bluuebunny/crossref_metadata_2025 huggingface dataset:
Decay Process of Serpentinite: The Case of the San Giovanni Baptistery (Florence, Italy) Pavement
Authors: Santo Alba Patrizia , Agostini Beatrice , Garzonio Carlo Alberto , Pecchioni Elena , Salvatici Teresa
Published: January 2022

Serpentinite is a low-grade metamorphic rock derived from the transformation of ultramafic rocks. Mainly because of its aesthetic characteristics it has been widely used as a building and ornamental stone. “Verde di Prato” is the most common local name used in Tuscany to refer to this type of rock, historically quarried in this area and used for many centuries in a large number of monuments of this region. In this paper, we report the results of a study carried out on the serpentinite from the pavement of the Florence baptistery, to properly characterize it from a physical point of view, describe the rock conservation state, and understand the phenomena responsible for its decay. The studied rock displays numerous forms of decay including fractures, loss of material, erosion, discolouration and efflorescence. X-ray diffractometer analyses of the efflorescence revealed the presence of numerous salts whose formation can be imputed to multiple, possibly concomitant, causes such as the high relative humidity and the variation of inside temperature, the presence of concrete and/or cementitious mortars in the subsoil, atmospheric pollution and the burial ground existing close the baptistery.
The LCA Commons—How an Open-Source Repository for US Federal Life Cycle Assessment (LCA) Data Products Advances Inter-Agency Coordination
Authors: Kahn Ezra , Antognoli Erin , Arbuckle Peter
Published: January 2022

Life cycle assessment (LCA) is a flexible and powerful tool for quantifying the total environmental impact of a product or service from cradle-to-grave. The US federal government has developed deep expertise in environmental LCA for a range of applications including policy, regulation, and emerging technologies. LCA professionals from across the government have been coordinating the distributed LCA expertise through a community of practice known as the Federal LCA Commons. The Federal LCA Commons has developed open data infrastructure and workflows to share knowledge and align LCA methods. This data infrastructure is a key component to creating a harmonized network of LCA capacity from across the federal government.
Analysis of Non-Minimum Phase System for AC/DC Battery Charger Power Factor Correction Converter
Authors: Nassary Mahmoud , Vidal-Idiarte Enric , Calvente Javier
Published: January 2022

Electric mobility is nowadays one of the more important trends regarding pollution reduction and global warming due to fuel consumption. Big efforts are done in order to develop efficient and reliable power electronic systems for electric vehicles. In two stage on board-battery chargers, one way of improving efficiency is by means of ensuring the DC-DC isolated converter always operates in the nominal input/output voltage ratio, that could be achieved with a variable DC-link operation. In this paper, a four-switch buck-boost based AC/DC converter is deeply analyzed in order to improve its dynamic performance, the power factor and the total harmonic distortion. The converter suffers from a non-minimum phase characteristic in different input–output transfer functions, which reduces the closed-loop bandwidth of the system. Therefore, after a deep converter analysis has been done, different solutions have been evaluated and tested. Finally, a control to different output transfer functions of the converter become minimum phase, which allows us to increase the system bandwidth and, consequently, high power factor, low harmonics distortion, single control structure and fast dynamics for wide output voltage range are achieved.
A Discrete Process Modelling and Simulation Methodology for Industrial Systems within the Concept of Digital Twins
Authors: Tsinarakis George , Sarantinoudis Nikolaos , Arampatzis George
Published: January 2022

A generic well-defined methodology for the construction and operation of dynamic process models of discrete industrial systems following a number of well-defined steps is introduced. The sequence of steps for the application of the method as well as the necessary inputs, conditions, constraints and the results obtained are defined. The proposed methodology covers the classical offline modelling and simulation applications as well as their online counterpart, which use the physical system in the context of digital twins, with extensive data exchange and interaction with sensors, actuators and tools from other scientific fields as analytics and optimisation. The implemented process models can be used for what-if analysis, comparative evaluation of alternative scenarios and for the calculation of key performance indicators describing the behaviour of the physical systems under given conditions as well as for online monitoring, management and adjustment of the physical industrial system operations with respect to given rules and targets. An application of the proposed methodology in a discrete industrial system is presented, and interesting conclusions arise and are discussed. Finally, the open issues, limitations and future extensions of the research are considered.
Value-Added Use of Waste PET in Rubberized Asphalt Materials for Sustainable Pavement
Authors: Xu Xiong , Chu Yaming , Luo Yi , Wu Qiaoyun , Chen Xuyong , Shu Suxun
Published: January 2022

Waste poly(ethylene terephthalate) (PET) drinking bottles and end-of-life scrap rubber tires are common municipal solid wastes discarded and produced every day, which are usually disposed of in landfills and stockpiles, occupying a great quantity of land and causing serious environmental issues. This study aims to first turn waste PET into two value-added derived additives under the chemical treatment of two amines, namely triethylenetetramine (TETA) and ethanolamine (EA), respectively, and then adopt them in association with crumb rubber (CR) to modify virgin bitumen for preparing various rubberized asphalt mixtures. Subsequently, the high- and low-temperature properties of the rubberized binder modified by PET additives (PET-TETA and PET-EA) were comparatively characterized through dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests, while the rutting resistance, fatigue resistance, and dynamic modulus of the further fabricated mixtures were evaluated and validated through mixture tests. The results obtained indicate that 2 wt.% PET-TETA and PET-EA contribute to increase the rutting failure temperature of asphalt rubber from 82.2 °C to 85.5 °C and 84.2 °C, respectively, retaining the high grade of PG 82; the low-temperature grade of asphalt rubber slightly decreased from PG-28 to PG-22 as the additive was added; the rut depth slightly changed from 3.10 mm to nearly 3.70 mm; and PET-TETA exhibits the potential to be capable of extending the fatigue life of asphalt rubber in contrast with PET-EA at different stress levels within 450 kPa. Based on the findings of this study, the developed recycling approach is considered to be applicable to not only alleviate the environmental concerns caused by the landfills and stockpiles of those wastes but also make them valuable for building more durable pavement.
Laplace Transform for Finite Element Analysis of Electromagnetic Interferences in Underground Metallic Structures
Authors: Cristofolini Andrea , Popoli Arturo , Sandrolini Leonardo , Pierotti Giacomo , Simonazzi Mattia
Published: January 2022

A numerical methodology is proposed for the calculation of transient electromagnetic interference induced by overhead high-voltage power lines in metallic structures buried in soil—pipelines for oil or gas transportation. A series of 2D finite element simulations was employed to sample the harmonic response of a given geometry section. The numerical inverse Laplace transform of the results allowed obtaining the time domain evolution of the induced voltages and currents in the buried conductors, for any given condition of the power line.
Impact of Water Solubility on Chemical Composition and Surface Structure of Two Generations of Bioceramic Root Canal Sealers
Authors: Abu Zeid Sawsan T. , Alamoudi Ruaa A. , Mokeem Saleh Abeer A.
Published: January 2022

Aimed to evaluate the effect of water solubility on chemical properties and surface structure of bioceramic-based (BC-HiFlow and BC-EndoSeqence) compared with resin-based (Adseal) root canal sealers. Fresh mix was inserted into polyethylene mold (n = 10) and subjected to Vicat needle to evaluate the setting time. The set discs were analyzed by Fourier transform infrared (FTIR) spectroscopy then immersed in deionized water for 1, 7, 14 and 28 days. The solubility%, pH changes, released calcium (Ca2+), phosphate (PO43−) and silicon (Si4+) ions were evaluated after each immersion period. The discs were analyzed by scanning electron microscopy/Energy dispersed X-ray (SEM/EDX) before and after solubility test. Although FTIR detected similar composition of both bioceramic-sealers, BC-EndoSequence determined the prolonged setting times. At the end of solubility test, both bioceramic-sealers exhibited significant greater solubility (>3%), alkaline pH (>11) at p < 0.001. Adseal displayed the significant greatest Ca2+ and PO43− released, while BC-HiFlow displayed the significant greatest Si4+ release (p < 0.001). SEM revealed voids and pores on the surface of all tested sealers with the greatest value on Adseal surface. In conclusion, although both bioceramic-sealers had high solubility, BC-Hiflow complied the ISO standard regarding setting time and least surface micropores better than that of BC-EndoSequence.
A Novel Synthetization Approach for Multi Coupled Line Section Impedance Transformers in Wideband Applications
Authors: Zhang Nan , Wang Xiaolong , Bao Chunxi , Wu Bin , Chen Chun-Ping , Ma Zhewang , Lu Geyu
Published: January 2022

In this paper, a novel synthetization approach is proposed for filter-integrated wideband impedance transformers (ITs). The original topology consists of N cascaded coupled line sections (CLSs) with 2N characteristic impedance parameters. By analyzing these characteristic impedances, a Chebyshev response can be derived to consume N + 2 design conditions. To optimize the left N − 2 variable parameters, CLSs were newly substituted by transmission lines (TLs) to consume the remaining variable parameters and simplify the circuit topology. Therefore, there are totally 2N − N − 2 substituting possibilities. To verify the proposed approach, 25 cases are listed under the condition of N = 5, and 7 selected cases are compared and discussed in detail. Finally, a 75–50 Ω IT with 100% fractional bandwidth and 20 dB bandpass return loss (RL) is designed and fabricated. The measured results meet the circuit simulation and the EM simulation accurately.
Anti-Inflammatory Activity of a Demineralized Bone Matrix: An In Vitro Pilot Study
Authors: Panahipour Layla , Omerbasic Anes , Oladzad Abbasabadi Azarakhsh , Nasirzade Jila , Kargarpour Zahra , Gruber Reinhard
Published: January 2022

Demineralized bone matrix (DBM) is commonly used for the reconstruction of bone defects. Early graft consolidation involves a transient inflammatory process. It is, however, unclear whether DBM can modulate this process. To test this possibility, we prepared acid lysates of demineralized ground cortical (DGC) and moldable demineralized fibers (MDF). Murine RAW 264.7 and primary bone marrow macrophages were exposed to acid lysates of DGC and MFD prior to provoking an inflammatory response with lipopolysaccharide (LPS). Similarly, murine ST2 mesenchymal cells were exposed to DGC and MFD with and without interleukin 1β (IL1) and TNFα. We show here that acid lysates of DGC and MFD reduced the expression of IL1 and IL6 in RAW 264.7 macrophages, as determined by RT-PCR and, for IL6, by immunoassay. This response was confirmed with primary macrophages. Likewise, desalted acid lysates exert anti-inflammatory properties on RAW 264.7 cells and in ST2 cells, the forced expression of IL6, inducible nitric oxide synthase (iNOS) and chemokine ligand 5 (CCL5) was reduced. These in vitro findings suggest that DGC and MFD lower the inflammation-induced expression of inflammatory mediators in murine cell-based bioassays.
Augmented, Virtual and Mixed Reality in Dentistry: A Narrative Review on the Existing Platforms and Future Challenges
Authors: Monterubbianesi Riccardo , Tosco Vincenzo , Vitiello Flavia , Orilisi Giulia , Fraccastoro Franco , Putignano Angelo , Orsini Giovanna
Published: January 2022

The recent advancements in digital technologies have led to exponential progress in dentistry. This narrative review aims to summarize the applications of Augmented Reality, Virtual Reality and Mixed Reality in dentistry and describes future challenges in digitalization, such as Artificial Intelligence and Robotics. Augmented Reality, Virtual Reality and Mixed Reality represent effective tools in the educational technology, as they can enhance students’ learning and clinical training. Augmented Reality and Virtual Reality and can also be useful aids during clinical practice. Augmented Reality can be used to add digital data to real life clinical data. Clinicians can apply Virtual Reality for a digital wax-up that provides a pre-visualization of the final post treatment result. In addition, both these technologies may also be employed to eradicate dental phobia in patients and further enhance patient’s education. Similarly, they can be used to enhance communication between the dentist, patient, and technician. Artificial Intelligence and Robotics can also improve clinical practice. Artificial Intelligence is currently developed to improve dental diagnosis and provide more precise prognoses of dental diseases, whereas Robotics may be used to assist in daily practice.
Mechanical Strength Study of a Cranial Implant Using Computational Tools
Authors: Santos Pedro O. , Carmo Gustavo P. , Sousa Ricardo J. Alves de , Fernandes Fábio A. O. , Ptak Mariusz
Published: January 2022

The human head is sometimes subjected to impact loads that lead to skull fracture or other injuries that require the removal of part of the skull, which is called craniectomy. Consequently, the removed portion is replaced using autologous bone or alloplastic material. The aim of this work is to develop a cranial implant to fulfil a defect created on the skull and then study its mechanical performance by integrating it on a human head finite element model. The material chosen for the implant was PEEK, a thermoplastic polymer that has been recently used in cranioplasty. A6 numerical model head coupled with an implant was subjected to analysis to evaluate two parameters: the number of fixation screws that enhance the performance and ensure the structural integrity of the implant, and the implant’s capacity to protect the brain compared to the integral skull. The main findings point to the fact that, among all tested configurations of screws, the model with eight screws presents better performance when considering the von Mises stress field and the displacement field on the interface between the implant and the skull. Additionally, under the specific analyzed conditions, it is observable that the model with the implant offers more efficient brain protection when compared with the model with the integral skull.
Relationships between Racket Arm Joint Moments and Racket Head Speed during the Badminton Jump Smash Performed by Elite Male Malaysian Players
Authors: Ramasamy Yuvaraj , Sundar Viswanath , Usman Juliana , Razman Rizal , Towler Harley , King Mark A.
Published: January 2022

Three-dimensional position data of nineteen elite male Malaysian badminton players performing a series of maximal jump smashes were collected using a motion capture system. A ‘resultant moments’ inverse dynamics analysis was performed on the racket arm joints (shoulder, elbow and wrist). Relationships between racket head speed and peak joint moments were quantified using correlational analyses, inclusive of a Benjamini–Hochberg correction for multiple-hypothesis testing. The racket head centre speed at racket–shuttlecock contact was, on average, 61.2 m/s with a peak of 68.5 m/s which equated to average shuttlecock speeds of 95.2 m/s with a peak of 105.0 m/s. The correlational analysis revealed that a larger shoulder internal rotation moment (r = 0.737), backwards shoulder plane of elevation moment (r = 0.614) and wrist extension moment (r = −0.564) were associated with greater racket head centre speed at racket–shuttlecock contact. Coaches should consider strengthening the musculature associated with shoulder internal rotation, plane of elevation and wrist extension. This work provides a unique analysis of the joint moments of the racket arm during the badminton jump smash performed by an elite population and highlights significant relationships between racket head speed and peak resultant joint moments.
Impact of Plant Growth Regulators to Development of the Second Generation Energy Crop Miscanthus × giganteus Produced Two Years in Marginal Post-Military Soil
Authors: Pidlisnyuk Valentina , Stefanovska Tatyana , Zhukov Olexander , Medkow Artem , Shapoval Pavlo , Stadnik Vitalii , Sozanskyi Martyn
Published: January 2022

The impact of the plant growth regulators (PGRs) Stimpo, Regoplant, and Charkor on the production of the second-generation energy crop Miscanthus × giganteus on marginal post-military soil was investigated during two vegetation seasons. The land, previously a tank training polygon, has not been in use since 1990 and has become marginal. Biological parameters (stem, shoot, and root lengths) and dry biomass values were evaluated in relation to the applied treatments. The multivariate general linear model (M-GLM) results showed a positive influence of Charkor on M. × giganteus development; the effect was markedly higher in the second year of vegetation. The impact of Stimpo and Regoplant was less noticeable; nevertheless, certain combinations of treatments showed satisfactory results. The M-GLM approach detected the inter-influence of the main factors of the production process, i.e., PGRs, soil, and year of growing. The results showed the predominant influence of year, PGRs and combined factor PGRs × year on the biological parameters; the other studied factors and their combinations were not as effective. Further research should focus on verifying the field-scale results for the M. × giganteus plantation established in a post-military area and compare the lab and field studies.
Suppression of Frequency Modulation to Amplitude Modulation Conversion with Modified Group Velocity Dispersion Compensation Device in the Front End of High-Power Lasers
Authors: Qian Xinlei , Wang Xiaochao , Lu Xinghua , Zhang Tianyu , Fan Wei
Published: January 2022

The group velocity dispersion (GVD) occurring in the front end of high-power lasers is one of the primary factors leading to the conversion of frequency modulation (FM) to amplitude modulation (AM). In this paper, we propose a modified, active, closed-loop feedback compensation device for GVD-induced FM–AM conversion, using a two-dimensional, electric, adjustable mirror mount and parallel grating pair to improve the long-term stability, efficiency of adjustment, and accuracy of compensation. Experimental results of a 12 h FM–AM depth test revealed that the depth varied between 2.28% and 5.22%. Moreover, we formulated a mathematical relationship between the dispersion parameters and temperature in optical fibers to analyze the intrinsic effect of temperature on FM–AM. The related simulation and experimental results consistently validated the quantitative relationship between the temperature and FM–AM depth.
State-of-Health of Li-Ion Battery Estimation Based on the Efficiency of the Charge Transfer Extracted from Impedance Spectra
Authors: Kallel Ahmed Yahia , Petrychenko Viktor , Kanoun Olfa
Published: January 2022

Several studies show that impedance spectroscopy is a suitable method for online battery diagnosis and State-of-Health (SoH) estimation. However, the most common method is to model the acquired impedance spectrum with equivalent circuits and focus on the most sensitive parameters, namely the charge-transfer resistance. This paper introduces first a detailed model of a battery cell, which is then simplified and adapted to the observable spectrum behavior. Based on the physical meaning of the model parameters, we propose a novel approach for SoH assessment combining parameters of the impedance spectrum by building the ratio of the solid electrolyte interphase (SEI) resistance to the total resistance of SEI and the charge transfer. This ratio characterizes the charge-transfer efficiency at the electrodes’ surfaces and should decrease systematically with SoH. Four different cells of the same type were cycled 400 times for the method validation, and impedance spectroscopy was performed at every 50th cycle. The results show a systematic correlation between the proposed ratio and the number of cycles on individual cell parameters, which build the basis of a novel online method of SoH assessment.
Femtosecond-Laser-Assisted Fabrication of Radiation-Resistant Fiber Bragg Grating Sensors
Authors: Choi Hun-Kook , Jung Young-Jun , Yu Bong-Ahn , Sung Jae-Hee , Sohn Ik-Bu , Kim Jong-Yeol , Ahsan Md. Shamim
Published: January 2022

This paper demonstrates the fabrication of radiation-resistant fiber Bragg grating (FBG) sensors using infrared femtosecond laser irradiation. FBG sensors were written inside acrylate-coated fluorine-doped single-mode specialty optical fibers. We detected the Bragg resonance at 1542 nm. By controlling the irradiation conditions, we improved the signal strength coming out from the FBG sensors. A significant reduction in the Bragg wavelength shift was detected in the fabricated FBG sensors for a radiation dose up to 105 gray, indicating excellent radiation resistance capabilities. We also characterized the temperature sensitivity of the radiation-resistant FBG sensors and detected outstanding performance.
Eco-Friendly Synthesis and Comparative In Vitro Biological Evaluation of Silver Nanoparticles Using Tagetes erecta Flower Extracts
Authors: Burlec Ana Flavia , Hăncianu Monica , Macovei Irina , Mircea Cornelia , Fifere Adrian , Turin-Moleavin Ioana-Andreea , Tuchiluș Cristina , Robu Silvia , Corciovă Andreia
Published: January 2022

The present study reports an eco-friendly synthesis method of silver nanoparticles (AgNPs) using two different extracts (aqueous and ethanolic) of Tagetes erecta flowers. When exposed to different biocompounds found in the plant, silver ions are reduced, thus, resulting in the green synthesis of nanoparticles. After performing the optimization of synthesis, the obtained AgNPs were characterized using various techniques. The UV–Vis spectrum of the synthesized nanoparticles showed maximum peaks at 410 and 420 nm. TEM analysis revealed that the particles were spherical with a size ranging from 10 to 15 nm, and EDX analysis confirmed the presence of silver metal. The average diameter value obtained through DLS analysis for the two types of AgNPs (obtained using aqueous and ethanolic extracts) was 104 and 123 nm. The Zeta potentials of the samples were −27.74 mV and −26.46 mV, respectively, which indicates the stability of the colloidal solution. The antioxidant and antimicrobial activities assays showed that nanoparticles obtained using the aqueous extract presented enhanced antioxidant activity compared to the corresponding extract, with both types of AgNPs exhibiting improved antifungal properties compared to the initial extracts.
Multi-Objective Optimization of Hybrid Renewable Tri-Generation System Performance for Buildings
Authors: Ghorab Mohamed , Yang Libing , Entchev Evgueniy , Lee Euy-Joon , Kang Eun-Chul , Kim Yu-Jin , Bae Sangmu , Nam Yujin , Kim Kwonye
Published: January 2022

Hybrid renewable energy systems are subject to extensive research around the world and different designs have found their way to the market and have been commercialized. These systems usually employ multiple components, both renewable and conventional, combined in a way to increase the system’s overall efficiency and resilience and to lower GHG emissions. In this paper, a hybrid renewable energy system was designed for residential use and its annual energy performance was investigated and optimized. The multi-module hybrid system consists of a Ground-Air Heat Exchanger (GAHX), Photovoltaic Thermal (PVT) panels and Air to Water Heat Pump (AWHP). The developed system’s annual performance was simulated in the TRaNsient SYStem (TRNSYS) environment and optimized using the General Algebraic Modelling System (GAMS) platform. Multi-objective non-linear optimization algorithms were developed and applied to define optimal system design and performance parameters while reducing cost and GHG emissions. The results revealed that the designed system was able to satisfy building thermal heating/cooling loads throughout the year. The ground source heat exchanger contributed 21.3% and 26.3% of the energy during heating and cooling seasons, respectively. The initial design was optimized in terms of key performance parameters and module sizes. The annual simulation analysis showed that the system was able to self-generate and meet nearly 29.4% of the total HVAC electricity needs, with the rest being supplied by the grid. The annual system module performance efficiencies were 13.4% for the PVT electric and 5.5% for the PVT thermal, with an AWHP COP of 4.0.
An α-Model Parametrization Algorithm for Optimization with Differential-Algebraic Equations
Authors: Drąg Paweł
Published: January 2022

An optimization task with nonlinear differential-algebraic equations (DAEs) was approached. In special cases in heat and mass transfer engineering, a classical direct shooting approach cannot provide a solution of the DAE system, even in a relatively small range. Moreover, available computational procedures for numerical optimization, as well as differential- algebraic systems solvers are characterized by their limitations, such as the problem scale, for which the algorithms can work efficiently, and requirements for appropriate initial conditions. Therefore, an αDAE model optimization algorithm based on an α-model parametrization approach was designed and implemented. The main steps of the proposed methodology are: (1) task discretization by a multiple-shooting approach, (2) the design of an α-parametrized system of the differential-algebraic model, and (3) the numerical optimization of the α-parametrized system. The computations can be performed by a chosen iterative optimization algorithm, which can cooperate with an outer numerical procedure for solving DAE systems. The implemented algorithm was applied to solve a counter-flow exchanger design task, which was modeled by the highly nonlinear differential-algebraic equations. Finally, the new approach enabled the numerical simulations for the higher values of parameters denoting the rate of changes in the state variables of the system. The new approach can carry out accurate simulation tests for systems operating in a wide range of configurations and created from new materials.
GC- and UHPLC-MS Profiles as a Tool to Valorize the Red Alga Asparagopsis armata
Authors: Pinto Diana C. G. A. , Lesenfants Marie L. , Rosa Gonçalo P. , Barreto Maria Carmo , Silva Artur M. S. , Seca Ana M. L.
Published: January 2022

Asparagopsis armata Harvey is a red alga native from the southern hemisphere and then introduced in the Mediterranean Sea and the Atlantic Ocean, including the Azores Archipelago, where it is considered an invasive alga. Some studies show that the extracts exhibit antimicrobial and antifouling activities, and it is incorporated in some commercialized cosmetic products. (e.g., Ysaline®). However, knowledge of this species chemical composition is scarce. The GC-MS and UHPLC-MS profiles of both the nonpolar and polar extracts were established to contribute to this problem solution. According to the results, A. armata is rich in a great structural variety of halogenated lipophilic and aromatic compounds, some of them identified here for the first time. In the lipophilic extract, 25 compounds are identified, being the halogenated compounds and fatty acids, the two major compound families, corresponding to 54.8% and 35.7% of identified compounds (224 and 147 mg/100 g of dry algae, respectively). The 1,4-dibromobuten-1-ol and the palmitic acid are the two most abundant identified compounds (155 and 83.4 mg/100 g of dry algae, respectively). The polar extract demonstrated the richness of this species in brominated phenolics, from which the cinnamic acid derivatives are predominant. The results obtained herein open new perspectives for valuing the A. armata as a source of halogenated compounds and fatty acids, consequently improving its biotechnological and economic potential. Promoting this seaweed and the consequent increase in its demand will contribute to biodiversity conservation and ecosystem sustainability.
Initialisation Approaches for Population-Based Metaheuristic Algorithms: A Comprehensive Review
Authors: Agushaka Jeffrey O. , Ezugwu Absalom E.
Published: January 2022

A situation where the set of initial solutions lies near the position of the true optimality (most favourable or desirable solution) by chance can increase the probability of finding the true optimality and significantly reduce the search efforts. In optimisation problems, the location of the global optimum solution is unknown a priori, and initialisation is a stochastic process. In addition, the population size is equally important; if there are problems with high dimensions, a small population size may lie sparsely in unpromising regions, and may return suboptimal solutions with bias. In addition, the different distributions used as position vectors for the initial population may have different sampling emphasis; hence, different degrees of diversity. The initialisation control parameters of population-based metaheuristic algorithms play a significant role in improving the performance of the algorithms. Researchers have identified this significance, and they have put much effort into finding various distribution schemes that will enhance the diversity of the initial populations of the algorithms, and obtain the correct balance of the population size and number of iterations which will guarantee optimal solutions for a given problem set. Despite the affirmation of the role initialisation plays, to our knowledge few studies or surveys have been conducted on this subject area. Therefore, this paper presents a comprehensive survey of different initialisation schemes to improve the quality of solutions obtained by most metaheuristic optimisers for a given problem set. Popular schemes used to improve the diversity of the population can be categorised into random numbers, quasirandom sequences, chaos theory, probability distributions, hybrids of other heuristic or metaheuristic algorithms, Lévy, and others. We discuss the different levels of success of these schemes and identify their limitations. Similarly, we identify gaps and present useful insights for future research directions. Finally, we present a comparison of the effect of population size, the maximum number of iterations, and ten (10) different initialisation methods on the performance of three (3) population-based metaheuristic optimizers: bat algorithm (BA), Grey Wolf Optimizer (GWO), and butterfly optimization algorithm (BOA).
Features of Bread Made from Different Amaranth Flour Fractions Partially Substituting Wheat Flour
Authors: Coţovanu Ionica , Mironeasa Silvia
Published: January 2022

Amaranth flour (AF) is recognized as high-quality raw material regarding nutrients and bioactive compounds, essential in supplying human health benefits, compared with white flour (WF). In this study, the effects of factors, different particles sizes (large, medium, and small), and levels of AF (5, 10, 15, and 20%) substituting WF on the responses, empirical and dynamic dough rheological properties, and some quality parameters of bread were successfully modeled using predictive models. Finally, the optimization of a formulation to maximize the AF level whilst maintaining bread quality for each type of particle size (PS) was performed based on the response surface methodology models generated. The rheological properties of the composite flour formulated were evaluated using Mixolab, alveograph, rheofermentometer, and dynamic rheometer. In addition, bread quality parameters, loaf volume, instrumental texture features, and firmness were evaluated. The anticipation of the optimal value for each response in terms of dough rheological properties during mixing, protein weakening, starch gelatinization and retrogradation, biaxial extension, fermentation, viscoelastic moduli, and creep and recovery compliance depending on PS. The optimal addition level was determined by a multi-objective optimization approach. The optimal addition level was 9.41% for large, 9.39% for medium, and 7.89% for small PS. The results can help manufacturers to develop bread products with the desired particle size with optimal technological and physical features.
Experimental Study of Methane Combustion Efficiency in a High-Enthalpy Oxygen-Containing Flow
Authors: Grishin Ilya , Zakharov Vyacheslav , Aref’ev Konstantin
Published: January 2022

The article presents the experimental study analysis results of the methane combustion efficiency in a high-enthalpy oxygen-containing flow (HOF) inside of constant cross-section channel, finite along the length. The range of initial HOF enthalpies was considered from 350 to 700 kJ/kg. The regularities of the HOF initial enthalpy influence on the methane combustion efficiency were obtained. The values of the fuel excess coefficient under which the maximum coefficients of methane combustion completeness in the HOF are realized were determined. The data obtained indicate the realization of transitional diffusion-kinetic modes of methane combustion and make it possible to assess the factors limiting the combustion process.
The Status and Trend of Chinese News Forecast Based on Graph Convolutional Network Pooling Algorithm
Authors: Han Xiao , Peng Jing , Peng Tailai , Chen Rui , Hou Boyuan , Xie Xinran , Cui Zhe
Published: January 2022

It is always a hot issue in the intelligence analysis field to predict the trend of news description by pre-trained language models and graph neural networks. However, there are several problems in the existing research: (1) there are few Chinese data sets on this subject in academia and industry; and (2) using the existing pre-trained language models and graph classification algorithms cannot achieve satisfactory results. The method described in this paper can better solve these problems. (1) We built a Chinese news database predicted by more than 9000 annotated news time trends, filling the gaps in this database. (2) We designed an improved method based on the pre-trained language model and graph neural networks pooling algorithm. In the graph pooling algorithm, the Graph U-Nets Pooling method and self-attention are combined, which can better solve the analysis of the problem of forecasting the development trend of news events. The experimental results show that the effect of this method compared with the baseline graph classification algorithm is improved, and it also solves the shortcomings of the pre-trained language model that cannot handle very long texts. Therefore, it can be concluded that our research has strong processing capabilities for analyzing and predicting the development trend of Chinese news events.
Size-Dependent Cytotoxic and Molecular Study of the Use of Gold Nanoparticles against Liver Cancer Cells
Authors: Al-Khedhairy Abdulaziz A. , Wahab Rizwan
Published: January 2022

The size of nanomaterials influences physicochemical parameters, and variations in the size of nanomaterials can have a significant effect on their biological activities in cells. Due to the potential applicability of nanoparticles (NPs), the current work was designed to carry out a size-dependent study of gold nanoparticles (GNPs) in different dimensions, synthesized via a colloidal solution process. Three dissimilar-sized GNPs, GNPs-1 (10–15 nm), GNPs-2 (20–30 nm), and GNPs-3 (45 nm), were prepared and characterized via transmission electron microscopy (TEM), high-resolution TEM (HR-TEM), hydrodynamic size, zeta potential, and UV-visible spectroscopy, and applied against liver cancer (HepG2) cells. Various concentrations of GNPs (1, 2, 5, 10, 50, and 100 µg/mL) were applied against the HepG2 cancer cells to assess the percentage of cell viability via MTT and NRU assays; reactive oxygen species (ROS) generation was also used. ROS generation was increased by 194%, 164%, and 153% for GNPs-1, GNPs-2, and GNPs-3, respectively, in the HepG2 cells. The quantitative polymerase chain reaction (qPCR) data for the HepG2 cells showed up-regulation in gene expression of apoptotic genes (Bax, p53, and caspase-3) when exposed to the different-sized GNPs, and defined their respective roles. Based on the results, it was concluded that GNPs of different sizes have the potential to induce cancer cell death.
Application of Experimental Measurements in a Wind Tunnel to the Development of a Model for Aerodynamic Drag on Elite Slalom and Giant Slalom Alpine Skiers
Authors: Majerič Matej , Verdel Nina , Ogrin Jan , Holmberg Hans-Christer , Supej Matej
Published: January 2022

Aerodynamic drag is a major cause of energy losses during alpine ski racing. Here we developed two models for monitoring the aerodynamic drag on elite alpine skiers in the technical disciplines. While 10 skiers assumed standard positions (high, middle, tuck) with exposure to different wind speeds (40, 60, and 80 km/h) in a wind tunnel, aerodynamic drag was assessed with a force plate, shoulder height with video-based kinematics, and cross-sectional area with interactive image segmentation. The two regression models developed had 3.9–7.7% coefficients of variation and 4.5–16.5% relative limits of agreement. The first was based on the product of the coefficient of aerodynamic drag and cross-sectional area (Cd∙S) and the second on the coefficient of aerodynamic drag Cd and normalized cross-sectional area of the skier Sn, both expressed as a function of normalized shoulder height (hn). In addition, normative values for Cd (0.75 ± 0.09–1.17 ± 0.09), Sn (0.51 ± 0.03–0.99 ± 0.05), hn (0.48 ± 0.03–0.79 ± 0.02), and Cd∙S (0.23 ± 0.03–0.66 ± 0.09 m2) were determined for the three different positions and wind speeds. Since the uncertainty in the determination of energy losses due to aerodynamic drag relative to total energy loss with these models is expected to be <2.5%, they provide a valuable tool for analysis of skiing performance.
Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology
Authors: Ahmad Afaq , Ullah Zahid , Khalid Muhammad , Ahmad Naveed
Published: January 2022

The fast increase in adoption and development of Electric Vehicles (EVs) has invited a significant challenge to the existing charging management techniques and infrastructure. It is necessary to efficiently manage a large number of mobile EVs. As compared to fuel and gasoline type vehicles, the EV has a limited driving range and needs to recharge its battery frequently during long journeys. Hence, with plug-in charging services one major concern is the long duration of battery recharging. In this paper, we employ heterogeneous BS (Battery Switching) technology to provide an alternative charging option to minimize the charging duration of EV. Furthermore, enabling BS reservation in a centralized manner for mobile EVs, load balancing algorithm and optimal selection of Battery Switching Station (BSS) across the network are proposed. In addition, we suggest a scheduling technique for depleted batteries to recharge effectively in BSS to minimize power loss and queuing time at selected BSS. We have conducted a performance evaluation by comparing the proposed scheme with other benchmarks, in terms of average trip duration, total trip energy consumption, etc. Finally, it is proven that the battery stock is managed across the network efficiently through the proposed scheme.
Bioinspired NEMS—Prospective of Collaboration with Nature
Authors: Simovic-Pavlovic Marina , Bokic Bojana , Vasiljevic Darko , Kolaric Branko
Published: January 2022

The fields of micro- and nanomechanics are strongly interconnected with the development of micro-electro-mechanical (MEMS) and nano-electro-mechanical (NEMS) devices, their fabrication and applications. This article highlights the biomimetic concept of designing new nanodevices for advanced materials and sensing applications.
Feasibility of Using Computer Vision and Artificial Intelligence Techniques in Detection of Some Apple Pests and Diseases
Authors: Abbaspour-Gilandeh Yousef , Aghabara Abdollah , Davari Mahdi , Maja Joe Mari
Published: January 2022

There are many methods to detect plant pests and diseases, but they are primarily time-consuming and costly. Computer vision techniques can recognize the pest- and disease-damaged fruits and provide clues to identify and treat the diseases and pests in their early stages. This study aimed to identify common pests, including the apple capsid (Plesiocoris rugicollis)/AC, apple codling moth (Cydia pomonella)/ACM, Pear lace bug (Stephanitis pyri)/PLB, and one physiological disease-apple russeting/AR in two cultivars, Golden Delicious and Red Delicious, using the digital image processing and sparse coding method. The Sparse coding method is used to reduce the storage of the elements of images so that the matrix can be processed faster. There have been numerous studies on the identification of apple fruit diseases and pests. However, most of the previous studies focused only on diagnosing a pest or disease, not on computational volume reduction and rapid detection. This research focused on the comprehensive study on identifying pests and diseases of apple fruit using sparse coding. The sparse coding algorithm in this work was designed using Matlab software. The apple pest and disease detection were performed based on 11 characteristics: R, G, B, L, a, b, H, S, V, Sift, and Harris. The class detection accuracy using the sparse coding method was obtained for 10 classes with three views of apple for S. pyri of red apple as 81%, S. pyri of golden apple as 88%, golden apple russeting as 85%, S. pyri and russeting of red apple as 100%, S. pyri and russeting of golden apple as 80%, codling moth of red apple as 86%, codling moth of golden apple as 72%, S. pyri of red apple as 83%, S. pyri of golden apple as 90%, codling moth and S. pyri of red apple as 80%, and codling moth and S. pyri of golden apple as 67%. The total processing time for developing the dictionary was 220 s. Once the dictionary was developed, pest and disease detection took only 0.175 s. The results of this study can be useful in developing automatic devices for the early detection of common pests and diseases of apples. Although the study was focused on apple diseases, results for this work have huge potential for other crops.
Large-Scale Printed Chinese Character Recognition for ID Cards Using Deep Learning and Few Samples Transfer Learning
Authors: Li Yi-Quan , Chang Hao-Sen , Lin Daw-Tung
Published: January 2022

In the field of computer vision, large-scale image classification tasks are both important and highly challenging. With the ongoing advances in deep learning and optical character recognition (OCR) technologies, neural networks designed to perform large-scale classification play an essential role in facilitating OCR systems. In this study, we developed an automatic OCR system designed to identify up to 13,070 large-scale printed Chinese characters by using deep learning neural networks and fine-tuning techniques. The proposed framework comprises four components, including training dataset synthesis and background simulation, image preprocessing and data augmentation, the process of training the model, and transfer learning. The training data synthesis procedure is composed of a character font generation step and a background simulation process. Three background models are proposed to simulate the factors of the background noise patterns on ID cards. To expand the diversity of the synthesized training dataset, rotation and zooming data augmentation are applied. A massive dataset comprising more than 19.6 million images was thus created to accommodate the variations in the input images and improve the learning capacity of the CNN model. Subsequently, we modified the GoogLeNet neural architecture by replacing the fully connected layer with a global average pooling layer to avoid overfitting caused by a massive amount of training data. Consequently, the number of model parameters was reduced. Finally, we employed the transfer learning technique to further refine the CNN model using a small number of real data samples. Experimental results show that the overall recognition performance of the proposed approach is significantly better than that of prior methods and thus demonstrate the effectiveness of proposed framework, which exhibited a recognition accuracy as high as 99.39% on the constructed real ID card dataset.
The Effect of Terpenoid Compounds on the Formation of Advanced Glycation Endproducts (AGEs) in Model Systems
Authors: Vlassopoulos Antonis , Mikrou Theano , Papantoni Artemis , Papadopoulos Georgios , Kapsokefalou Maria , Mallouchos Athanasios , Gardeli Chrysavgi
Published: January 2022

Background: Terpenoid compounds, despite their established antioxidant ability, are neglected as potential glycation regulators. Methods: In-vitro model systems of lysine (0.1 M) with glucose (0.1 M and 1 M) were incubated at 80 °C and 100 °C for 3 h in the presence of aniseed oil, thymol and linalool (2–8 μΜ). Color development, absorbance at UV-Vis (280 nm, 360 nm, 420 nm), fluorescence intensity (λexc = 370 nm, λemm = 440 nm) and lysine depletion (HPLC-FL) were measured to monitor the progress of the Maillard reaction. Response Surface Methodology was used to analyze the impact of the five experimental conditions on the glycation indices. Results: All terpenoid compounds promoted color development and did not affect lysine depletion. The choice of terpenoid compound impacted glycation at 280 nm, 360 nm and 420 nm (p < 0.02). The effect was stronger at lower temperatures (p < 0.002) and 0.1 M glucose concentrations (p < 0.001). Terpenoid concentration was important only at 360 nm and 420 nm (p < 0.01). No impact was seen for fluorescence intensity from the choice of terpenoid compounds and their dose (p = 0.08 and p = 0.44 respectively). Conclusion: Terpenoid compounds show both anti- and proglycative activity based on the incubation conditions. Thymol showed the largest antiglycative capacity, followed by aniseed oil and linalool. Maximal antiglycative capacity was seen at 0.1 M glucose, 2 μΜ terpenoid concentration, 80 °C and 1 h incubation.
Quantitative Evaluation of Light Collimating for Commercial UV-LEDs Based on Analytic Collimating Lens
Authors: Syu Yong-Sin , Lee Yung-Chun
Published: January 2022

This paper proposes a lens design method for effectively collimating the light emitting from a light-emitting diode (LED). This collimating lens contains two aspherical lens surfaces which can be mathematically characterized using a few designing parameters, and hence is called an analytic collimating lens. An optical ray-tracing algorithm has been developed for these analytic collimating lenses to analyze their optical performance and to optimize their designs. Six high-power and commercially available ultraviolet (UV) LEDs are chosen as examples for demonstrating the optimal collimating lens design. For each UV-LED, the corresponding optical collimating lens is determined by inputting the ray data file provided by the manufacture over a finite-size emitting area. The divergent angles of the six UV-LEDs have been successfully collimated to a narrow range in between 1.56° to 2.84° from their original radiation angle around 46° to 120°. Furthermore, the proposed analytical collimating lenses are suitable for mass-production using standard mold injection methods, and hence possess great potentials for industry applications of LEDs.