bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Nanodispersed Catalysts in Microwave Application during the Development of Unconventional Hydrocarbon Reserves: A Review of Potential Applications
Authors: Vakhin Alexey V. , Khelkhal Mohammed Amine , Tajik Arash , Gafurov Marat R. , Morozov Oleg G. , Nasybullin Aydar R. , Karandashov Sergey A. , Ponomarev Andrey A. , Krapivnitskaia Tatiana O. , Glyavin Mikhail Yu. , Slavkina Olga V. , Shchekoldin Konstantin A.
Published: February 2021

Electromagnetic impact on oil reservoir manifests itself in various physical and chemical phenomena and attracts a significant scientific and technological interest. Microwave (MW) radiation heating can be more efficient for the oil recovery than heat transfer by convection or by thermal conduction. MW influence can also lead to significant changes in the physicochemical and rheological properties of oil caused by chemical processes of transformation of the oil high-molecular components such as resins and asphaltenes. The efficiency of transition-metal catalysts applied for the in-situ conversion of hydrocarbons directly in the reservoir might be significantly increased by exposing the oil formation to MW radiation. Actually, transition metals nanoparticles and their oxides are considered as active absorbers of MW radiation and; therefore, they can be used to intensify MW impact on the reservoir. Catalyst particles dispersed in the formation provide enhanced MW sweep. Taken together, the functioning of the catalysts and the effect of microwave radiation provide deep conversion of resins and asphaltenes, a decrease in the viscosity of the produced oil and an increase in oil recovery factor, along with a decrease in water cut of the well production. The present review analyzes the latest works on the combined application of microwave exposure and dispersed catalysts. In addition, this review discusses the prospects and perspectives of practical application of electromagnetic heating to enhance heavy oil recovery in the presence of nanoparticles.
Centrifugal Filter-Assisted Block Freeze Crystallization Applied to Blueberry Juice
Authors: Orellana-Palma Patricio , Guerra-Valle María , Zúñiga Rommy N.
Published: February 2021

The impact of centrifugal-filter assisted block freeze crystallization (CFBFC) on the physicochemical parameters, total phenolic content (TPC), total anthocyanin content (TAC), and total flavonoid content (TFC), antioxidant activity (AA) and process parameters applied to blueberry juice was studied. Additionally, CFBFC was contrasted with gravitational BFC (GBFC) and centrifugal BFC (CBFC) techniques. For CFBFC process, the solutes values were ≈35.9 °Brix (fresh juice ≈13.8 °Brix), with a very dark red/purple color. Moreover, the bioactive components values presented a significant increase of 2.1, 2.0, 1.8, and 3.1 times compared to the initial TPC, TAC, TFC, and AA values, respectively, and these values were higher than GBFC and CBFC techniques. For efficiency, percentage of concentrate, and solute yield, CFBFC showed values close to 86%, 81%, and 0.9 (kg/kg), respectively, which were higher values than GBFC (48%, 38%, and 0.5 (kg/kg)) and CBFC (79%, 68%, and 0.7 (kg/kg)). Therefore, this research offers new benefits with the addition of the filter in the centrifugal BFC, and thus, CFBFC offers an advantage due to the better separation than GBFC and CBFC, since the filter can be designated as a second separation stage, and only one cycle is necessary to obtain high quality properties in the final solution.
Regenerative Potential of Enamel Matrix Protein Derivative and Acellular Dermal Matrix for Gingival Recession: A Systematic Review and Meta-Analysis
Authors: Shaikh Muhammad Saad , Lone Mohid Abrar , Matabdin Hesham , Lone Muneeb Ahmed , Soomro Azeem Hussain , Zafar Muhammad Sohail
Published: February 2021

Objective: The purpose of this study was to assess the clinical effectiveness of using a combination of enamel matrix protein derivative and acellular dermal matrix in comparison to acellular dermal matrix alone for treating gingival recessions. Methods: The Cochrane Library (Wiley), PubMed by Medline (NLM), Medline (EBSCO), and Embase (Ovid) databases were searched for entries up to April 2020. Only clinical trials were included. Primary outcomes were root coverage (%), changes in keratinized tissue width and recession (mm). Meta-analysis was conducted for root coverage, changes in keratinized tissue width, recession, clinical attachment level and probing depth. Results: Four studies were selected for the analysis. In primary outcomes, root coverage, change in keratinized tissue width and recession analysis showed a mean difference of 4.99% (p = 0.11), 0.20 mm (p = 0.14) and 0.13 mm (p = 0.23) respectively between the two groups. Secondary outcomes analysis also exhibited a statistically insignificant difference between the test and control group with mean difference of 0.11 mm (p = 0.32) in clinical attachment level gain and -0.03 mm (p = 0.29) in probing depth reduction analysis. Conclusions: Within the limits of this study, enamel matrix protein derivative combined with acellular dermal matrix used for treating gingival recession defects resulted in no beneficial effect clinically than acellular dermal matrix only.
“There’s No Discrimination, These Are Just the Rules of the Game”: Russian Scholars’ Perception of the Research Writing and Publication Process in English
Authors: Shchemeleva Irina
Published: February 2021

This paper reports on the study of multilingual speakers’ perception of their research writing practices in English and in their local language—Russian—and the publication process in English. It is based on interviews with 18 scholars from social sciences and humanities working in a leading university in Russia. The study discusses social factors influencing multilingual scholars’ choice of languages as well as their personal motivation to choose English as the main language of publication. Special attention is given to their attitude to proofreading as part of the publication process. The interview results suggest that, from the participants’ perspective, the benefits they gain by publishing research in English seem to outweigh costs they experience in the process of writing and publishing. The study contributes to the on-going debate about the position of multilingual scholars in the competition to publish in top-rated journals, suggesting that the traditional doctrine of linguistic injustice, from the participants’ point-of-view, does not seem to be relevant for every multilingual scholar.
The Importance of Rumors in the Spanish Sports Press: An Analysis of News about Signings Appearing in the Newspapers Marca, As, Mundo Deportivo and Sport
Authors: Herrero-Gutiérrez Francisco-Javier , Urchaga-Litago José-David
Published: February 2021

The front pages of newspapers are the main showcase to sell the product. Those first pages are a perfect hook for newspapers to attract readers; thus, it becomes vital to show striking pieces of information, captivating the audience. In the case of the written sport press in Spain, there is a key period in which true information is mingled with half-truths and even rumors: The summer transfer window. This paper shows an analysis of the front-page news appearing in the Spanish sports newspapers Marca, As, Mundo Deportivo, and Sport, over a five-year period (2015–2019), based on a sample of 120 different issues of the newspaper. Many times, the media present information either as something true or as a hypothesis or possibility. After quantitatively analyzing that, it can be noticed that in more than 50% of the cases, the signing or sale of the player referenced on the front page (the main news) does not occur. Similarly, it can be observed that there is a direct link connecting the news referring to Real Madrid with Marca and As, and Fútbol Club Barcelona with Mundo Deportivo and Sport. Finally, almost 100% of this news is showed along with real photographs, using photo montage in just a few cases.
Airborne Laser Scanning Point Cloud Classification Using the DGCNN Deep Learning Method
Authors: Widyaningrum Elyta , Bai Qian , Fajari Marda K. , Lindenbergh Roderik C.
Published: February 2021

Classification of aerial point clouds with high accuracy is significant for many geographical applications, but not trivial as the data are massive and unstructured. In recent years, deep learning for 3D point cloud classification has been actively developed and applied, but notably for indoor scenes. In this study, we implement the point-wise deep learning method Dynamic Graph Convolutional Neural Network (DGCNN) and extend its classification application from indoor scenes to airborne point clouds. This study proposes an approach to provide cheap training samples for point-wise deep learning using an existing 2D base map. Furthermore, essential features and spatial contexts to effectively classify airborne point clouds colored by an orthophoto are also investigated, in particularly to deal with class imbalance and relief displacement in urban areas. Two airborne point cloud datasets of different areas are used: Area-1 (city of Surabaya—Indonesia) and Area-2 (cities of Utrecht and Delft—the Netherlands). Area-1 is used to investigate different input feature combinations and loss functions. The point-wise classification for four classes achieves a remarkable result with 91.8% overall accuracy when using the full combination of spectral color and LiDAR features. For Area-2, different block size settings (30, 50, and 70 m) are investigated. It is found that using an appropriate block size of, in this case, 50 m helps to improve the classification until 93% overall accuracy but does not necessarily ensure better classification results for each class. Based on the experiments on both areas, we conclude that using DGCNN with proper settings is able to provide results close to production.
New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping
Authors: Lin Yi-Chun , Zhou Tian , Wang Taojun , Crawford Melba , Habib Ayman
Published: February 2021

Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyping activities (e.g., canopy cover estimation, plant localization, and flowering date identification). Among potential products, orthophotos play an important role in agricultural management. Traditional orthophoto generation strategies suffer from several artifacts (e.g., double mapping, excessive pixilation, and seamline distortions). The above problems are more pronounced when dealing with mid- to late-season imagery, which is often used for establishing flowering date (e.g., tassel and panicle detection for maize and sorghum crops, respectively). In response to these challenges, this paper introduces new strategies for generating orthophotos that are conducive to the straightforward detection of tassels and panicles. The orthophoto generation strategies are valid for both frame and push-broom imaging systems. The target function of these strategies is striking a balance between the improved visual appearance of tassels/panicles and their geolocation accuracy. The new strategies are based on generating a smooth digital surface model (DSM) that maintains the geolocation quality along the plant rows while reducing double mapping and pixilation artifacts. Moreover, seamline control strategies are applied to avoid having seamline distortions at locations where the tassels and panicles are expected. The quality of generated orthophotos is evaluated through visual inspection as well as quantitative assessment of the degree of similarity between the generated orthophotos and original images. Several experimental results from both UAV and ground platforms show that the proposed strategies do improve the visual quality of derived orthophotos while maintaining the geolocation accuracy at tassel/panicle locations.
An Optimized Framework for Energy-Resource Allocation in a Cloud Environment based on the Whale Optimization Algorithm
Authors: Goyal Shanky , Bhushan Shashi , Kumar Yogesh , Rana Abu ul Hassan S. , Bhutta Muhammad Raheel , Ijaz Muhammad Fazal , Son Youngdoo
Published: February 2021

Cloud computing offers the services to access, manipulate and configure data online over the web. The cloud term refers to an internet network which is remotely available and accessible at anytime from anywhere. Cloud computing is undoubtedly an innovation as the investment in the real and physical infrastructure is much greater than the cloud technology investment. The present work addresses the issue of power consumption done by cloud infrastructure. As there is a need for algorithms and techniques that can reduce energy consumption and schedule resource for the effectiveness of servers. Load balancing is also a significant part of cloud technology that enables the balanced distribution of load among multiple servers to fulfill users’ growing demand. The present work used various optimization algorithms such as particle swarm optimization (PSO), cat swarm optimization (CSO), BAT, cuckoo search algorithm (CSA) optimization algorithm and the whale optimization algorithm (WOA) for balancing the load, energy efficiency, and better resource scheduling to make an efficient cloud environment. In the case of seven servers and eight server’s settings, the results revealed that whale optimization algorithm outperformed other algorithms in terms of response time, energy consumption, execution time and throughput.
Surface Plasmon Enhanced Fluorescence Temperature Mapping of Aluminum Nanoparticle Heated by Laser
Authors: Zakiyyan Naadaa , Darr Charles M. , Chen Biyan , Mathai Cherian , Gangopadhyay Keshab , McFarland Jacob , Gangopadhyay Shubhra , Maschmann Matthew R.
Published: February 2021

Partially aggregated Rhodamine 6G (R6G) dye is used as a lights-on temperature sensor to analyze the spatiotemporal heating of aluminum nanoparticles (Al NPs) embedded within a tetrafluoroethylene, hexafluoropropylene, and vinylidene fluoride (THV) fluoropolymer matrix. The embedded Al NPs were photothermally heated using an IR laser, and the fluorescent intensity of the embedded dye was monitored in real time using an optical microscope. A plasmonic grating substrate enhanced the florescence intensity of the dye while increasing the optical resolution and heating rate of Al NPs. The fluorescence intensity was converted to temperature maps via controlled calibration. The experimental temperature profiles were used to determine the Al NP heat generation rate. Partially aggregated R6G dyes, combined with the optical benefits of a plasmonic grating, offered robust temperature sensing with sub-micron spatial resolution and temperature resolution on the order of 0.2 °C.
Real-Time Emotion Classification Using EEG Data Stream in E-Learning Contexts
Authors: Nandi Arijit , Xhafa Fatos , Subirats Laia , Fort Santi
Published: February 2021

In face-to-face and online learning, emotions and emotional intelligence have an influence and play an essential role. Learners’ emotions are crucial for e-learning system because they promote or restrain the learning. Many researchers have investigated the impacts of emotions in enhancing and maximizing e-learning outcomes. Several machine learning and deep learning approaches have also been proposed to achieve this goal. All such approaches are suitable for an offline mode, where the data for emotion classification are stored and can be accessed infinitely. However, these offline mode approaches are inappropriate for real-time emotion classification when the data are coming in a continuous stream and data can be seen to the model at once only. We also need real-time responses according to the emotional state. For this, we propose a real-time emotion classification system (RECS)-based Logistic Regression (LR) trained in an online fashion using the Stochastic Gradient Descent (SGD) algorithm. The proposed RECS is capable of classifying emotions in real-time by training the model in an online fashion using an EEG signal stream. To validate the performance of RECS, we have used the DEAP data set, which is the most widely used benchmark data set for emotion classification. The results show that the proposed approach can effectively classify emotions in real-time from the EEG data stream, which achieved a better accuracy and F1-score than other offline and online approaches. The developed real-time emotion classification system is analyzed in an e-learning context scenario.
A Robust Steered Response Power Localization Method for Wireless Acoustic Sensor Networks in an Outdoor Environment
Authors: Huang Yiwei , Tong Jianfei , Hu Xiaoqing , Bao Ming
Published: February 2021

The localization of outdoor acoustic sources has attracted attention in wireless sensor networks. In this paper, the steered response power (SRP) localization of band-pass signal associated with steering time delay uncertainty and coarser spatial grids is considered. We propose a modified SRP-based source localization method for enhancing the localization robustness in outdoor scenarios. In particular, we derive a sufficient condition dependent on the generalized cross-correlation (GCC) waveform function for robust on-grid source localization and show that the SRP function with GCCs satisfying this condition can suppress the disturbances induced by the grid distance and the uncertain steering time delays. Then a GCC refinement procedure for band-pass GCCs is designed, which uses complex wavelet functions in multiple sub-bands to filter the GCCs and averages the envelopes of the filtered GCCs as the equivalent GCC to match the sufficient condition. Simulation results and field experiments demonstrate the excellent performance of the proposed method against the existing SRP-based methods.
Follow the Trail: Machine Learning for Fraud Detection in Fintech Applications
Authors: Stojanović Branka , Božić Josip , Hofer-Schmitz Katharina , Nahrgang Kai , Weber Andreas , Badii Atta , Sundaram Maheshkumar , Jordan Elliot , Runevic Joel
Published: February 2021

Financial technology, or Fintech, represents an emerging industry on the global market. With online transactions on the rise, the use of IT for automation of financial services is of increasing importance. Fintech enables institutions to deliver services to customers worldwide on a 24/7 basis. Its services are often easy to access and enable customers to perform transactions in real-time. In fact, advantages such as these make Fintech increasingly popular among clients. However, since Fintech transactions are made up of information, ensuring security becomes a critical issue. Vulnerabilities in such systems leave them exposed to fraudulent acts, which cause severe damage to clients and providers alike. For this reason, techniques from the area of Machine Learning (ML) are applied to identify anomalies in Fintech applications. They target suspicious activity in financial datasets and generate models in order to anticipate future frauds. We contribute to this important issue and provide an evaluation on anomaly detection methods for this matter. Experiments were conducted on several fraudulent datasets from real-world and synthetic databases, respectively. The obtained results confirm that ML methods contribute to fraud detection with varying success. Therefore, we discuss the effectiveness of the individual methods with regard to the detection rate. In addition, we provide an analysis on the influence of selected features on their performance. Finally, we discuss the impact of the observed results for the security of Fintech applications in the future.
An Outline of Multi-Sensor Fusion Methods for Mobile Agents Indoor Navigation
Authors: Qu Yuanhao , Yang Minghao , Zhang Jiaqing , Xie Wu , Qiang Baohua , Chen Jinlong
Published: February 2021

Indoor autonomous navigation refers to the perception and exploration abilities of mobile agents in unknown indoor environments with the help of various sensors. It is the basic and one of the most important functions of mobile agents. In spite of the high performance of the single-sensor navigation method, multi-sensor fusion methods still potentially improve the perception and navigation abilities of mobile agents. This work summarizes the multi-sensor fusion methods for mobile agents’ navigation by: (1) analyzing and comparing the advantages and disadvantages of a single sensor in the task of navigation; (2) introducing the mainstream technologies of multi-sensor fusion methods, including various combinations of sensors and several widely recognized multi-modal sensor datasets. Finally, we discuss the possible technique trends of multi-sensor fusion methods, especially its technique challenges in practical navigation environments.
2.4 GHz GaN HEMT Class-F Synchronous Rectifier Using an Independent Second Harmonic Tuning Circuit
Authors: Na Jongyun , Yi Sang-Hwa , Shin Jaekyung , Koo Hyungmo , Bae Jongseok , Hwang Keum-Cheol , Lee Kang-Yoon , Yang Youngoo
Published: February 2021

This paper proposes a class-F synchronous rectifier using an independent second harmonic tuning circuit for the power receiver of 2.4 GHz wireless power transmission systems. The synchronous rectifier can be designed by inverting the RF output port to the RF input port of the pre-designed class-F power amplifier based on time reversal duality. The design of the class-F power amplifier deploys an independent second harmonic tuning circuit in the matching networks to individually optimize the impedances of the fundamental and the second harmonic. The synchronous rectifier at the 2.4 GHz frequency is designed and implemented using a 6 W gallium nitride high electron mobility transistor (GaN HEMT). Peak RF-dc conversion efficiency of the rectifier of 69.6% is achieved with a dc output power of about 7.8 W, while the peak drain efficiency of the class-F power amplifier is 72.8%.
Potentiometric Response of Solid-State Sensors Based on Ferric Phosphate for Iron(III) Determination
Authors: Paut Andrea , Prkić Ante , Mitar Ivana , Bošković Perica , Jozić Dražan , Jakić Miće , Vukušić Tina
Published: February 2021

A novel ion-selective electrode with membranes based on iron(III) phosphate and silver sulfide integrated into a completely new electrode body design has been developed for the determination of iron(III) cations. The best response characteristics with linear potential change were found in the iron(III) concentration range from 3.97 × 10−5 to 10−2 mol L−1. The detection limit was found to be 2.41 × 10−5 mol L−1 with a slope of −20.53 ± 0.63 and regression coefficient of 0.9925, while the quantification limit was 3.97 × 10−5 M. The potential change per concentration decade ranged from −13.59 ± 0.54 to −20.53 ± 1.56 for Electrode Body 1 (EB1) and from −17.28 ± 1.04 to −24 ± 1.87 for Electrode Body 2 (EB2), which is presented for the first time in this work. The prepared electrode has a long lifetime and the ability to detect changes in the concentration of iron cations within 20 s. Membrane M1 showed high recoveries in the determination of iron cations in iron(III) standard solutions (98.2–101.2%) as well as in two different pharmaceuticals (98.6–106.5%). This proves that this type of sensor is applicable in the determination of ferric cations in unknown samples, and the fact that all sensor parts are completely manufactured in our laboratory proves the simplicity of the method.
The MindGomoku: An Online P300 BCI Game Based on Bayesian Deep Learning
Authors: Li Man , Li Feng , Pan Jiahui , Zhang Dengyong , Zhao Suna , Li Jingcong , Wang Fei
Published: February 2021

In addition to helping develop products that aid the disabled, brain–computer interface (BCI) technology can also become a modality of entertainment for all people. However, most BCI games cannot be widely promoted due to the poor control performance or because they easily cause fatigue. In this paper, we propose a P300 brain–computer-interface game (MindGomoku) to explore a feasible and natural way to play games by using electroencephalogram (EEG) signals in a practical environment. The novelty of this research is reflected in integrating the characteristics of game rules and the BCI system when designing BCI games and paradigms. Moreover, a simplified Bayesian convolutional neural network (SBCNN) algorithm is introduced to achieve high accuracy on limited training samples. To prove the reliability of the proposed algorithm and system control, 10 subjects were selected to participate in two online control experiments. The experimental results showed that all subjects successfully completed the game control with an average accuracy of 90.7% and played the MindGomoku an average of more than 11 min. These findings fully demonstrate the stability and effectiveness of the proposed system. This BCI system not only provides a form of entertainment for users, particularly the disabled, but also provides more possibilities for games.
The Interface between Nanoenergy and Self-Powered Electronics
Authors: Wang Yi-Lin , Deng Hai-Tao , Ren Zhen-Yu , Liu Xin-Tian , Chen Yu , Tu Cheng , Chen Jun-Lian , Zhang Xiao-Sheng
Published: February 2021

In recent decades, nanogenerators based on several techniques such as triboelectric effects, piezoelectric effects, or other mechanisms have experienced great developments. The nanoenergy generated by nanogenerators is supposed to be used to overcome the problem of energy supply problems for portable electronics and to be applied to self-powered microsystems including sensors, actuators, integrated circuits, power sources, and so on. Researchers made many attempts to achieve a good solution and have performed many explorations. Massive efforts have been devoted to developing self-powered electronics, such as self-powered communication devices, self-powered human–machine interfaces, and self-powered sensors. To take full advantage of nanoenergy, we need to review the existing applications, look for similarities and differences, and then explore the ways of achieving various self-powered systems with better performance. In this review, the methods of applying nanogenerators in specific circumstances are studied. The applications of nanogenerators are classified into two categories, direct utilization and indirect utilization, according to whether a treatment process is needed. We expect to offer a line of thought for future research on self-powered electronics.
A Dynamic Motion Analysis of a Six-Wheel Ground Vehicle for Emergency Intervention Actions
Authors: Grigore Lucian Ștefăniță , Gorgoteanu Damian , Molder Cristian , Alexa Octavian , Oncioiu Ionica , Ștefan Amado , Constantin Daniel , Lupoae Marin , Bălașa Răzvan-Ionuț
Published: February 2021

To protect the personnel of the intervention units operating in high-risk areas, it is necessary to introduce (autonomous/semi-autonomous) robotic intervention systems. Previous studies have shown that robotic intervention systems should be as versatile as possible. Here, we focused on the idea of a robotic system composed of two vectors: a carrier vector and an operational vector. The proposed system particularly relates to the carrier vector. A simple analytical model was developed to enable the entire robotic assembly to be autonomous. To validate the analytical-numerical model regarding the kinematics and dynamics of the carrier vector, two of the following applications are presented: intervention for extinguishing a fire and performing measurements for monitoring gamma radiation in a public enclosure. The results show that the chosen carrier vector solution, i.e., the ground vehicle with six-wheel drive, satisfies the requirements related to the mobility of the robotic intervention system. In addition, the conclusions present the elements of the kinematics and dynamics of the robot.
A Sensing Device with the Optical Temperature Sensors-Based Quad-RX Module and a Security Module
Authors: Kim Kyeeun , Park Siwoong , Yeo Chanil , Park Hyoung-Jun , Kim Hyunjin , Heo Young Soon , Kang Hyun Seo , Kim Kyungsoo
Published: February 2021

In this paper, we present a sensing device with the optical temperature sensors-based quad receiver (Quad-RX) module and a security module. In addition, in order to prevent cyberattacks on critical national infrastructures and key facilities, we implemented symmetric-key and secure hash algorithm-based hardware security modules in the key elements of the sensing device. A preliminary test was conducted prior to a field trial to verify the performance of the developed sensing device. The accuracy and stability of the sensing device were then verified for 1 month in a field test at facilities for energy storage systems and photovoltaic converters in sewage treatment plants.
Accuracy Investigation of the Pose Determination of a VR System
Authors: Bauer Peter , Lienhart Werner , Jost Samuel
Published: February 2021

The usage of VR gear in mixed reality applications demands a high position and orientation accuracy of all devices to achieve a satisfying user experience. This paper investigates the system behaviour of the VR system HTC Vive Pro at a testing facility that is designed for the calibration of highly accurate positioning instruments like geodetic total stations, tilt sensors, geodetic gyroscopes or industrial laser scanners. Although the experiments show a high reproducibility of the position readings within a few millimetres, the VR system has systematic effects with magnitudes of several centimetres. A tilt of about 0.4° of the reference plane with respect to the horizontal plane was detected. Moreover, our results demonstrate that the tracking algorithm faces problems when several lighthouses are used.
Smart Node Networks Orchestration: A New E2E Approach for Analysis and Design for Agile 4.0 Implementation
Authors: Bertoli Annalisa , Cervo Andrea , Rosati Carlo Alberto , Fantuzzi Cesare
Published: February 2021

The field of cyber-physical systems is a growing IT research area that addresses the deep integration of computing, communication and process control, possibly with humans in the loop. The goal of such area is to define modelling, controlling and programming methodologies for designing and managing complex mechatronics systems, also called industrial agents. Our research topic mainly focuses on the area of data mining and analysis by means of multi-agent orchestration of intelligent sensor nodes using internet protocols, providing also web-based HMI visualizations for data interpretability and analysis. Thanks to the rapid spreading of IoT systems, supported by modern and efficient telecommunication infrastructures and new decentralized control paradigms, the field of service-oriented programming finds new application in wireless sensor networks and microservices paradigm: we adopted such paradigm in the implementation of two different industrial use cases. Indeed, we expect a concrete and deep use of such technologies with 5G spreading. In the article, we describe the common software architectural pattern in IoT applications we used for the distributed smart sensors, providing also design and implementation details. In the use case section, the prototypes developed as proof of concept and the KPIs used for the system validation are described to provide a concrete solution overview.
Nano-Scale Stiffness and Collagen Fibril Deterioration: Probing the Cornea Following Enzymatic Degradation Using Peakforce-QNM AFM
Authors: Kazaili Ahmed , Abdul-Amir Al-Hindy Hayder , Madine Jillian , Akhtar Riaz
Published: February 2021

Under physiological conditions, the cornea is exposed to various enzymes, some of them have digestive actions, such as amylase and collagenase that may change the ultrastructure (collagen morphology) and sequentially change the mechanical response of the cornea and distort vision, such as in keratoconus. This study investigates the ultrastructure and nanomechanical properties of porcine cornea following incubation with α-amylase and collagenase. Atomic force microscopy (AFM) was used to capture nanoscale topographical details of stromal collagen fibrils (diameter and D-periodicity) and calculate their elastic modulus. Samples were incubated with varying concentrations of α-amylase and collagenase (crude and purified). Dimethylmethylene blue (DMMB) assay was utilised to detect depleted glycosaminoglycans (GAGs) following incubation with amylase. Collagen fibril diameters were decreased following incubation with amylase, but not D-periodicity. Elastic modulus was gradually decreased with enzyme concentration in amylase-treated samples. Elastic modulus, diameter, and D-periodicity were greatly reduced in collagenase-treated samples. The effect of crude collagenase on corneal samples was more pronounced than purified collagenase. Amylase was found to deplete GAGs from the samples. This enzymatic treatment may help in answering some questions related to keratoconus, and possibly be used to build an empirical animal model of keratoconic corneas with different progression levels.
Phthalocyanine-Functionalized Magnetic Silica Nanoparticles as Anion Chemosensors
Authors: Rodrigues João M. M. , Farinha Andreia S. F. , Lin Zhi , Cavaleiro José A. S. , Tome Augusto C. , Tome Joao P. C.
Published: February 2021

Anionic species are one of the most common pollutants in residual and freshwaters. The presence of anthropogenic anions in water drastically increases the toxicity to living beings. Here, we report the preparation of a new optical active material based on tri(tosylamino)phthalocyanines grafted to ferromagnetic silica nanoparticles for anion detection and removal. The new unsymmetrical phthalocyanines (Pcs) proved to be excellent chemosensors for several anions (AcO−, Br−, Cl−, CN−, F−, H2PO4−, HSO4−, NO2−, NO3−, and OH−) in dimethyl sulfoxide (DMSO). Furthermore, the Pcs were grafted onto magnetic nanoparticles. The resulting novel hybrid material showed selectivity and sensitivity towards CN−, F−, and OH− anions in DMSO with limit of detection (LoD) of ≈4.0 µM. In water, the new hybrid chemosensor demonstrated selectivity and sensitivity for CN− and OH− anions with LoD of ≈0.2 µM. The new hybrids are easily recovered using a magnet, allowing recyclability and reusability, after acidic treatment, without losing the sensing proprieties.
Chemical Sensors for Farm-to-Table Monitoring of Fruit Quality
Authors: Wilson Denise
Published: February 2021

Farm-to-table operations produce, transport, and deliver produce to consumers in very different ways than conventional, corporate-scale agriculture operations. As a result, the time it takes to get a freshly picked fruit to the consumer is relatively short and the expectations of the consumer for freshness and quality are high. Since many of these operations involve small farms and small businesses, resources to deploy sensors and instruments for monitoring quality are scarce compared to larger operations. Within stringent power, cost, and size constraints, this article analyzes chemical sensor technologies suitable for monitoring fruit quality from the point of harvest to consumption in farm-to-table operations. Approaches to measuring sweetness (sugar content), acidity (pH), and ethylene gas are emphasized. Not surprisingly, many instruments developed for laboratory use or larger-scale operations are not suitable for farm-to-table operations. However, there are many opportunities still available to adapt pH, sugar, and ethylene sensing to the unique needs of localized farm-to-table operations that can help these operations survive and expand well into the future.
Breathable Textile Rectangular Ring Microstrip Patch Antenna at 2.45 GHz for Wearable Applications
Authors: Memon Abdul Wahab , de Paula Igor Lima , Malengier Benny , Vasile Simona , Van Torre Patrick , Van Langenhove Lieva
Published: February 2021

A textile patch antenna is an attractive package for wearable applications as it offers flexibility, less weight, easy integration into the garment and better comfort to the wearer. When it comes to wearability, above all, comfort comes ahead of the rest of the properties. The air permeability and the water vapor permeability of textiles are linked to the thermophysiological comfort of the wearer as they help to improve the breathability of textiles. This paper includes the construction of a breathable textile rectangular ring microstrip patch antenna with improved water vapor permeability. A selection of high air permeable conductive fabrics and 3-dimensional knitted spacer dielectric substrates was made to ensure better water vapor permeability of the breathable textile rectangular ring microstrip patch antenna. To further improve the water vapor permeability of the breathable textile rectangular ring microstrip patch antenna, a novel approach of inserting a large number of small-sized holes of 1 mm diameter in the conductive layers (the patch and the ground plane) of the antenna was adopted. Besides this, the insertion of a large number of small-sized holes improved the flexibility of the rectangular ring microstrip patch antenna. The result was a breathable perforated (with small-sized holes) textile rectangular ring microstrip patch antenna with the water vapor permeability as high as 5296.70 g/m2 per day, an air permeability as high as 510 mm/s, and with radiation gains being 4.2 dBi and 5.4 dBi in the E-plane and H-plane, respectively. The antenna was designed to resonate for the Industrial, Scientific and Medical band at a specific 2.45 GHz frequency.
Adaptive Complex Variational Mode Decomposition for Micro-Motion Signal Processing Applications
Authors: Xia Saiqiang , Yang Jun , Cai Wanyong , Zhang Chaowei , Hua Liangfa , Zhou Zibo
Published: February 2021

In order to suppress the strong clutter component and separate the effective fretting component from narrow-band radar echo, a method based on complex variational mode decomposition (CVMD) is proposed in this paper. The CVMD is extended from variational mode decomposition (VMD), which is a recently introduced technique for adaptive signal decomposition, limited to only dealing with the real signal. Thus, the VMD is extended from the real domain to the complex domain firstly. Then, the optimal effective order of singular value is obtained by singular value decomposition (SVD) to solve the problem of under-decomposition or over-decomposition caused by unreasonable choice of decomposition layer, it is more accurate than detrended fluctuation analysis (DFA) and empirical mode decomposition (EMD). Finally, the strongly correlated modes and weakly correlated modes are judged by calculating the Mahalanobis distance between the band-limited intrinsic mode functions (BLIMFs) and the original signal, which is more robust than the correlation judgment methods such as computing cross-correlation, Euclidean distance, Bhattachryya distance and Hausdorff distance. After the weak correlation modes are eliminated, the signal is reconstructed locally, and the separation of the micro-motion signal is realized. The experimental results show that the proposed method can filter out the strong clutter component and the fuselage component from radar echo more effectively than the local mean decomposition (LMD), empirical mode decomposition and moving target indicator (MTI) filter.
Fully Flexible Textile Antenna-Backed Sensor Node for Body-Worn UWB Localization
Authors: Van Baelen Dries , Macoir Nicola , Van den Brande Quinten , De Poorter Eli , Lemey Sam , Verhaevert Jo , Rogier Hendrik
Published: February 2021

A mechanically flexible textile antenna-backed sensor node is designed and manufactured, providing accurate personal localization functionality by application of Decawave’s DW1000 Impulse Radio Ultra-Wideband (IR-UWB) Integrated Circuit (IC). All components are mounted on a flexible polyimide foil, which is integrated on the backplane of a wearable cavity-backed slot antenna designed for IR-UWB localization in Channels 2 and 3 of the IEEE 802.15.4-2011 standard (3744 MHz–4742.4 MHz). The textile antenna’s radiation pattern is optimized to mitigate body effects and to minimize absorption by body tissues. Furthermore, its time-domain characteristics are measured to be adequate for localization. By combining the antenna and the bendable Printed Circuit Board (PCB), a mechanically supple sensor system is realized, for which the performance is validated by examining it as a node used in a complete localization system. This shows that six nodes around the body must be deployed to provide system coverage in all directions around the wearer. Even without using sleep mode functionalities, the measurements indicate that the system’s autonomy is 13.3 h on a 5 V 200 mAh battery. Hence, this system acts as a proof of concept for the joining of localization electronics and other sensors with a full-textile antenna into a mechanically flexible sensor system.
Student Perception of the Social Value of Responsible Management
Authors: Mazilescu Crisanta-Alina , Auzoult-Chagnault Laurent , Viscu Loredana Ileana , Gangloff Bernard
Published: February 2021

In responsible management, managerial efficiency and sustainable development meet and influence each other. In order to give meaning to their organisation, to respect and look after their collaborators, a manager must promote a set of values on a personal, organisational and societal level. The purpose of this paper is to study the social value attributed to responsible management by students of a technical university. We have therefore undertaken to study a set of seven values attributed to responsible management and, more precisely, their utility and social desirability on a personal, organisational and societal level. The values have been operationalized with personality descriptors. The 60 participants in this study are students from a Romanian technical university. They had to assess, on four scales of seven points each (two for desirability and two for social utility), the value of a person characterised by one of the seven values attributed to responsible management. The results show us that efficiency is the value perceived by the students as being the most desirable for responsible management, and that in terms of social utility, agility is the most appreciated value. We found that there is indeed an effect of the context in which these values are perceived. Efficiency, audacity, dedication and integrity are perceived as more useful at an organisational level, while solidarity was perceived as more useful on a societal level. At the organisational level we also found a gender effect, in the sense that women appreciate people who are efficient, have integrity or are humble more than men do.
Fruit Quality and Antioxidant Activities of Yellow-Skinned Apple Cultivars Coated with Natural Sucrose Monoesters
Authors: Jung Seok-Kyu , Choi Hyun-Sug
Published: February 2021

Yellow-skinned ‘Tsugaru’, ‘Summer King’, and ‘Shinano Gold’ apples (Malus × domestica Borkh.) were coated with a mixture of edible sucrose monoesters of fatty acid and ethanol that had never been applied in those apple fruits, for up to 28 days after room temperature storage (DAS) to evaluate their morphological characteristics, fruit qualities, and antioxidant concentrations. The coating treatment significantly reduced respiration rates of ‘Tsugaru’ and ‘Summer King’ apples at both 14 and 28 DAS, and ‘Shinano Gold’ at 28 DAS. The coated ‘Tsugaru’ and ‘Summer King’ apples were found in greater coverage with fragments of the sucrose esters than those of ‘Shinano Gold’, exhibiting greater skin greasiness and thickness. The coated ‘Tsugaru’ and ‘Summer King’ apples mostly maintained high fruit firmness, peel color, vitamin C, total polyphenol concentrations, and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity. The recent developed coating material contributed to improving shelf-life of the ‘Tsugaru’ and ‘Summer King’ apples and fruit defense systems as a novel post-harvest technology for sustainable food security.
Is Active Lifestyle Related to Autonomic Nervous System Function and Lipid Profile in People with Overweight? A Study Pilot
Authors: Espinoza-Salinas Alexis , Molina-Sotomayor Edgardo , Cano-Montoya Johnattan , Gonzalez-Jurado Jose Antonio
Published: February 2021

Autonomic nervous system function is an important predictor of physical fitness. The objective of this study was to find out the associations of autonomic activity parameters, lipid profile, insulin concentrations, and insulin resistance in overweight men with the level of physical activity. A descriptive and correlational study was carried out in 28 overweight men: 14 physically active (PA) and 14 physically inactive (PI). The following variables were assessed: Level of physical activity, HRV (heart rate variability), basal insulin, HOMA-IR index (Homeostasis Model Assessment Insulin-Resistance), and lipid profile. The main results show a positive correlation between the spectral parameters of the HRV and total cholesterol (r = 0.24), LDL (r = 0.59), VLDL (r = 0.86), and insulin (r = 0.88) of sedentary people, evidencing a directly proportional correlation with BMI. We conclude that weight gain and a sedentary lifestyle are associated with an increase in sympathetic discharge, which, in turn, is associated with an increase in lipid profile and insulin levels.
Biophilia beyond the Building: Applying the Tools of Urban Biodiversity Planning to Create Biophilic Cities
Authors: Panlasigui Stephanie , Spotswood Erica , Beller Erin , Grossinger Robin
Published: February 2021

In response to the widely recognized negative impacts of urbanization on biodiversity, many cities are reimagining urban design to provide better biodiversity support. Some cities have developed urban biodiversity plans, primarily focused on improving biodiversity support and ecosystem function within the built environment through habitat restoration and other types of urban greening projects. The biophilic cities movement seeks to reframe nature as essential infrastructure for cities, seamlessly integrating city and nature to provide abundant, accessible nature for all residents and corresponding health and well-being outcomes. Urban biodiversity planning and biophilic cities have significant synergies in their goals and the means necessary to achieve them. In this paper, we identify three key ways by which the urban biodiversity planning process can support biophilic cities objectives: engaging the local community; identifying science-based, quantitative goals; and setting priorities for action. Urban biodiversity planning provides evidence-based guidance, tools, and techniques needed to design locally appropriate, pragmatic habitat enhancements that support biodiversity, ecological health, and human health and well-being. Developing these multi-functional, multi-benefit strategies that increase the abundance of biodiverse nature in cities has the potential at the same time to deepen and enrich our biophilic experience in daily life.
Community Participation and Residents’ Support for Tourism Development in Ancient Villages: The Mediating Role of Perceptions of Conflicts in the Tourism Community
Authors: Wang Mingsen , Jiang Jinbo , Xu Songjun , Guo Yi
Published: February 2021

As increasing numbers of tourists have begun to visit ancient villages, conflicts between tourism development and residents have become one of the main challenges to the sustainable development of the tourism community. This research explores the relationship between community participation and residents’ support for tourism development in an ancient village. This study surveyed 249 indigenous residents living in Whampoa Village, Guangzhou, China. The findings show that community participation in tourism development has a positive influence on residents’ support for tourism development, and this relationship is mediated by the perceptions of conflicts in the tourism community. This study contributes a new theoretical perspective and practical implications for the sustainable development of ancient villages.