Additionally, these models did not account for BAS facets encompassing the anticipation of reward, i.e., goal-driven persistence (BAS–GDP) and reward interest (BAS–RI), from those that deal with the actual hedonic experience of reward, i.e., reward reactivity (BAS–RR) and impulsivity (BAS–I). Using resting electroencephalographic (EEG) recordings, the source localization (LORETA) method allowed us to calculate the hemispheric asymmetry of the current density within the alpha band (7.5–13 Hz) in ten regions of interest. Compared to low BAS subtrait scorers, high BAS subtrait scorers (except for BAS–I) were correlated with greater relative left-sided activity in the superior frontal gyrus (BA10). Further, an isolated effective coherence (iCOH) analysis of the beta activity (21 Hz) disclosed that high impulsive scorers as compared to low impulsive ones had higher connectivity between the superior frontal gyrus and middle temporal gyrus, which was not compensated for by enhanced inhibitory alpha (11 Hz) connectivity between these regions. For the beta frequency, we also found in highly impulsive individuals that (i) both left and right middle temporal lobes directly influenced the activity of the left and right superior frontal lobes, and (ii) a clear decoupling between left and right superior frontal lobes. These findings could indicate reduced control by the supervisory system in more impulsive individuals.
Push or Pull for a Better Selectivity? A Study on the Electronic Effects of Substituents of the Pyridine Ring on the Enantiomeric Recognition of Chiral Pyridino-18-Crown-6 Ethers
Authors: Szemenyei Balázs , Novotny Balázs , Zsolnai Sarolta , Miskolczy Zsombor , Biczók László , Takács Attila , Kollár László , Drahos László , Móczár Ildikó , Huszthy Péter
Published: October 2020

Seven dimethyl-substituted optically active pyridino-18-crown-6 ethers containing various substituents at position 4 of the pyridine ring were studied with regards to the electron-donating and -withdrawing effects of substituents on enantiomeric recognition. In order to compile this set of compounds, we prepared four novel pyridino-18-crown-6 ethers, including an intermediate of a new synthetic route for a formerly reported crown ether. The discriminating ability of these pyridino-crown ethers with C2-symmetry toward the enantiomers of protonated primary amines was examined by isothermal titration calorimetry.
Erratum: Abbas, M.; Iqbal, H.; De la Sen, M. Generation of Julia and Madelbrot Sets via Fixed Points. Symmetry 2020, 12, 86
Authors: Abbas Mujahid , Iqbal Hira , De la Sen Manuel
Published: October 2020

The authors wish to make the following corrections to their paper [...]
Toward Social Media Content Recommendation Integrated with Data Science and Machine Learning Approach for E-Learners
Authors: Shahbazi Zeinab , Byun Yung Cheol
Published: October 2020

Electronic Learning (e-learning) has made a great success and recently been estimated as a billion-dollar industry. The users of e-learning acquire knowledge of diversified content available in an application using innovative means. There is much e-learning software available—for example, LMS (Learning Management System) and Moodle. The functionalities of this software were reviewed and we recognized that learners have particular problems in getting relevant recommendations. For example, there might be essential discussions about a particular topic on social networks, such as Twitter, but that discussion is not linked up and recommended to the learners for getting the latest updates on technology-updated news related to their learning context. This has been set as the focus of the current project based on symmetry between user project specification. The developed project recommends relevant symmetric articles to e-learners from the social network of Twitter and the academic platform of DBLP. For recommendations, a Reinforcement learning model with optimization is employed, which utilizes the learners’ local context, learners’ profile available in the e-learning system, and the learners’ historical views. The recommendations by the system are relevant tweets, popular relevant Twitter users, and research papers from DBLP. For matching the local context, profile, and history with the tweet text, we recognized that terms in the e-learning system need to be expanded to cover a wide range of concepts. However, this diversification should not include such terms which are irrelevant. To expand terms of the local context, profile and history, the software used the dataset of Grow-bag, which builds concept graphs of large-scale Computer Science topics based on the co-occurrence scores of Computer Science terms. This application demonstrated the need and success of e-learning software that is linked with social media and sends recommendations for the content being learned by the e-Learners in the e-learning environment. However, the current application only focuses on the Computer Science domain. There is a need for generalizing such applications to other domains in the future.