bluuebunny/crossref_metadata_2025 huggingface dataset:
Collaborative Networks: A Pillar of Digital Transformation
Authors: Camarinha-Matos Luis M. , Fornasiero Rosanna , Ramezani Javaneh , Ferrada Filipa
Published: December 2019

The notion of digital transformation encompasses the adoption and integration of a variety of new information and communication technologies for the development of more efficient, flexible, agile, and sustainable solutions for industrial systems. Besides technology, this process also involves new organizational forms and leads to new business models. As such, this work addresses the contribution of collaborative networks to such a transformation. An analysis of the collaborative aspects required in the various dimensions of the 4th industrial revolution is conducted based on a literature survey and experiences gained from several research projects. A mapping between the identified collaboration needs and research results that can be adopted from the collaborative networks area is presented. Furthermore, several new research challenges are identified and briefly characterized.
Automatic Lip Reading System Based on a Fusion Lightweight Neural Network with Raspberry Pi
Authors: Wen Jing , Lu Yuanyao
Published: December 2019

Virtual Reality (VR) is a kind of interactive experience technology. Human vision, hearing, expression, voice and even touch can be added to the interaction between humans and machine. Lip reading recognition is a new technology in the field of human-computer interaction, which has a broad development prospect. It is particularly important in a noisy environment and within the hearing- impaired population and is obtained by means of visual information from a video to make up for the deficiency of voice information. This information is a visual language that benefits from Augmented Reality (AR). The purpose is to establish an efficient and convenient way of communication. However, the traditional lip reading recognition system has high requirements of running speed and performance of the equipment because of its long recognition process and large number of parameters, so it is difficult to meet the requirements of practical application. In this paper, the mobile end lip-reading recognition system based on Raspberry Pi is implemented for the first time, and the recognition application has reached the latest level of our research. Our mobile lip-reading recognition system can be divided into three stages: First, we extract key frames from our own independent database, and then use a multi-task cascade convolution network (MTCNN) to correct the face, so as to improve the accuracy of lip extraction. In the second stage, we use MobileNets to extract lip image features and long short-term memory (LSTM) to extract sequence information between key frames. Finally, we compare three lip reading models: (1) The fusion model of Bi-LSTM and AlexNet. (2) A fusion model with attention mechanism. (3) The LSTM and MobileNets hybrid network model proposed by us. The results show that our model has fewer parameters and lower complexity. The accuracy of the model in the test dataset is 86.5%. Therefore, our mobile lip reading system is simpler and smaller than other PC platforms and saves computing resources and memory space.
Fire Properties of Acrylonitrile Butadiene Styrene Enhanced with Organic Montmorillonite and Exolit Fire Retardant
Authors: Simionescu Tudor Mihai , Minea Alina Adriana , Reis Paulo Nobre Balbis dos
Published: December 2019

In this paper an experimental investigation on fire retardancy of a new polymer nanocomposite derived from organic montmorillonite and exolit fire retardant in an acrylonitrile- butadiene-styrene copolymer by analyzing the flammability and fire behavior is described. The samples were prepared by melting and mixing nanocomposites and fire retardant in different concentrations in an acrylonitrile-butadiene-styrene base polymer. It was found that using only one component (organic montmorillonite or fire retardant) the burning stops in 10 s on the sample. Confirmation of synergy in flammability by combining both montmorillonite and flame retardants was noticed and is discussed regarding the flame-retardant mechanisms assessed by means of the Limiting oxygen index (LOI), UL 94, and cone-calorimeter methods. The acrylonitrile- butadiene-styrene preparation with 15–20 wt% fire retardant and 1–2 wt% organic montmorillonite reached a UL-94 V-0 classification, contrasting with the pure acrylonitrile- butadiene-styrene and the acrylonitrile-butadiene-styrene with 15 wt% fire retardant and acrylonitrile-butadiene-styrene with 1–2 wt% organic montmorillonite formulations, which completely burned. Finally, the samples showed a very good synergy going to a higher reduction of the peak heat release rate and to a minimum mass reduction, as obtained from cone calorimeter tests.
Energy Market Management for Distribution Network with a Multi-Microgrid System: A Dynamic Game Approach
Authors: Tong Xin , Hu Cungang , Zheng Changbao , Rui Tao , Wang Bo , Shen Weixiang
Published: December 2019

This paper proposes an energy market management framework to address the day-ahead optimization of a distribution network (DN) with a multi-microgrid (MMG). In this framework, an economic optimization based on a dynamic game is designed to ensure the reliability and stability of the DN operation while setting the internal transaction price to minimize the operation cost of the distribution network operator (DNO). The DNO, as a leader, sets the power flow constraints and microgrid operators (MGOs), as followers, respond to the internal transaction price and in turn affect the DNO’s price decision. The price incentive mechanism of the DNO is to encourage MGs to participate in energy market management, to promote joint operation of MGs and to reduce the operation cost of MGOs. The differential evolution algorithm and mixed integer programming method are applied to find the equilibrium solution to the dynamic game. Numerical simulations of a modified IEEE 33-bus system show the effectiveness of the proposed energy market management framework.
Efficient Parallel Algorithms for 3D Laplacian Smoothing on the GPU
Authors: Xiao Lei , Yang Guoxiang , Zhao Kunyang , Mei Gang
Published: December 2019

In numerical modeling, mesh quality is one of the decisive factors that strongly affects the accuracy of calculations and the convergence of iterations. To improve mesh quality, the Laplacian mesh smoothing method, which repositions nodes to the barycenter of adjacent nodes without changing the mesh topology, has been widely used. However, smoothing a large-scale three dimensional mesh is quite computationally expensive, and few studies have focused on accelerating the Laplacian mesh smoothing method by utilizing the graphics processing unit (GPU). This paper presents a GPU-accelerated parallel algorithm for Laplacian smoothing in three dimensions by considering the influence of different data layouts and iteration forms. To evaluate the efficiency of the GPU implementation, the parallel solution is compared with the original serial solution. Experimental results show that our parallel implementation is up to 46 times faster than the serial version.
Optimized Refraction Travel Time Tomography
Authors: Liu Sixin , Jia Zhuo , Zhu Yinuo , Zhao Xueran , Cheng Siyuan
Published: December 2019

In seismic refraction exploration, travel time tomography is the most widely used method in engineering and environmental geophysical exploration. In this paper, we mainly optimize the travel time tomography of refraction. First, with respect to the forward algorithm, we introduce a new travel time calculation method to improve the accuracy and efficiency of forward calculation. Based on the fast marching method (FMM), we introduce an improved forward calculation method called the multi-stencil fast marching method (MSFM). In the process of inversion, we propose a dynamic prior model composite constraint (DPMCC) method based on the T0 difference method from the idea of multi-scale inversion. Meanwhile, we use the prior information to improve the accuracy of inversion. Furthermore, we use the dynamic regularization factor selection method to make the inversion solution more stable and reliable. Finally, we test and analyze the synthetic data and the measured data to verify the effectiveness of the optimized travel time tomography algorithm.
Urban Air Quality Analysis and Forecast Based on Intelligent Algorithm with Parameter Optimization and Decision Rules
Authors: Lee Chou-Yuan , Lee Zne-Jung , Huang Jian-Qiong , Ye Fu-Lan , Ning Zheng-Yuan , Yang Cheng-Fu
Published: December 2019

Air pollution has an ongoing devastating impact on the planet, damaging ecosystems, depleting natural resources, and endangering human health. This paper proposes a new intelligent algorithm that includes parameter optimization and decision rules to forecast and analyze of urban air quality. Through analysis of 24-h daily air quality data provided by the Beijing Air Quality Monitoring Station, simulated annealing (SA) and a decision tree (DT) emerge as the key factors. We prove that in the investigated algorithm, SA and DT can be used to make decision rules and achieve better accuracy for classification. We find that SA can be used to adjust the best parameter settings for the DT. Simulation results show that the accuracy of the proposed algorithm for classification is far better than other existing approaches.
Steel Surface Defect Diagnostics Using Deep Convolutional Neural Network and Class Activation Map
Authors: Lee Soo Young , Tama Bayu Adhi , Moon Seok Jun , Lee Seungchul
Published: December 2019

Steel defect diagnostics is considerably important for a steel-manufacturing industry as it is strongly related to the product quality and production efficiency. Product quality control suffers from a real-time diagnostic capability since it is less-automatic and is not reliable in detecting steel surface defects. In this study, we propose a relatively new approach for diagnosing steel defects using a deep structured neural network, e.g., convolutional neural network (CNN) with class activation maps. Rather than using a simple deep learning algorithm for the classification task, we extend the CNN diagnostic model for being used to analyze the localized defect regions within the images to support a real-time visual decision-making process. Based on the experimental results, the proposed approach achieves a near-perfect detection performance at 99.44% and 0.99 concerning the accuracy and F-1 score metric, respectively. The results are better than other shallow machine learning algorithms, i.e., support vector machine and logistic regression under the same validation technique.
Mobile AR: User Evaluation in a Cultural Heritage Context
Authors: Marto Anabela , Gonçalves Alexandrino
Published: December 2019

The growing number of mobile augmented reality applications has been favoring its awareness and usage among diversified areas. Focusing on cultural heritage applications, this study presents an evaluation of a mobile augmented reality application tested at Conimbriga, an archaeological site. The prototype developed for this purpose, named DinofelisAR, allowed users to view, over 360 degrees, a majestic reconstruction of a Forum from the Roman Era superimposed over its current ruins. Thus, users were able to keep perceiving the present-day surroundings of a Roman city in ruins while, at the same time, had the possibility to explore the matching virtual model. The results presented, arising from 90 participants involved in this evaluation, praise the sense of opportunity for new augmented reality solutions targeted at cultural heritage sites.
Failure Prediction for the Tearing of a Pin-Loaded Dual Phase Steel (DP980) Adjusting Guide
Authors: Hong Seokmoo , Kim Jinkyoo , Jun Taehwan
Published: December 2019

Owing to their outstanding strength, in recent years, there has been an increased use of advanced high-strength steel (AHSS) sheets in the automotive sector. Their low formability, however, poses a challenge to forming, and failure prediction requires accurate knowledge of its material behavior over a large strain range up to ultimate failure, in order to exploit their full capacity in forming, but also in crash events. For predicting the fracture of an adjusting guide loaded by a pin, first, the force–displacement data are extracted from tensile tests using DP980 specimens of diverse shapes, all of which represent a certain loading mode. Using digital image correlation (DIC), we determine the stress triaxialities corresponding to the diverse loading conditions and establish the triaxiality failure diagram (TFD), which serves as the basis for the generalized incremental stress state-dependent damage model (GISSMO). Then, the damage parameters (necking and failure strains) are determined for each loading mode by reverse engineering-based optimization. Finally, these damage parameters are applied to the adjusting guide, and the numerical results are compared with the experimental data. Comparisons of the external load–displacement curves and the local equivalent strain distributions show that using the damage model with the material parameters obtained in here allows for the accurate prediction of the guide’s failure behavior, and the applicability of GISSMO to complex loading cases.
A General Approach Based on Newton’s Method and Cyclic Coordinate Descent Method for Solving the Inverse Kinematics
Authors: Chen Yuhan , Luo Xiao , Han Baoling , Jia Yan , Liang Guanhao , Wang Xinda
Published: December 2019

The inverse kinematics of robot manipulators is a crucial problem with respect to automatically controlling robots. In this work, a Newton-improved cyclic coordinate descent (NICCD) method is proposed, which is suitable for robots with revolute or prismatic joints with degrees of freedom of any arbitrary number. Firstly, the inverse kinematics problem is transformed into the objective function optimization problem, which is based on the least-squares form of the angle error and the position error expressed by the product-of-exponentials formula. Thereafter, the optimization problem is solved by combining Newton’s method with the improved cyclic coordinate descent (ICCD) method. The difference between the proposed ICCD method and the traditional cyclic coordinate descent method is that consecutive prismatic joints and consecutive parallel revolute joints are treated as a whole in the former for the purposes of optimization. The ICCD algorithm has a convenient iterative formula for these two cases. In order to illustrate the performance of the NICCD method, its simulation results are compared with the well-known Newton–Raphson method using six different robot manipulators. The results suggest that, overall, the NICCD method is effective, accurate, robust, and generalizable. Moreover, it has advantages for the inverse kinematics calculations of continuous trajectories.
Three-Dimensional Reconstruction of Thermal Volumetric Sources from Surface Temperature Fields Measured by Infrared Thermography
Authors: Groz Marie-Marthe , Abisset-Chavanne Emmanuelle , Meziane Anissa , Sommier Alain , Pradère Christophe
Published: December 2019

Non-destructive testing (NDT) of materials and structures is a very important industrial issue in the fields of transport, aeronautics and space as well as in the medical domain. Active infrared thermography is an NDT method that consists of providing an external excitation to cause an elevation of the temperature field in the material, consequently allowing evaluation of the resulting temperature field at the surface. However, thermal exciters that are used (flash lamps, halogen, lasers) act only on the surface of the sample. On the other hand, several energy conversion systems can lead to the generation of volumetric sources; the phenomena of thermo-acoustics, thermo-induction, thermomechanics or thermochemistry can be cited. For instance, ultrasonic waves can generate volumetric heat sources if the material is viscoelastic or if there is a defect. The reconstruction of these sources is the initial process for the quantification of parameters responsible for the heating. Characterizing a heat source means reconstructing its geometry and the supplied power. Identification of volumetric heat sources from surface temperature fields is a mathematically ill-posed problem. The main cause of the issue is the diffusive nature of the temperature. In this work, 3D reconstruction of the volumetric heat sources from the resulting surface temperature field, measured by infrared thermography, is studied. An analysis of the physical problem enables specifying the limits of the reconstruction. In particular, a criterion on the achievable spatial resolution is defined, and a reconstruction limitation for in-depth sources is highlighted.
A Theoretical Study of the Energetic Stability and Geometry of Silicon-Vacancy Color Centers in Diamond (001) Surfaces
Authors: Pan Yuanhui , Shen Wei , Shen Shengnan , Li Hui
Published: December 2019

Single neutral silicon-vacancy ( SiV 0 ) color centers under H-, O-, or N-terminated diamond (001) surfaces were investigated using density functional theory. The formation energy calculation indicated that it is generally easier for SiV 0 to be embedded in an O-terminated diamond (001) surface as compared with H- and N-terminated surfaces, which were effected above the fifth C layer. The effects of the surface termination species on inner diamond atoms decay to be negligible below the fifth C layer. The binding energy results indicated that SiV centers exhibited rather high energetic stability once formed. Additionally, it was revealed that these three surface-terminating species had contracting or expanding effects on inner surface atoms. The calculation for density of states showed that the N-terminated diamond (001) surface served as a suitable medium for single SiV 0 to function as a single-photon source.
Probing the Antitumor Mechanism of Solanum nigrum L. Aqueous Extract against Human Breast Cancer MCF7 Cells
Authors: Ling Binbing , Xiao Shujun , Yang Jinha , Wei Ying , Sakharkar Meena K. , Yang Jian
Published: December 2019

Solanum nigrum L. is one of the major medicinal plants used to treat cancer. However, the functional mechanism of S. nigrum L. extract is still unknown in spite of numerous studies on its active components. In this study, we probed the potential anticancer mechanism of the aqueous extract of S. nigrum L. (AESN) towards human breast cancer cell line MCF7. At a concentration of 10 g/L, AESN caused 43% cytotoxicity, inhibited the migration, and suppressed the activities of hexokinase and pyruvate kinase by about 30% and 40%, respectively, towards the MCF7 cells. RT2-PCR analysis of a panel of 89 caner-related genes identified 13 upregulated and eight downregulated genes (>2-folds) in MCF7 cells upon AESN treatment. Gene ontology (GO) and functional disease ontology (FunDO) analyses show that the antitumor function of S. nigrum L. involves multiple genes and these genes are shared across other diseases or disorders.
The Role of the Ω-Loop in Regulation of the Catalytic Activity of TEM-Type β-Lactamases
Authors: Egorov Alexey , Rubtsova Maya , Grigorenko Vitaly , Uporov Igor , Veselovsky Alexander
Published: December 2019

Bacterial resistance to β-lactams, the most commonly used class of antibiotics, poses a global challenge. This resistance is caused by the production of bacterial enzymes that are termed β-lactamases (βLs). The evolution of serine-class A β-lactamases from penicillin-binding proteins (PBPs) is related to the formation of the Ω-loop at the entrance to the enzyme’s active site. In this loop, the Glu166 residue plays a key role in the two-step catalytic cycle of hydrolysis. This residue in TEM–type β-lactamases, together with Asn170, is involved in the formation of a hydrogen bonding network with a water molecule, leading to the deacylation of the acyl–enzyme complex and the hydrolysis of the β-lactam ring of the antibiotic. The activity exhibited by the Ω-loop is attributed to the positioning of its N-terminal residues near the catalytically important residues of the active site. The structure of the Ω-loop of TEM-type β-lactamases is characterized by low mutability, a stable topology, and structural flexibility. All of the revealed features of the Ω-loop, as well as the mechanisms related to its involvement in catalysis, make it a potential target for novel allosteric inhibitors of β-lactamases.
Glucose Uptake Stimulatory and PTP1B Inhibitory Activities of Pimarane Diterpenes from Orthosiphon stamineus Benth
Authors: Nguyen Phi Hung , Tuan Huynh Nhu , Hoang Duc Thuan , Vu Quoc Trung , Pham Minh Quan , Tran Manh Hung , To Dao Cuong
Published: December 2019

Seven pimarane diterpenes (1–7) were isolated from Orthosiphon stamineus Benth. by assay-guided isolation. All of the isolates possessed a 2-deoxy-2-((7-nitro-2,1,3-benzoxadiazol-4-yl)amino)-d-glucose uptake effect in 3T3-L1 adipocytes at concentrations of 5 and 10 μM. Most of them showed potent inhibition against protein tyrosine phosphatase 1B with IC50 values ranging from 0.33 to 9.84 μM. In the kinetic study, all inhibition types were exposed for the examined potencies, including mixed-competitive (1), non-competitives (3 and 5), competitive (6), and uncompetitive (7). The results suggested that O. stamineus and its pimarane diterpenes might exert the hypoglycemic effect via the insulin signaling pathway targeting inhibition of protein tyrosine phosphatase 1B (PTP1B) activity.
Long-Lasting Effects of GSPE on Ileal GLP-1R Gene Expression Are Associated with a Hypomethylation of the GLP-1R Promoter in Female Wistar Rats
Authors: Ginés Iris , Gil-Cardoso Katherine , D’Addario Claudio , Falconi Anastasia , Bellia Fabio , Blay M Teresa , Terra Ximena , Ardévol Anna , Pinent Montserrat , Beltrán-Debón Raúl
Published: December 2019

Flavonoids have been shown to modulate GLP-1 in obesity. GLP-1 induces some of its effects through the intestinal GLP-1 receptor (GLP-1R), though no data exist on how flavonoids affect this receptor. Here, we examine how a dose of grape seed proanthocyanidin extract (GSPE) with anti-obesity activity affects intestinal GLP-1R and analyze whether epigenetics play a role in the long-lasting effects of GSPE. We found that 10-day GSPE administration prior to the cafeteria diet upregulated GLP-1R mRNA in the ileum 17 weeks after the GSPE treatment. This was associated with a hypomethylation of the GLP-1R promoter near the region where the SP1 transcription factor binds. In the colon, the cafeteria diet upregulated GLP-1R without showing any GSPE effect. In conclusion, we have identified long-lasting GSPE effects on GLP-1R gene expression in the ileum that are partly mediated by hypomethylation at the gene promoter and may affect the SP1 binding factor.
The Integrity of α-β-α Sandwich Conformation Is Essential for a Novel Adjuvant TFPR1 to Maintain Its Adjuvanticity
Authors: Li Qiao , Ning Xiuzhe , Wang Yuepeng , Zhu Qing , Guo Yan , Li Hao , Zhou Yusen , Kou Zhihua
Published: December 2019

TFPR1 is a novel peptide vaccine adjuvant we recently discovered. To define the structural basis and optimize its application as an adjuvant, we designed three different truncated fragments that have removed dominant B epitopes on TFPR1, and evaluated their capacity to activate bone marrow-derived dendritic cells and their adjuvanticity. Results demonstrated that the integrity of an α-β-α sandwich conformation is essential for TFPR1 to maintain its immunologic activity and adjuvanticity. We obtained a functional truncated fragment TFPR-ta ranging from 40–168 aa of triflin that has similar adjuvanticity as TFPR1 but with 2-log fold lower immunogenicity. These results demonstrated a novel approach to evaluate and improve the activity of protein-based vaccine adjuvant.
A Critical Comparison between Flow-through and Lateral Flow Immunoassay Formats for Visual and Smartphone-Based Multiplex Allergen Detection
Authors: Ross Georgina M. S. , Salentijn Gert IJ. , Nielen Michel W. F.
Published: December 2019

(1) Background: The lack of globally standardized allergen labeling legislation necessitates consumer-focused multiplexed testing devices. These should be easy to operate, fast, sensitive and robust. (2) Methods: Herein, we describe the development of three different formats for multiplexed food allergen detection, namely active and passive flow-through assays, and lateral flow immunoassays with different test line configurations. (3) Results: The fastest assay time was 1 min, whereas even the slowest assay was within 10 min. With the passive flow approach, the limits of detection (LOD) of 0.1 and 0.5 ppm for total hazelnut protein (THP) and total peanut protein (TPP) in spiked buffer were reached, or 1 and 5 ppm of THP and TPP spiked into matrix. In comparison, the active flow approach reached LODs of 0.05 ppm for both analytes in buffer and 0.5 and 1 ppm of THP and TPP spiked into matrix. The optimized LFIA configuration reached LODs of 0.1 and 0.5 ppm of THP and TPP spiked into buffer or 0.5 ppm for both analytes spiked into matrix. The optimized LFIA was validated by testing in 20 different blank and spiked matrices. Using device-independent color space for smartphone analysis, two different smartphone models were used for the analysis of optimized assays.
Synthesis of Hydroxy Sodalite from Coal Fly Ash for Biodiesel Production from Waste-Derived Maggot Oil
Authors: Malonda Shabani Juvet , Babajide Omotola , Oyekola Oluwaseun , Petrik Leslie
Published: December 2019

Zeolites are aluminosilicate crystalline materials known for their unique characteristics, and have been prominent for nearly half a century due to their wide and important industrial applications. The production of zeolites, however, remains a challenge due to the high cost of commercial reagents conventionally used as feedstocks. In the current study, hydroxy sodalite (HS) zeolite samples were synthesised from coal fly ash feedstock by a direct hydrothermal synthesis method. The effects of hydrothermal crystallisation synthesis time on phase crystallinity, crystal size, and morphology of the formed HS were investigated. The prepared samples were characterised using XRD, SEM, EDS and FT-IR techniques. The XRD results of the samples prepared with varying synthesis times confirmed the formation of HS from low to high phase purity and crystallinity from 11 to over 98%. The SEM results reflected gradual variation in crystal morphology, of which highly crystalline HS samples were associated with hexagonal-cubic and cubic-platelet crystals. The FTIR, depicting zeolite characteristics of T–O and T–O–T stretching vibrations in the molecular framework, further confirmed the formation of HS zeolites for samples obtained above the 24-h synthesis time. These zeolite samples were then evaluated for their catalytic activities in the conversion of maggot oil to biodiesel. The application of the various hydroxy sodalite samples for the transesterification of maggot oil yielded up to 84.10% biodiesel (FAME) with physicochemical properties that were in compliance with the biodiesel specification standards. This study investigated the novel use of a coal fly ash-derived, heterogeneous HS catalyst in biodiesel production from maggot oil, and indicates its potential to enhance biodiesel yield and quality upon process optimisation tests.
Cu(II) and Fe(III) Complexes Derived from N-Acetylpyrazine-2-Carbohydrazide as Efficient Catalysts Towards Neat Microwave Assisted Oxidation of Alcohols
Authors: Sutradhar Manas , Roy Barman Tannistha , Pombeiro Armando J. L. , Martins Luísa M. D. R. S.
Published: December 2019

The mononuclear Cu(II) complex [Cu((kNN′O-HL)(H2O)2] (1) was synthesized using N-acetylpyrazine-2-carbohydrazide (H2L) and characterized by elemental analysis, IR spectroscopy, ESI-MS and single crystal X-ray crystallography. Two Fe(III) complexes derived from the same ligand viz, mononuclear [Fe((kNN′O-HL)Cl2] (2) and the binuclear [Fe(kNN′O-HL)Cl(μ-OMe)]2 (3) (synthesized as reported earlier), were also used in this study. The catalytic activity of these three complexes (1–3) was examined towards the oxidation of alcohols using tert-butyl hydroperoxide (TBHP) as oxidising agent under solvent-free microwave irradiation conditions. Primary and secondary benzyl alcohols (benzyl alcohol and 1-phenylethanol), and secondary aliphatic alcohols (cyclohexanol) were used as model substrates for this study. A comparison of their catalytic efficiency was performed. Complex 1 exhibited the highest activity in the presence of TEMPO as promoter for the oxidation of 1-phenylethanol with a maximum yield of 91.3% of acetophenone.
Tailoring of Hydrotalcite-Derived Cu-Based Catalysts for CO2 Hydrogenation to Methanol
Authors: Frusteri Leone , Cannilla Catia , Todaro Serena , Frusteri Francesco , Bonura Giuseppe
Published: December 2019

Ternary CuxZnyAlz catalysts were prepared using the hydrotalcite (HT) method. The influence of the atomic x:y:z ratio on the physico-chemical and catalytic properties under CO2 hydrogenation conditions was probed. The characterization data of the investigated catalysts were obtained by XRF, XRD, BET, TPR, CO2-TPD, N2O chemisorption, SEM, and TEM techniques. In the “dried” catalyst, the typical structure of a hydrotalcite phase was observed. Although the calcination and subsequent reduction treatments determined a clear loss of the hydrotalcite structure, the pristine phase addressed the achievement of peculiar physico-chemical properties, also affecting the catalytic activity. Textural and surface effects induced by the zinc concentration conferred a very interesting catalyst performance, with a methanol space time yield (STY) higher than that of commercial systems operated under the same experimental conditions. The peculiar behavior of the hydrotalcite-like samples was related to a high dispersion of the active phase, with metallic copper sites homogeneously distributed among the oxide species, thereby ensuring a suitable activation of H2 and CO2 reactants for a superior methanol production.
Electrochemical Sensing of Caffeic Acid Using Gold Nanoparticles Embedded in Poly(3,4-ethylenedioxythiophene) Layer by Sinusoidal Voltage Procedure
Authors: Bottari Davide , Pigani Laura , Zanardi Chiara , Terzi Fabio , Paţurcă Sanda Victorinne , Grigorescu Sorin Dan , Matei Cristian , Lete Cecilia , Lupu Stelian
Published: December 2019

The increasing demand for sensitive electrochemical sensors in various medical and industrial applications promotes the fabrication of novel sensing materials with improved electrocatalytic and analytical performances. This work deals with the development of a composite material based on gold nanoparticles (AuNPs) embedded in poly(3,4-ethylenedioxythiophene) (PEDOT) layer for electrochemical determination of caffeic acid (CA). CA is a phenolic compound with excellent antioxidant properties that is present in vegetables, fruits, and alcoholic and non-alcoholic beverages. Its analytical quantification is of great interest in food production monitoring and healthcare applications. Therefore, the development of sensitive analytical devices for CA monitoring is required. The AuNPs have been prepared in situ onto PEDOT coated glassy carbon electrode (GC) by means of an innovative procedure consisting on the use of a sinusoidal voltage (SV) superimposed on a constant potential. The physico-chemical properties of the PEDOT-AuNPs composite material were investigated by a range of techniques including cyclic voltammetry, electrochemical quartz crystal microbalance, and scanning electron microscopy. The glassy carbon electrode/poly(3,4-ethylenedioxythiophene)-gold nanoparticles-sinusoidal voltage (GC/PEDOT-AuNPs-SV) sensor exhibited good analytical performance toward the CA quantification with a linear response over a wide concentration range from 10 µM to 1 mM. In addition, the proposed GC/PEDOT-AuNPs-SV sensor was successfully applied in the determination of total polyphenols content expressed as equivalents of CA in juice samples.
A Hierarchical Machine Learning Model to Discover Gleason Grade-Specific Biomarkers in Prostate Cancer
Authors: Hamzeh Osama , Alkhateeb Abedalrhman , Zheng Julia Zhuoran , Kandalam Srinath , Leung Crystal , Atikukke Govindaraja , Cavallo-Medved Dora , Palanisamy Nallasivam , Rueda Luis
Published: December 2019

(1) Background:One of the most common cancers that affect North American men and men worldwide is prostate cancer. The Gleason score is a pathological grading system to examine the potential aggressiveness of the disease in the prostate tissue. Advancements in computing and next-generation sequencing technology now allow us to study the genomic profiles of patients in association with their different Gleason scores more accurately and effectively. (2) Methods: In this study, we used a novel machine learning method to analyse gene expression of prostate tumours with different Gleason scores, and identify potential genetic biomarkers for each Gleason group. We obtained a publicly-available RNA-Seq dataset of a cohort of 104 prostate cancer patients from the National Center for Biotechnology Information’s (NCBI) Gene Expression Omnibus (GEO) repository, and categorised patients based on their Gleason scores to create a hierarchy of disease progression. A hierarchical model with standard classifiers in different Gleason groups, also known as nodes, was developed to identify and predict nodes based on their mRNA or gene expression. In each node, patient samples were analysed via class imbalance and hybrid feature selection techniques to build the prediction model. The outcome from analysis of each node was a set of genes that could differentiate each Gleason group from the remaining groups. To validate the proposed method, the set of identified genes were used to classify a second dataset of 499 prostate cancer patients collected from cBioportal. (3) Results: The overall accuracy of applying this novel method to the first dataset was 93.3%; the method was further validated to have 87% accuracy using the second dataset. This method also identified genes that were not previously reported as potential biomarkers for specific Gleason groups. In particular, PIAS3 was identified as a potential biomarker for Gleason score 4 + 3 = 7, and UBE2V2 for Gleason score 6. (4) Insight: Previous reports show that the genes predicted by this newly proposed method strongly correlate with prostate cancer development and progression. Furthermore, pathway analysis shows that both PIAS3 and UBE2V2 share similar protein interaction pathways, the JAK/STAT signaling process.
Milestones of Dentistry: Advent of Anesthetics in Oral Surgery
Authors: Cervino Gabriele
Published: December 2019

The history of dentistry, of course, has followed a constant development since the dawn of society. The dental profession, reserved in ancient times to people with special skills and high rank, after the Middle Ages was diminished and practiced by barbers. The pharmacological evolution of oral surgery techniques has led this branch, today as never before, to obtain a level of specialization and preparation comparable to all other specialist medical branches. Some milestones in the history of dentistry will be considered so as to finally understand how the importance of anesthetic drugs was of primary importance, and which drugs are used today.
A Novel Improved Feature Extraction Technique for Ship-Radiated Noise Based on IITD and MDE
Authors: Li Zhaoxi , Li Yaan , Zhang Kai , Guo Jianli
Published: December 2019

Ship-radiated noise signal has a lot of nonlinear, non-Gaussian, and nonstationary information characteristics, which can reflect the important signs of ship performance. This paper proposes a novel feature extraction technique for ship-radiated noise based on improved intrinsic time-scale decomposition (IITD) and multiscale dispersion entropy (MDE). The proposed feature extraction technique is named IITD-MDE. First, IITD is applied to decompose the ship-radiated noise signal into a series of intrinsic scale components (ISCs). Then, we select the ISC with the main information through the correlation analysis, and calculate the MDE value as feature vectors. Finally, the feature vectors are input into the support vector machine (SVM) for ship classification. The experimental results indicate that the recognition rate of the proposed technique reaches 86% accuracy. Therefore, compared with the other feature extraction methods, the proposed method provides a new solution for classifying different types of ships effectively.
Dynamic Performance Evaluation of Various GNSS Receivers and Positioning Modes with Only One Flight Test
Authors: Lim Cheolsoon , Yoon Hyojung , Cho Am , Yoo Chang-Sun , Park Byungwoon
Published: December 2019

The performance of global navigation satellite system (GNSS) receivers in dynamic modes is mostly assessed using results obtained from independent maneuvering of vehicles along similar trajectories at different times due to limitations of receivers, payload, space, and power of moving vehicles. However, such assessments do not ensure valid evaluation because the same GNSS signal environment cannot be ensured in a different test session irrespective of how accurately it mimics the original session. In this study, we propose a valid methodology that can evaluate the dynamic performance of multiple GNSS receivers in various positioning modes with only one dynamic test. We used the record-and-replay function of RACELOGIC’s LabSat3 Wideband and developed a software that can log and re-broadcast Radio Technical Commission for Maritime Services (RTCM) messages for the augmented systems. A preliminary static test and a drone test were performed to verify proper operation of the system. The results show that the system could efficiently evaluate the performances of stand-alone, differential GNSS, and real time kinematics positioning for three GNSS receivers in two different positioning modes by repeatedly re-radiating the recorded signals acquired through only one flight. Our proposed system is expected to be useful in evaluating dynamic navigation performance accurately and conveniently in a valid manner.
Realization of High-Performance Broadband Quadrature Directional Couplers in UMS PH25 Technology
Authors: Gruszczynski Slawomir , Smolarz Robert , Wincza Krzysztof
Published: December 2019

The problem of the realization of broadband quadrature directional couplers in UMS (United Monolithic Semiconductors) PH25 is thoroughly investigated. The limitations of the selected technology are discussed with respect to directional couplers’ design. It is shown that, in such technologies, two major problems have to be overcome to achieve the high-performance of the resulting integrated couplers, i.e., the realization of appropriate coupling together with appropriate characteristic impedances, and the equalization of inductive and capacitive coupling coefficients that are inherently different in inhomogeneous dielectric structures. Three different solutions that allow for achieving strong coupling in the selected UMS PH25 process were selected and experimentally investigated, showing the possibility of such circuits’ realization. In each of the presented integrated couplers, capacitive compensation techniques were applied for coupling coefficients’ equalization.
Accelerating Retinal Fundus Image Classification Using Artificial Neural Networks (ANNs) and Reconfigurable Hardware (FPGA)
Authors: Ghani Arfan , See Chan H. , Sudhakaran Vaisakh , Ahmad Jahanzeb , Abd-Alhameed Raed
Published: December 2019

Diabetic retinopathy (DR) and glaucoma are common eye diseases that affect a blood vessel in the retina and are two of the leading causes of vision loss around the world. Glaucoma is a common eye condition where the optic nerve that connects the eye to the brain becomes damaged, whereas DR is a complication of diabetes caused by high blood sugar levels damaging the back of the eye. In order to produce an accurate and early diagnosis, an extremely high number of retinal images needs to be processed. Given the required computational complexity of image processing algorithms and the need for high-performance architectures, this paper proposes and demonstrates the use of fully parallel field programmable gate arrays (FPGAs) to overcome the burden of real-time computing in conventional software architectures. The experimental results achieved through software implementation were validated on an FPGA device. The results showed a remarkable improvement in terms of computational speed and power consumption. This paper presents various preprocessing methods to analyse fundus images, which can serve as a diagnostic tool for detection of glaucoma and diabetic retinopathy. In the proposed adaptive thresholding-based preprocessing method, features were selected by calculating the area of the segmented optic disk, which was further classified using a feedforward neural network (NN). The analysis was carried out using feature extraction through existing methodologies such as adaptive thresholding, histogram and wavelet transform. Results obtained through these methods were quantified to obtain optimum performance in terms of classification accuracy. The proposed hardware implementation outperforms existing methods and offers a significant improvement in terms of computational speed and power consumption.
An Electromagnetic Lock Actuated by a Mobile Phone Equipped with a Self-Made Laser Pointer
Authors: Perng Jau-Woei , Hsieh Tung-Li
Published: December 2019

The main purpose of this study was to create an acousto-optic control lock device to convert electrical signals with a specific sound command using an acousto-optic conversion module, thereby improving the reliability and safety of opening or closing remote controlled door locks, such as car central locks or rolling doors. We used music playing through a smart phone speaker to create a special laser pointer to connect with the smart phone‘s auxiliary input. The laser pointer (wavelength of 630–650 nm and maximum output of 5 mw) lights up when the smart phone’s music starts playing at a music frequency matching the light frequency. When the solar panel receives light, it converts the frequency of the light signal into an electrical frequency signal. The current is amplified using the power amplifier and then the amplified current flows to the sound recognition module. The sound recognition module performs audio comparison on the set sound signal, and once the comparison is correct, the output voltage activates the electromagnetic switch on the door to open or close it.
Energy Rate Maximization with Sum-Rate Constraint for SWIPT in Multiple-Access Channels
Authors: Shim Yeonggyu , Shin Wonjae
Published: December 2019

This paper considers simultaneous wireless information and power transfer (SWIPT) systems in the two-user Gaussian multiple access channel (G-MAC). In SWIPT systems, for a transmit signal each transmitter consists of an information-carrying signal and energy-carrying signal. By controlling a different set of the power for the information transmission and power for the energy transmission under a total power constraint, the information sum-rate and energy transmission rate can be achieved. As the information carrying-to-transmit power ratio at transmitters and the information sum-rate increases, however, the energy transmission rate decreases. In other words, there is a fundamental trade-off between the information sum-rate and the energy transmission rate according to the power-splitting ratio at each transmitter. Motivated by this, this paper proposes an optimal power-splitting scheme that maximizes the energy transmission rate subject to a minimum sum-rate constraint. In particular, a closed-form expression of the power-splitting coefficient is presented for the two-user G-MAC under a minimum sum-rate constraint. Numerical results show that the energy rate of the proposed optimal power-splitting scheme is greater than that of the fixed power-splitting scheme.
A Two-Degree-of-Freedom Cantilever-Based Vibration Triboelectric Nanogenerator for Low-Frequency and Broadband Operation
Authors: Tang Gang , Cheng Fang , Hu Xin , Huang Bo , Xu Bin , Li Zhibiao , Yan Xiaoxiao , Yuan Dandan , Wu Wenjing , Shi Qiongfeng
Published: December 2019

With the continual increasing application requirements of broadband vibration energy harvesters (VEHs), many attempts have been made to broaden the bandwidth. As compared to adopted only a single approach, integration of multi-approaches can further widen the operating bandwidth. Here, a novel two-degree-of-freedom cantilever-based vibration triboelectric nanogenerator is proposed to obtain high operating bandwidth by integrating multimodal harvesting technique and inherent nonlinearity broadening behavior due to vibration contact between triboelectric surfaces. A wide operating bandwidth of 32.9 Hz is observed even at a low acceleration of 0.6 g. Meanwhile, the peak output voltage is 18.8 V at the primary resonant frequency of 23 Hz and 1 g, while the output voltage is 14.9 V at the secondary frequency of 75 Hz and 2.5 g. Under the frequencies of these two modes at 1 g, maximum peak power of 43.08 μW and 12.5 μW are achieved, respectively. Additionally, the fabricated device shows good stability, reaching and maintaining its voltage at 8 V when tested on a vacuum compression pump. The experimental results demonstrate the device has the ability to harvest energy from a wide range of low-frequency (<100 Hz) vibrations and has broad application prospects in self-powered electronic devices and systems.
Comparison of Open Source Power Grid Models—Combining a Mathematical, Visual and Electrical Analysis in an Open Source Tool
Authors: Heitkoetter Wilko , Medjroubi Wided , Vogt Thomas , Agert Carsten
Published: December 2019

Power grid models are important in relation to several topics and applications, especially the modelling, optimisation and extension of electrical grids. The significance of grid models is heightened by the increase in renewable energy generation and the challenges associated with its integration into the power grid. However, despite their crucial importance, grid models have generally not been made publicly available for scientific studies or technical analyses. Little information has been published about either the details and methods used in the derivation of these models, or their input and output data. Recently, several projects were initiated in an effort to address this by developing open source grid models and associated data. These projects used different approaches and methods, but most are based on the OpenStreetMap database. The goal of this paper is to compare the different available grid models on the basis of the structure and derivation methods used. Therefore, a novel combination of a graph-theoretical, Geographic Information System (GIS)-based and power-related comparison level is introduced using the open source tool AutoGridComp, which was developed by the authors. The grid models considered in this study are the Scientific Grid Model (SciGRID), GridKit and open street map Transmission Grid Model (osmTGmod) models for Germany.